Agenda packet — Belmont City Council, September 10, 2024 (part 2 of 4)

6. ADEQUATE SITES
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915-945 RALSTON AVENUE AND 940 EMMETT STREET (SITE R)
APN Address Acres Existing Use
Improv/
Land
Ratio
Total
Capacity
Building
Age
Building
Stories
045-182-040 915 Ralston Avenue 0.13 Vacant retail 0.80 10 1970 1 045-182-030 925 Ralston Avenue 0.13 Retail store parking lot 0 10 N/A N/A 045-182-200 940 Emmett Street 0.17 Office parking 0 12 N/A N/A 045-182-210 940 Emmett Street 0.31 Professional Offices 0.46 23 1972 2 045-182-020 945 Ralston Avenue 0.15
Multi-unit commercial
restaurant/service
retail

0.54 12 1960 1
TOTAL 0.89 0-0.80 68
This housing site is comprised of five lots totaling 0.89 acres after consolidation and is currently zoned Village Corridor (VC). The sites are owned by a single owner who has expressed interest in redeveloping the site. The buildings are over 50 years old and currently have vacancies, therefore the existing use should not be considered an impediment to redevelopment. A density of 75 du/acre was used to calculate a realistic capacity of 68 units. This site is similar to the 608 Harbor pipeline project, which consolidated four parcels resulting in a 0.71-acre site and 103 units.
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6. ADEQUATE SITES
B ELMONT H OUSING E LEMENT 2023 - 2031 6-43
1085 SIXTH AVENUE AND 995 RALSTON AVENUE (SITE S)
APN Address Acres Existing Use
Improv/
Land
Ratio
Total
Capacity
Building
Age
Building
Stories
045-182-220 1085 Sixth Avenue 0.17 City Hall parking lot 0 13 N/A N/A 045-182-010 995 Ralston Avenue 0.36 Gas station and auto repair 0.07 27 1974 1
TOTAL 0.53 0-0.07 40
Site S includes two lots totaling 0.53 acres after consolidation and is currently zoned Village Corridor (VC). 1085 Sixth Avenue is a City-owned site which is being used as a parking lot on an interim basis pending future redevelopment. The adjacent property is a 50-year-old building used as a gas station and auto repair shop and has a very low ILR, therefore the existing uses should not be considered an impediment to redevelopment. There has been prior development interest in this site although no planning applications were submitted. A density of 75 du/acre was used to calculate a realistic capacity of 40 units. 277

6. ADEQUATE SITES
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1520 El Camino Real and 1538 El Camino Real (Site T)
APN Address Acres Existing Use
Improv/
Land
Ratio
Total
Capacity
Building
Age
Building
Stories
045-253-300 1520 El Camino Real 0.20 Used car lot 0.09 15 1959 1 045-253-290 1538 El Camino Real 0.47 Multi-unit retail and service uses strip mall 0.43 35 1988 1
TOTAL 0.67 0.09-0.43 50
This housing site includes two lots totaling 0.67 acres after consolidation. 1520 El Camino Real is currently zoned Village Corridor Mixed Use (VCMU) and 1538 El Camino Real is currently zoned Corridor Mixed Use (CMU). The commercial strip mall at 1538 El Camino has several vacancies. Given the low ILR and single-story buildings, the existing uses at this site are not considered an impediment to consolidation and redevelopment. There has been no development interest to date on this site. A density of 75 du/acre was used to calculate a realistic capacity of 50 units.
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6. ADEQUATE SITES
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1501 EL CAMINO REAL (SITE U)
APN Address Acres Existing Use
Improv/
Land
Ratio
Total
Capacity
Building
Age
Building
Stories
045-252-080 1501 El Camino Real 1.02 Multi-unit commercial retail strip center 0.39 76 1980 1
TOTAL 1.02 0.39 76
This housing site is 1.02 acres and is currently zoned Corridor Mixed Use (CMU). The property is used as a commercial retail strip center with both tuck-under and surface parking. The property currently has multiple vacant spaces. Given the age of the building and low ILR, the existing uses at this site are not considered an impediment to redevelopment. There has been no development interest to date on this site. A density of 75 du/acre was used to calculate a realistic capacity of 76 units.
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6. ADEQUATE SITES
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1601 EL CAMINO REAL (SITE V)
APN Address Acres Existing Use
Improv/
Land
Ratio
Total
Capacity
Building
Age
Building
Stories
045-252-100 1601 El Camino Real 1.68 Multi-unit commercial retail strip center 0.20 126 1958 1
TOTAL 1.68 0.20 126
This housing site is 1.68 acres and is currently zoned Corridor Mixed Use (CMU). This property is a commercial retail/office strip center with ample surface parking. There are currently several vacancies in the strip center. Given the buildings are over 60 years old, have a low ILR, are single-story, and have vacancies, the existing uses at this site are not considered an impediment to redevelopment. There has been no development interest to date on this site.

This site is similar to the pending project at 580 Masonic Way, a 1.26-acre site with 139 units proposed and an ILR of 0.32. A density of 75 du/acre was used to calculate a realistic capacity of 126 units.
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6.5 SITES SUMMARY
State Housing Element Law requires local governments to prepare an inventory of land suitable for residential development, including vacant sites, sites having the potential for redevelopment, and an analysis of the relationship of zoning, public facilities, and services to these sites. The inventory of land suitable for residential development must be used to identify sites that can be developed for housing within the planning period.

Table 6-11 summarizes the City of Belmont’s capacity to meet RHNA goals.

TABLE 6-11: SITES INVENTORY AFFORDABILITY BREAKDOWN
Housing Opportunity Sites
Very
Low-Income
LowIncomeModerateIncome
Above
ModerateIncome Total
2023-2031 RHNA 488 281 283 733 1,785
Pipeline Projects 131 175 21 487 814
Pending Projects 63 13 11 122 209
Projected ADUs 0 0 90 0 90
RHNA Credit Subtotal 194 188 122 609 1,113
Opportunity Sites 322 184 186 484 1,176
Total 516 372 308 1,093 2,289
Buffer 28 91 25 360 504
Buffer % 6% 32% 9% 49% 28%
Source: City of Belmont, 2024.

RHNA BUFFER
In 2017, Senate Bill (SB) 166 was signed into law and included new “no net loss” provisions that require communities to provide an ongoing, adequate supply of land resources for housing development during the entirety of the housing element update planning period. These provisions mean communities face risks of non-compliance should a housing site be developed with non-residential uses, lower residential densities, or residential uses at affordability levels higher than anticipated by the housing element. To avoid non-compliance, HCD advises communities to “buffer” their assigned RHNA numbers. The City of Belmont proposes a 28% buffer of 504 housing units, bringing the City’s proposed potential development to 2,289 housing units, as shown in Table 6-11 above.
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B ELMONT H OUSING E LEMENT 2023 - 2031 7-1
7 HOUSING GOALS,

POLICIES, AND

PROGRAMS
California Government Code Section 65583(b)(1) requires the Housing Element to contain “a statement of goals, quantified objectives, and policies relative to the maintenance, preservation, and development of housing.” Three types of statements are included in this section: goals, policies, and programs. Goals express broad, long-term statements for desired outcomes. The City has developed five goals pursuant to HCD requirements for the 6th Cycle relate to housing production, removal of constraints, housing preservation, promoting access to housing opportunities, and affirmatively furthering fair housing (AFFH).

Each goal is followed by policies intended to guide decision makers, staff, and other City representatives on how to achieve the goals. Specific programs are included to ensure the effective implementation of the policies. As required by law, quantified objectives have been developed for housing production, rehabilitation, and conservation. These are presented at the end of this section. The quantified objectives provide metrics for evaluating the effectiveness of the Element.

7.1 GOALS, POLICIES, AND IMPLEMENTING PROGRAMS
GOAL H1: PRODUCE NEW HOUSING AT ALL INCOME LEVELS, WITH A FOCUS ON AFFORDABLE HOUSING.

To meet the targets set by RHNA, the city will facilitate the production of abundant and affordable new housing in a wide diversity of unit types and sizes. 283

7. HOUSING GOALS, POLICIES, AND PROGRAMS
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Policy H1.A: Provide adequate capacity to meet the Sites Inventory for Regional Housing Needs Allocation (RHNA).

Policy H1.B: Encourage a range of both market-rate and affordable housing in a variety of unit sizes and types to accommodate the varied housing needs of diverse households.

Policy H1.C: Coordinate with the local water and sewer agencies to assist in planning for adequate water and sewer service.

Program H1.1: Monitor Regional Housing Need Allocation and Residential Capacity.

To ensure sufficient residential capacity is maintained to accommodate the RHNA for each income category throughout the planning period, continue to implement a formal, project-by-project evaluation procedure pursuant to Government Code section 65863.

Quantified Objectives:
 The City will track the number of units that have been constructed at each income level and the number of units to be built on the identified site to determine the remaining site capacity by income category. The records will be updated continuously as developments are approved.
 If a development is being approved on an identified site at a lower density than what was assumed in the Housing Element, additional adequate sites must be made available within 180 days of approving the development.

Geographic Target: Citywide
Implementation Timeline: 2024 - 2031 ongoing as projects are approved Responsible Body: Housing and Planning Divisions
Funding Source(s): Community Development Department Budget Program H1.2: Use Public Funding for Low/Moderate Income Housing. Use City affordable housing funds to produce additional affordable housing projects and to leverage other regional, state, and federal funding sources to support the construction of affordable housing.

Quantified Objectives:
 The City shall utilize local Affordable Housing Funds (Successor Agency Housing Funds, Inclusionary housing in-lieu funds, Commercial Linkage Fees, and Residential Development Mitigation Fees) to fund affordable housing development, and to leverage other public funding sources for affordable housing projects. Priority shall be given to development of housing at lower-income levels.
 Available and projected Affordable Housing Funds can leverage the production of 100 units during the planning period.
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Geographic Target: Citywide
Implementation Timeline:
 2024-2031 (Ongoing as developers apply for affordable housing projects).

Responsible Body: Housing Division
Funding Source(s): Affordable Housing Funds
Program H1.3: Water and Sewer Providers. Ensure immediate delivery of the Housing Element to water and sewer providers to facilitate streamline reviews and ensure adequate capacity for housing projects.

Quantified Objectives:
 Water and sewer service providers must establish specific procedures to grant priority water and sewer service to developments with units affordable to lowerincome households based on jurisdictions' Housing Element's RHNA allocation (Gov. Code, Section 65589.7.) The City will immediately deliver the housing element to water and sewer service providers.

Geographic Target: Citywide
Implementation Timeline:
 Upon adoption in Spring 2024, the City will immediately send the Housing Element to applicable water and sewer providers.

Responsible Body: Planning Division
Funding Source(s): Community Development Department Budget Program H1.4: Establish By-Right Housing Designation for Prior Housing Sites.

Designate housing sites that have carried over from the prior Housing Element to allow housing development by-right consistent with State law.

Quantified Objectives:
 Amend the Zoning Code to establish a "by-right" designation for housing sites reused from prior Housing Elements for housing projects that propose a minimum of 20% affordable units.

Geographic Target: Specific Sites
Implementation Timeline:
 Completed in January 2024.

Responsible Body: Planning Division
Funding Source(s): Community Development Department Budget 285

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Program H1.5: Facilitate Pipeline and Pending Projects. The City will facilitate and support pipeline and pending projects during the planning period by working with applicants to ensure reviews are done in a timely manner, providing technical assistance, and limiting public meetings as required by SB 330. As needed, the City will provide incentives or additional assistance like expediting project review, supporting funding applications, and working to avoid unnecessary delays in processing of the applications.

Quantified Objectives:
 For each housing project, maintain a designated project planner and engineer, as well as a senior manager from both the Community Development Department and Public Works Department to help facilitate the project and monitor progress.  1,023 units (including 194 very low-, 188 low-, 32 moderate-, and 609 abovemoderate income units) constructed by end of planning period Geographic Target: Citywide
Implementation Timeline:
 Ongoing
Responsible Body: Planning Division
Funding Source(s): Community Development Department Budget GOAL H2: PRESERVE EXISTING HOUSING THAT IS AFFORDABLE TO LOWER- AND MIDDLE-INCOME RESIDENTS.

As the City continues to grow, it remains important to maintain and preserve existing affordable housing as well as non-deed restricted housing that is naturally affordable for middle and lower-income households.

Policy H2.A: Continue to monitor, track, and encourage preservation of affordable housing atrisk of loss or conversion to market rate housing.

Policy H2.B: Continue partnering with housing service organizations to preserve existing affordable housing.

Policy H2.C: Invest funding into the purchase and preservation of affordable housing.

Program H2.1: Support Retention of Existing Lower-Income Units. Preserve “at-risk” affordable units through monitoring and partnering, working with nonprofits, and exploring available funding sources to preserve affordability. This activity will include both units in all affordable developments with expiring deed restrictions, as well as potential BMR units that are reaching the end of the term. 286

7. HOUSING GOALS, POLICIES, AND PROGRAMS
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Quantified Objectives:
 Advertise units going to sale to nonprofits.
 Outreach and negotiate with owners for affordability extensions.  Provide tenant education and affirmatively market available units to affected tenants.
 Objective: 106 units over the cycle.

Geographic Target: Citywide
Implementation Timeline:
 Annually, at the time of APR preparation, review the list of potentially at-risk units within the next ten years. In addition, in Q1, reach out to any owners regarding potential affordability extensions. Assist in the provision of tenant education by owners and nonprofit stakeholders. Liaise with nonprofits in Q2 to update them on potential acquisition opportunities. Ensure compliance with State Preservation Notice Law.
 In Q1 2025, draft preferences for any new affordable projects for displaced tenants in at-risk properties. Bring recommended language to CC for adoption in Q4 2025 and implement in Q1 2026.

Responsible Body: Housing Division
Funding Source(s): Housing Division Budget
Program H2.2: Manage Portfolio of Deed Restricted Affordable Units. The City will formalize its method of managing the City’s deed restricted units by identifying a service provider or developing additional staff capacity.

Quantified Objective:
 Review best practices and evaluate staff resources to manage the portfolio of units. Make a determination on the best way to manage the units.  If the outside provider approach is selected, develop a Request for Proposals to distribute to Bay Area service providers to manage existing and new affordable units, both for sale and rental; select a provider and begin transitioning this work to the provider.

Geographic Target: Citywide
Implementation Timeline:
 In Q3 2024, conduct analysis and determine whether to proceed with a service provider or staff approach.
 If a service provider approach is selected, launch RFP in Q1 2025; select provider and implement program in Q4 2025.

Responsible Body: Housing Division
Funding Source(s): Housing Division Budget
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Program H2.3: Require Replacement Units. Adopt a policy requiring replacement units subject to the requirements of Government Code Section 65915 (c)(3) when new development occurs on a housing inventory site which currently has or within the past five years had residential uses (existing, vacated or demolished) and was legally restricted to low-income households, or subject to price control, or occupied by lowincome households. Require that demolition permits include an assessment of rents to determine income status and plan to replace lost lower-income units.

Quantified Objectives:
 Adopt a policy requiring new housing development to replace all affordable housing units lost due to new development on site, at equal or greater levels of affordability.

Geographic Target: Citywide
Implementation Timeline:
 Conduct best practices review beginning in Q1 2025 on replacement options that would extend past 2034, including conferring with neighboring jurisdictions interested in the same outcomes; bring recommendations to City Council in Q3 2025 and implement approved policy in Q4 2025.

Responsible Body: Housing Division
Funding Source(s): Housing Division Budget
Program H2.4: Rehabilitation of Existing Housing Occupied by Lower-Income Households. The City will partner with and provide financial assistance, outreach, or resources to support housing service organizations and/or non-profit organizations that help preserve existing housing that is affordable to lower-income residents by providing home repairs and energy-efficiency improvements for low-income households.

Quantified Objectives:
 Establish partnerships with organizations that provide repair and energyefficiency improvements for properties occupied by low-income residents, such as Peninsula Clean Energy, El Concilio of San Mateo County, and Rebuilding Together Peninsula, and explore opportunities to increase their reach in Belmont through enhanced financial assistance and targeted outreach to lower-income households.
 Continue to coordinate with housing service providers, non-profit housing developers, and affordable housing property managers to support their rehabilitation efforts.
 20 units occupied by low-income households over the cycle will undergo energyefficiency improvements or home repairs.

Geographic Target: Citywide
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Implementation Timeline:
 Outreach to housing service providers bi-annually to confer on resources available and opportunities for partnerships, beginning in Q4 2024.

Responsible Body: Housing Division
Funding Source(s): Affordable Housing Funds
Program H2.5: Preserve Existing Affordable Units. Develop a plan to preserve the City's affordable units that will expire in the next decade to keep them affordable long term.

Quantified Objectives:
 Work with property owners of existing assisted housing developments for lowerincome households and partner with nonprofits to determine methods to extend affordability covenants to preserve affordable units, including assistance from the City.
 Conduct best practices research on other jurisdictions' programs and prepare recommendations to City Council.

Geographic Target: Citywide
AFFH Action Area: Protect existing residents from displacement Implementation Timeline:
 Conduct best practices work in Q3 2025; bring recommendations to Council in the Q1 2026; implement program by mid-2026.

Responsible Body: Housing Division
Funding Source(s): Affordable Housing Funds
GOAL H3: PROMOTE ACCESS TO HOUSING OPPORTUNITIES FOR LOW-INCOME HOUSEHOLDS AND PERSONS WITH SPECIAL HOUSING NEEDS.

The city can improve access to housing for all income groups and special needs communities by providing education and information on specific programs and affordable housing opportunities offered locally, regionally, and by the state.

Policy H3.A: Increase access to homeownership opportunities for lower income households.

Policy H3.B: Increase access and awareness of housing programs and affordable housing unit availability through use of new technology as part of a robust and proactive public outreach strategy.
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Program H3.1: Home Ownership Financing. Support access to home ownership opportunities and connect potential homeowners to financing sources specifically targeted to first time homebuyers or affordable housing units.

Quantified Objective:
 Partner with housing organizations and financing stakeholders to host at least one first time homebuyer workshop in Belmont during the planning period.

Geographic Target: Citywide
Implementation Timeline:
 In Q3 2025 and every three years after, partner with stakeholders, including HEART, to offer first time homebuyer workshops in Belmont.

Responsible Body: Housing Division
Funding Source(s): Housing Division Budget
Program H3.2: Continue to Participate in Countywide Below Market Rate Unit Web Portal. San Mateo County and multiple other jurisdictions collaborate on a web portal that includes affordable housing units available for rent, online applications, and access to the waitlist for future units.

Quantified Objective:
 Support the County in maintaining online portal for a BMR applications and waitlist.
 Promote the County’s online portal through the City’s website.  Modify developer agreements when appropriate to require developers to use the Countywide portal.

Geographic Target: Citywide
Implementation Timeline: Ongoing as projects complete construction Responsible Body: Housing Division and San Mateo County Funding Source(s): Housing Division Budget
GOAL H4: REMOVAL OF CONSTRAINTS OF THE PRODUCTION OF HOUSING.

The city can further the production of housing to meet RHNA goals by eliminating governmental policies or regulations that unnecessarily constrain the development or improvement of market-rate or affordable housing.

Policy H4.A: Periodically review and update the Zoning Ordinance to remove language that constrains development and stay abreast of updates to State law to reduce constraints to emergency shelters, low barrier navigation centers, supportive housing, and group homes. 290

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Policy H4.B: Reduce constraints to housing development by increasing floor area ratios and density, waiving lot consolidation permit fees, and reducing parking requirements.

Policy H4.C: Provide clear and transparent information on the City’s website regarding development standards, the development review process, and associated fees.

Program H4.1: Update Zoning Code to Increase Floor Area Ratios and Density.

Modify the Zoning Ordinance to allow for increased floor area ratios and density to better facilitate development projects.

Quantified Objectives:
 Modify the Corridor Mixed Use (CMU) zoning district to increase the maximum allowed Floor Area Ratio (FAR) from 1.75 (2.2 with community benefits) to 2.0 (2.5 with community benefits), and to eliminate the maximum residential density metric.
 Modify the Village Station Core (VSC) zoning district to increase the maximum allowed FAR from 1.5 (2.0 with community benefits) to 2.0 (2.5 with community benefits).

Geographic Target: CMU and VSC districts
Implementation Timeline:
 Completed in January 2024
Responsible Body: Planning Division
Funding Source(s): Community Development Department Budget Program H4.2: Zoning Code Amendments to Remove Constraints. The City will annually review, and amend as necessary, the Zoning Code to ensure consistency with State Housing Government Code requirements and remove or lessen constraints on new housing development, pertaining to, but not limited to:
 Emergency Shelters: Ensure full compliance with State laws pertaining to housing for homeless persons, including removing the following constraints:

1. Define emergency shelters to include associated uses such as low barrier navigation centers, bridge housing, respite/recuperative care, and other inclusive terms for shelters.

2. Update parking requirements to comply with AB139/Government Code section 65583, subdivision (a)(4)(A), AB 2339, and any other parking requirements.

3. Increase the maximum number of beds allowed by-right in the S-2 Combining District to 20, with a commitment to review this limit in 2027 based on updated homeless population counts to determine if the limit should be increased.
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 Permanent Supportive Housing. Amend the Zoning Code to ensure consistency with AB 2162 by allowing by-right 100% affordable housing that has 25% or 12 units of permanent supportive housing, where multi-family or mixed-use housing is permitted.
 Transitional and Supportive Housing. Amend the Zoning Code to permit transitional housing and supportive housing as a residential use in all zones allowing residential uses and only subject to those restrictions that apply to other residential dwellings of the same type in the same zone. (Gov. Code, Section 65583, subd. (c)(3).)
 Low-Barrier Navigation Centers: Amend the Zoning Code to allow low-barrier navigation centers for the homeless by right in zones that allow for mixed-use and nonresidential zones permitting multi-family uses, per Government Code Section 65662.
 Density Bonus: Comply with changes in California's density bonus law (Government Code Section 65915, as revised) and promote the density bonus through the City website and/or informational brochures that will be displayed at the City's Permit Center.
 Residential Care Facilities: Amend the Zoning Code to ensure definition of residential care facilities and small residential care facilities continue to comply with State law, and amend the zoning code to eliminate the requirement for a use permit for care facilities of seven or more persons with a disability, and allow them in all zones allowing residential uses based on objective criteria to facilitate approval certainty, except in areas where this conflicts with the San Carlos Airport Land Use Plan.
 Reasonable Accommodation: Amend the Zoning Code to ensure certainty and eliminate discretionary review.
 Definition of Family: Amend the Zoning Code definition of “Family” to remove the reference to “internally structured relationship” and instead define a family as one or more persons living together in a dwelling unit, with common access to, and common use of all living, kitchen, and eating areas within the dwelling unit.  Mobile Homes: Amend the Zoning Code to allow mobile home parks as a special use in all residential zones, consistent with Government Code Section 65852.7.  Farmworker Housing: Amend the Zoning Code to define "farmworker housing" and allow it within the districts to be determined, consistent with State requirements.

Quantified Objectives:
• Adopt Zoning Code amendments.

Geographic Target: Citywide
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Implementation Timeline:
 Amend the Zoning Code by Q4 2024.
 Review State Density Bonus law annually and update Zoning Code within 6 months of review, as needed.

Responsible Body: Planning Division
Funding Source(s): Community Development Department Budget Program H4.3: Lot Consolidation Fee Waivers. Waive the permit fees for subdivisions actions to consolidate lots for housing development projects with at least 20% very low- and/or extremely low-income units.

Quantified Objectives:
 Bring proposal to City Council to waive lot consolidation permit fees for developments with at least 20% very low- and/or extremely low-income units.

Geographic Target: Citywide
Implementation Timeline:
 City Council review draft policy in Q3 2026. Adopt policy in Q4 2026.

Responsible Body: Planning Division
Funding Source(s): Community Development Department Budget Program H4.4: Reduce Parking Requirements. Reduce parking requirements in certain residential zoning districts.

Quantified Objectives:
 The City will modify the parking requirements in the R-2, R-3, and R-4 zoning districts to reduce parking requirements consistent with other multi-family zoning districts (CMU, RC, Village Districts). It should also be noted that since January 2023, Assembly Bill 2097 has prohibited all Cities from enforcing minimum parking standards on properties within one half mile of public transit. A large majority of R-2, R-3, and R-4 properties are located within one half mile of public transit and will not be subject to minimum parking standards.

Geographic Target: R-2, R-3, and R-4 zoning districts
Implementation Timeline:
 Beginning in Q1 2025, develop code amendments to reduce parking requirements in the R-2, R-3 and R-4 zoning districts to be consistent with other multi-family zoning districts.
 Bring recommended changes to PC in Q4 2025 and to CC in Q1 2026 for approval.

Implement in Q2 2026.
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Responsible Body: Planning Division
Funding Source(s): Community Development Department Budget Program H4.5: Evaluation of Zoning Constraints. While the City’s development standards have proven to not be a constraint to housing development in recent years, it is important to continue to evaluate their effectiveness during the planning period. The City will monitor and analyze the interrelationship between the zoning standards, objective design standards, and State Density Bonus to identify and remove constraints to housing development. In addition, the City will conduct a peer agencies evaluation of zoning standards such as height and open space requirements as part of the analysis.

Quantified Objectives:
 Maintain a list of housing applications and use of State Density Bonus law with particular attention to what concessions/incentives and waivers developers are requesting.
 Monitor how developers are applying the City’s Objective Design Standards and track feedback from developers on any standards that are difficult to implement.  Monitor applications for Conditional Use Permits for ground floor residential to determine if the current provisions are appropriate to maintain the City’s goal of supplying commercial uses to serve the growing residential population and are not a barrier to housing development.
 Conduct a review of peer cities to confirm that Belmont’s zoning standards are in line with other cities that support diverse housing opportunities. The review will also include consulting and considering feedback from local and regional market rate and affordable housing developers.
 If the resulting analysis identifies opportunity to remove additional constraints, complete zoning code amendments to remove those constraints.

Geographic Target: Citywide in zoning districts that allow multi-family housing Implementation Timeline:
 Ongoing from 2024-2031, maintain list of how Density Bonus is applied, feedback from developers on feasibility of the adopted Objective Design Standards, and applications for Conditional Use Permits for ground floor residential uses.  Peer agency and developer evaluation completed in Q4 2026.  If zoning amendments are necessary to remove constraints, adopt by Q2 2027.

Responsible Body: Planning Division
Funding Source(s): Community Development Department Budget 294

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Program H4.6: Update the City's Webpage to Provide Enhanced Information for Housing Developers. Provide a clear summary of procedures, development standards, and fees for housing development on the Community Development webpage.

Quantified Objectives:
 Create and maintain a developer resources page to make it easier to navigate the City's development process; include updated development and impact fees consistent with State law.
 Prepare written procedures for SB 35 projects. Update the City's website with information and resources for SB 35 streamlined ministerial review, including providing a Notice of Intent form.

Geographic Target: Citywide
Implementation Timeline:
 Update the City's website annually in Starting in Q2 2024 to provide transparency on development fees, standards, and SB 35 streamlining.

Responsible Body: Planning Divisions
Funding Source(s): Community Development Department Budget Program H4.7: Monitor Commercial Development in Mixed-Use Districts. The City will continue monitoring commercial development in mixed-use districts and if the City find that the trends are shifting or incentivizing 100% commercial, the City will review and take action as necessary.

Quantified Objectives:
 Maintain a list of development applications in Commercial Mixed-Use districts with particular attention to whether or not commercial development is being proposed as a mixed-use or as a stand-alone use.
 Analyze whether zoning amendments or other development incentives are needed to encourage residential development in these zones and implement changes within one year of shift in development trends towards 100% commercial projects.

Geographic Target: Commercial Mixed-Use Districts
Implementation Timeline:
 Analyze development trends on an annual basis starting in Q4 2024. If changes are needed, implement and/or adopt within one year of shift in development trends towards 100% commercial projects
Responsible Body: Community Development Department
Funding Source(s): Community Development Department Budget 295

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GOAL H5: PROMOTE FAIR HOUSING ACCESS AND EQUAL OPPORTUNITIES FOR ALL PERSONS (SEE FAIR HOUSING ACTION PLAN IN CHAPTER 3, AFFH SUMMARY).

AFFH policies and programs increase the variety of housing types geographically distributed throughout the city, prevent displacement of low-income communities of color, and address identified fair housing issues to foster an inclusive community.

Policy H5.A: Increase awareness of and support the enforcement of laws and regulations prohibiting discrimination in lending practices and in the sale or rental of housing.

Policy H5.B: Increase available financial resources for affordable housing in order to better fund efforts to foster stable residential integration and increased access to opportunity. Increase integration by increasing the supply of affordable housing for families in higher opportunity areas.

Policy H5.C: Improve communications and coordination between jurisdictions, service providers, and agencies in the County.

Policy H5.D: Reduce the displacement of low-income communities of color by enhancing protections for vulnerable tenants and homeowners.

Policy H5.E: Continue to support local programs with a proven track record of assisting Belmont residents and workers to find housing.

Policy H5.F: Encourage housing development on properties with religious institutions and educational uses.

Policy H5.G: Increase the production of a variety of housing types in single-family neighborhoods throughout the City.

Policy H5.H: Strengthen ADU and SB9 Monitoring and Outreach Programs to encourage units with a demographic range of occupants.

Program H5.1: Update Website to Improve Access to Fair Housing Information and Housing Services. Increase community outreach and availability of fair housing resources and other housing services in multiple languages through the City’s Housing webpage. Advertise two existing HIP Housing programs with a track record of assisting Belmont residents and workers: 1) The Self Sufficiency Program provides subsidized rent and support services to low-income parents or emancipated foster youth who are in school to increase their earning power and become financially self-sufficient within 1-5 years; and 2) The Housing Readiness Program supports people who contact HIP to help them become more “housing ready” including housing resources, assistance completing housing applications, and offering activities that help prepare people to access housing.
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Quantified Objectives:
 Maintain and improve webpage with comprehensive housing related information and materials for low-income households seeking housing opportunities, and coordinate with providers to market programs electronically.  Provide an easy way for residents and property owners to find information on fair housing laws, rights, and responses (e.g., filing a complaint and ensuring property owners do not violate fair housing laws) on the City’s website.  Provide information in multiple languages.
 Conduct a best practices review of other jurisdictions' websites. Update Belmont's website to contain fair housing resources and information on how to connect with housing services.
 Update website quarterly and promote through City newsletter.  On an annual basis, maintain an average of two families in the Self Sufficiency Program, and two households in the Housing Readiness Program.

Implementation Timeline:
 Complete best practices review by Q1 2025; complete website update by Q2 2025, update quarterly thereafter.

Responsible Body: Housing Division
Funding Source(s): Housing Division Budget
Program H5.2: Coordinate with other jurisdictions and agencies in the County to advance AFFH goals. San Mateo County has a proven track record of collaboration between jurisdictions. As cities move towards more active efforts to further fair housing, there are new opportunities to collaborate.

Quantified Objectives:
 Attend regular meetings with 21 Elements (with planners and housing staff), 21 Directors (with Community Development Directors) and Housing Managers group.
 Collaborate with peer jurisdictions to implement Housing Element Programs that would benefit from efficiencies of scale.

Implementation Timeline:
 Attend meetings as scheduled, typically every other month for each group.

Responsible Body: Planning and Housing Divisions
Funding Source(s): Housing Division Budget
Program H5.3: Modify the Inclusionary Housing Program. Adjust the City's Below Market Rate (Inclusionary) Program to provide pathways for the construction of 297

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affordable units that address the needs of residents with extremely low and very low incomes who face very high rates of cost burden in the city.

Quantified Objectives:
 Expand the variety of housing units produced under the inclusionary housing program.
 Perform a feasibility analysis to redesign the program to allow a menu of options to produce units at different below market income levels.

Geographic Target: Citywide
Implementation Timeline:
 Complete feasibility analysis by Q4 2025; adopt redesigned program by Q1 2026.

Responsible Body: Planning and Housing Divisions
Funding Source(s): Community Development Budget
Program H5.4: Work with Housing Developers to Affirmatively Market Housing to Households with Disproportionate Housing Needs. The City actively supports collaboration between the private sector and service providers to connect persons in need of housing with new housing opportunities. Special attention will be paid to Black and Hispanic households that are more cost burdened and persons with disabilities.

Quantified Objectives:
 Establish a list of community service providers to distribute to developers of affordable housing.
 Coordinate with developers to ensure organizations are notified when new affordable housing becomes available.
 Partner service provider agencies to receive and respond to 30 intake calls per year from Belmont residents.
 Require developer agreements and affordable housing agreements to require affirmative marketing of below market rate units to households with higher needs.
 Require developers to affirmatively market approximately 640 very low-income and low-income housing units (based on the number of units anticipated to be constructed during the 8-year planning period, excluding those already completed as of May 2024) to households with disproportionate housing needs.  Target 15% of below market rate units to be occupied by households with disproportionate housing needs.

Geographic Target: All projects that include affordable units.

Implementation Timeline:
 Establish list of service providers by Q4 2024 and update annually thereafter. 298

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 Ongoing as projects are processed, review developer marketing plans to ensure affirmative marketing is included.

Responsible Body: Housing Division
Funding Source(s): Housing Division Budget
Program H5.5: Provide Fair Housing Training for Landlords and Tenants. Partner with Project Sentinel to provide training with a focus on tenant’s rights, race-based discrimination, and reasonable accommodations.

Quantified Objectives:
 Increase awareness of fair housing laws and tenants' rights to reduce unlawful discrimination and displacement.
 Partner with Project Sentinel to provide training every two years. Market training through direct outreach to landlords and through local service providers to reach tenants and enroll 10 residents in each training.
 Conduct a City Council study session on fair housing laws and available resources and notify at least 10 large multifamily property owners and five service providers to encourage participation in the meeting.

Geographic Target: Citywide
Implementation Timeline:
 Ongoing annual check in with Project Sentinel.
 Provide training in 2025 and every two years thereafter.  Conduct a City Council study session in Q3 2025.

Responsible Body: Housing Division, Project Sentinel
Funding Source(s): Housing Division Budget
Program H5.6: Expand Tenant Protections. The City will extend tenant protections to address displacement and relocation costs.

Quantified Objectives:
 Extend AB1482 provisions to require tenant relocation payments for No Fault evictions for those with tenure less than one year.
 Explore tenant protection policies that require documentation from landlords who use substantial remodel exemption to evict tenants.  Establish Right to Return policy for tenants displaced from homes due to demolition or substantial remodels.
 Conduct proactive outreach to tenants and tenant groups and engage with 30 rental households a year on tenant protection policies and available resources. 299

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Geographic Target: Citywide
Implementation Timeline:
 In Q4 2025, draft extended tenant protections provisions and research policy provisions for substantial remodel exemptions and right of return policies. Bring recommended language to City Council in Q1 2026.
 Conduct proactive outreach to tenants and tenant groups bi-annually.

Responsible Body: Housing Division
Funding Source(s): Housing Division Budget
Program H5.7: Continue Financial Support of Existing Home Sharing Program. The City will continue to provide financial support for the HIP Housing Home Sharing Program that matches individuals seeking housing with people who have a room or ADU to rent.

Quantified Objectives:
 Provide financial support each fiscal year through 2031 in the amount of $5,000.  Meet annually with HIP staff to discuss outreach methods and opportunities to reach underserved populations.
 On an annual basis, maintain an average of eight (8) households in a Home Sharing match.
 Match three (3) new residents per year with a housemate.

Geographic Target: Citywide, with an emphasis in low-density neighborhoods.

Implementation Timeline:
 City will grant funding as part of annual budget process.  Meet with HIP Housing within one year of Housing Element Certification and annually thereafter.

Responsible Body: Housing Division
Funding Source(s): Housing Division Budget
Program H5.8: Facilitate Development of Housing on Institutional Properties.

Conduct direct outreach and provide technical assistance to religious institutions and private schools to encourage development of housing on their sites.

Quantified Objectives:
 Conduct direct outreach to religious institution site owners or operators to inform them about SB4 (California Government Code Section 65913.16) that allows byright processing of certain affordable housing projects and any other regulations that encourage housing development on these sites.
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 Conduct direct outreach to site owners or operators of private schools to discuss the feasibility of developing housing on their sites.
 Provide technical assistance to religious and educational institutions including offering meetings, assigning a dedicated planner, assisting with development feasibility studies, and connecting institutions with potential developers or design professionals to help expedite the process. As appropriate provide incentives for development such as streamlined review and financial assistance for affordable projects.

Geographic Target: Specific sites citywide with an emphasis in low-density neighborhoods.

Implementation Timeline:
 Reach out to each religious institution site owner or operator within one year following Housing Element certification and annually thereafter.  Provide mailed notifications to religious institutions within six months of the adoption of any new State legislation that reduces barriers to development of religious institution sites.
 Reach out to each private school site owner or operator within one year following Housing Element certification and annually thereafter.

Responsible Body: Housing and Planning Divisions
Funding Source(s): Housing Division Budget and Affordable Housing Fund Program H5.9: Amend Zoning Code to Facilitate Production of ADUs and SB9 units.

Adopt zoning code amendments to facilitate production of additional ADUs and SB9 units in single-family neighborhoods.

Quantified Objectives:
 Complete zoning ordinance amendments to allow ADUs and SB9 units up to 1,200 square feet on single-family properties 10,000 square feet or greater. This would complement State law by allowing larger ADUs on larger properties spread throughout the city.
 Complete zoning ordinance amendments to allow all properties zoned singlefamily to convert from one unit to two units within the existing building envelope through a ministerial process. This would complement SB9 law by allowing greater flexibility in unit sizes. SB9 captures the division of existing homes to two units up to 800 square feet per unit. This program would allow any existing home to be divided into a duplex, regardless of the unit sizes. The property owner would also be allowed to build an ADU and JADU (for a total of 4 units).

Geographic Target: Citywide, with an emphasis in low-density neighborhoods.

Implementation Timeline:
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 Complete zoning ordinance amendments and establish policies and procedures to facilitate these types of projects within one year following Housing Element Certification.

Responsible Body: Community Development Department
Funding Source(s): Community Development Department Budget Program H5.10: Provide Financial Support for ADUs that Serve Lower-Income Households. Establish a grant or loan program to support low-income homeowners to construct ADUs or incentivize homeowners to construct ADUs affordable to lower income households.

Quantified Objectives:
 Analyze best practices for establishing an effective grant or loan program for ADUs.
 Participate in Countywide ADU Resource Center process for developing a loan/grant program and determine whether Countywide program meets the City’s needs and objectives.
 Finalize program and conduct outreach through the City website and newsletter, as well as local service providers.
 Target five grants/loans for five households during the planning period. Target special needs populations such as seniors, persons with disabilities, and large households.

Geographic Target: Citywide, with an emphasis in low-density neighborhoods.

Implementation Timeline:
 Participate in Countywide process in 2024.
 Establish a grant or loan program by Q4 2025.

Responsible Body: Housing Division
Funding Source(s): Affordable Housing Fund
Program H5.11: Conduct Outreach to Encourage ADU and SB9 Unit Production.

Strengthen ADU and SB9 outreach programs to encourage a range of unit sizes, with a demographic range of occupants, that are geographically dispersed throughout the city.

Quantified Objectives:
 Perform analysis and identify areas of the city with the highest potential for the addition of ADUs and JADUs due to sloping lots that create underfloor area prime for conversion to living area. Conduct direct outreach to those property owners and provide technical assistance. Target special needs populations such as seniors, developmentally disabled, and large households. 302

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 Establish an online plans gallery to allow property owners to access pre-reviewed ADU plans that can be downloaded for free or purchased from the designer.

Homeowners will be able to search for specific types and sizes of ADUs to meet a variety of needs.
 Participate in Countywide ADU Resource Center to facilitate coordinated, highquality outreach and technical assistance.  Create high-quality outreach materials including website updates, handouts, FAQs and application forms. Include materials targeted toward homeowners, rather than just design professionals.
 Conduct annual outreach to all ADU/JADU/SB9 property owners with HIP Housing information to encourage rental to a range of households (not just friends and family).

Geographic Target: Citywide, with an emphasis in low-density neighborhoods Implementation Timeline:
 Conduct analysis and outreach related to units on sloped sites in Q2 2025.  Join ADU Resource Center and launch online plans gallery in Q3 2024.  Create new outreach materials in Q1 2025.
 Conduct outreach to all ADU/JADU/SB9 owners within 9 months of Housing Element Certification and annually thereafter.

Responsible Body: Community Development Department
Funding Source(s): Community Development Department Budget Program H5.12: Create an AFFH Monitoring Program. Create an AFFH Monitoring Program to encourage units with a demographic range of occupants that are geographically dispersed throughout the city.

Quantified Objectives:
 The City hopes to achieve 120 units (above the RHNA) of which 50% would be low and moderate income through Housing Mobility Programs H5.3, H5.8, H5.9, H5.10, H5.11, and H5.12.
 Create a master list of all ADUs, JADUs, and SB9 units and map them to allow monitoring of their location throughout the city.
 Establish an ADU monitoring and reporting program, including mapping of location in the city, progress on ADU production, affordability, and geographical distribution.
 Monitor the distribution of ADUs and SB9 units. If ADUs and SB9 units are concentrated in certain areas of the city, analyze constraints and adjust outreach techniques to encourage distributed units.
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 Assess by mid-cycle (2027) if ADU and JADU production is meeting the City’s 6th cycle RHNA goals. If not, consider additional efforts such as reducing process and permitting fees to incentivize production. If trends indicate a potential substantial shortfall in meeting the estimated ADUs in the sites inventory, consider additional efforts to incentivize ADU production and reassess and revise the overall sites strategy for the RHNA by 2027 through adjusting ADU capacity assumptions with actual permitted units, and/or identifying additional sites for consideration to expand site capacity to the extent necessary to accommodate the RHNA.

Geographic Target: Citywide, with an emphasis in low-density neighborhoods.

Implementation Timeline:
 Create a list and map of existing ADUs, JADUs and SB9 units within six months of Housing Element adoption.
 Participate in regional process to establish an ADU monitoring program on timing they set forward.
 If ADU production does not meet target, consider additional efforts such as reducing process and permitting fees to incentivize production in 2027.

Responsible Body: Community Development Department
Funding Source(s): Community Development Department Budget

QUANTIFIED OBJECTIVES
The quantified objectives section estimates the number of units likely to be constructed, rehabilitated, or conserved/preserved by income level during the 2023-2031 planning period.

The quantified objectives do not represent a ceiling on development, but rather set a target goal for the jurisdiction to achieve, based on needs, resources, and constraints.

According to HCD, the sum of the quantified objectives for the programs should ideally be equal to or surpass the community's identified housing needs. However, State law recognizes that the total housing needs identified may exceed available resources and the community's ability to satisfy this need within the context of the general plan. Under these circumstances, the quantified objectives need not match the identified existing housing needs but should establish the maximum number of housing units that can be constructed, rehabilitated, and conserved over an eight-year time frame. The quantified objectives do not necessarily meet the goals of RHNA because they are not a full projection of anticipated housing development within the Housing Element Cycle. It is an estimate of actual production, given available resources and projected pipelines projects.

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development projects that are anticipated to be completed within the next eight years. The City is not aware of any pending housing preservation or rehabilitation projects.

Based on residential building permits issued in the last year and residential projects that have been initially reviewed or approved by the Planning department that have not been built, the quantified objective for non-subsidized pending and pipeline projects in above-moderateincome projects is 606 units. The total quantified objectives for the 2023-2031 planning period are outlined in Table 7-1. Table 7-2 includes quantified objectives for housing production and how they align with the City’s overall RHNA.
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TABLE 7-1: QUANTIFIED OBJECTIVES FOR CYCLE 6 (2023 – 2031)

ELI VLI LI MOD
Above
MOD Total
Conservation 30 30 20 0 0 80
Rehabilitation 5 5 10 0 0 20
Preservation 0 0 104 2 0 106
Housing Production
Housing Mobility Programs 10 10 40 60 0 120
Pipeline Projects Subsidized by the City 69 62 94 0 3 228 Other Pipeline Projects 0 0 81 0 484 565
Pending Projects 17 46 13 11 122 209
Housing Inventory Sites 126 126 154 186 484 1,076
Housing Inventory Sites Projected to be
Subsidized by the City 35 35 30 0 0 100
Pipeline and Projected ADUs 0 0 0 111 0 111
Subtotal Housing Production Units 257 279 412 368 1,093 2,409 TOTAL 292 314 546 370 1,093 2,615
Source: City of Belmont, 2024.

TABLE 7-2: HOUSING PRODUCTION QUANTIFIED OBJECTIVES ALIGNMENT WITH BELMONT’S RHNA
Income Level
Housing
Production
Quantified
Objective
Eight-Year
RHNA Figure
% of RHNA
to be Produced
Extremely and Very Low-Income 536 488 110%
Low-Income 412 281 147%
Moderate-Income 368 283 130%
Market Rate 1,093 733 149%
TOTAL 2,409 1,785
Source: City of Belmont, 2024.

7.2 PROGRAM IMPLEMENTATION MATRIX
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TABLE 7-3: PROGRAM IMPLEMENTATION MATRIX
Program 2024 2025 2026 2027 2028 2029 2030 2031
Program H1.1: Monitor Regional Housing Need Allocation. Monitor housing production against ABAG Fair Share Allocation in compliance with no net loss requirements during planning period. Monitor all housing unit production by all income categories.
 Ongoing  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing Program H1.2: Use Public Funding for Low/Moderate Income Housing. Use City affordable housing funds to produce additional affordable housing projects and to leverage other regional, state, and federal funding sources to support the construction of affordable housing.
 Ongoing  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing Program HI.3: Water and Sewer Providers. Ensure immediate delivery of the Housing Element to water and sewer providers to facilitate streamline reviews and ensure adequate capacity for housing projects.
 Deliver adopted
Housing Element
Program H1.4: Establish By-Right Housing Designation for Prior Housing Sites.

Designate housing sites that have carried over from the prior Housing Element to allow housing development by-right consistent with State law.  Completed in
January
Program H.1.5: Facilitate Pipeline and Pending Projects. The City will facilitate and support pipeline and pending projects during the planning period by working with applicants to ensure reviews are done in a timely manner, providing technical assistance, and limiting public meetings as required by SB 330. As needed, the City will provide incentives or additional assistance like expediting project review, supporting funding applications, and working to avoid unnecessary delays in processing of the applications.
 Ongoing  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing Program H2.1: Support Retention of Existing Lower-Income Units. Preserve “atrisk” affordable units through monitoring and partnering, working with nonprofits, and exploring available funding sources to preserve affordability. This activity will include both units in all affordable developments with expiring deed restrictions, as well as potential BMR units that are reaching the end of the term.  Ongoing review of
at-risk units and
tenant education
 Annual review of atrisk units, possible
affordability
extensions,
acquisition
opportunities, and
tenant education.
 Q1: Draft
preferences for any
new affordable
projects for
displaced tenants in
at-risk properties
 Q4: Recommend
preference language
to CC for adoption
 Ongoing review of
at-risk units and
tenant education
 Q1: Implement
preference policy.
 Ongoing review of
at-risk units and
tenant education
 Ongoing review of
at-risk units and
tenant education
 Ongoing review of
at-risk units and
tenant education
 Ongoing review of
at-risk units and
tenant education
 Ongoing review of
at-risk units and
tenant education
Program H2.2: Manage Portfolio of Deed Restricted Affordable Units. The City will formalize its method of managing the City’s deed restricted units by identifying a service provider or developing additional staff capacity.  Q3: Conduct analysis
and determine
whether to proceed
with a service
provider or staff
approach.
 Q1: If a service
provider approach is
selected, launch RFP
 Q4: Select provider
and implement
program
Program H2.3: Require Replacement Units. Adopt a policy requiring replacement units subject to the requirements of Government Code Section 65915 (c)(3) when new development occurs on a housing inventory site which currently has or within the past five years had residential uses (existing, vacated or demolished) and was legally restricted to low-income households, or subject to price control, or occupied by low-income households. Require that demolition permits include an assessment of rents to determine income status and plan to replace lost lowerincome units.  Q1: Conduct best
practices review on
replacement options
that would extend past
2034
 Q3: Bring
recommendations to
City Council
 Q4: implement
approved policy.
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Program H2.4: Rehabilitation of Existing Housing Occupied by Lower-Income Households. The City will partner with and provide financial assistance, outreach, or resources to support housing service organizations and/or non-profit organizations that help preserve existing housing that is affordable to lowerincome residents by providing home repairs and energy-efficiency improvements for low-income households.
 Q4: Outreach to
housing service
providers
 Q4: Outreach to
housing service
providers
 Q4: Outreach to
housing service
providers
 Q4: Outreach to
housing service
providers
Program H2.5: Preserve Existing Affordable Units. Develop a plan to preserve the City's affordable units that will expire in the next decade to keep them affordable long term.
 Q3: Conduct best
practices research
 Q1: Bring
recommendations to
Council beginning
2026
 Q2-Q3: Implement
program by mid2026.

Program H3.1: Home Ownership Financing. Support access to home ownership opportunities and connect potential homeowners to financing sources specifically targeted to first time homebuyers or affordable housing units.  Q3: Offer first time
homebuyer
workshops
 Q3: Offer first time
homebuyer
workshops
 Q3: Offer first time
homebuyer
workshops
Program H3.2: Continue to Participate in Countywide Below Market Rate Unit Web Portal. San Mateo County and multiple other jurisdictions collaborate on a web portal that includes affordable housing units available for rent, online applications, and access to the waitlist for future units.  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing Program H4.1: Update Zoning Code to Increase Floor Area Ratios and Density.

Modify the Zoning Ordinance to allow for increased floor area ratios and density to better facilitate development projects.
 Completed in
January
Program H4.2: Zoning Code Amendments to Remove Constraints. The City will annually review, and amend as necessary, the Zoning Code to ensure consistency with State Housing Government Code requirements and remove or lessen constraints on new housing development.
 Q4: Amend Zoning
Code
 Review State Density
Board law and
update Zoning Code
w/in 6 months of
review, as needed
 Review State Density
Board law and
update Zoning Code
w/in 6 months of
review, as needed
 Review State Density
Board law and
update Zoning Code
w/in 6 months of
review, as needed
 Review State Density
Board law and
update Zoning Code
w/in 6 months of
review, as needed
 Review State Density
Board law and
update Zoning Code
w/in 6 months of
review, as needed
 Review State Density
Board law and
update Zoning Code
w/in 6 months of
review, as needed
 Review State Density
Board law and
update Zoning Code
w/in 6 months of
review, as needed
 Review State Density
Board law and
update Zoning Code
w/in 6 months of
review, as needed
Program H4.3: Lot Consolidation Fee Waivers. Waive the permit fees for subdivisions actions to consolidate lots for housing development projects with at least 20% very low- and/or extremely low-income units.
 Q3: City Council
review draft policy
 Q4: Adopt policy
Program H4.4: Reduce Parking Requirements. Reduce parking requirements in certain residential zoning districts.
 Q1: Develop code
amendments to
reduce parking
requirements in the
R-2, R-3 and R-4
zoning districts to be
consistent with
other multi-family
zoning districts
 Q4: Bring
recommended
changes to PC
 Q1: Bring
recommended
changes to CC for
approval
 Q2: Implement
Program H4.5: Evaluation of Zoning Constraints. While the City’s development standards have proven to not be a constraint to housing development in recent years, it is important to continue to evaluate their effectiveness during the planning period. The City will monitor and analyze the interrelationship between the zoning standards, objective design standards, and State Density Bonus to identify and remove constraints to housing development. In addition, the City will conduct a peer agencies evaluation of zoning standards such as height and open space requirements as part of the analysis.
 Ongoing: Monitor
use of density bonus
and feasibility of
Objective Design
Standards
 Ongoing: Monitor
use of density bonus
and feasibility of
Objective Design
Standards
 Ongoing: Monitor
use of density bonus
and feasibility of
Objective Design
Standards
 Q4: Peer agency and
developer zoning
standards evaluation
completed
 Ongoing: Monitor
use of density bonus
and feasibility of
Objective Design
Standards
 Q2: Adopt zoning
amendments, if
needed to remove
constraints
 Ongoing: Monitor
use of density bonus
and feasibility of
Objective Design
Standards
 Ongoing: Monitor
use of density bonus
and feasibility of
Objective Design
Standards
 Ongoing: Monitor
use of density bonus
and feasibility of
Objective Design
Standards
 Ongoing: Monitor
use of density bonus
and feasibility of
Objective Design
Standards
Program H4.6: Update the City's Webpage to Provide Enhanced Information for Housing Developers. Provide a clear summary of procedures, development standards, and fees for housing development on the Community Development webpage.
 Q2: Update the City's
website
 Q2: Update the City's
website
 Q2: Update the City's
website
 Q2: Update the City's
website
 Q2: Update the City's
website
 Q2: Update the City's
website
 Q2: Update the City's
website
 Q2: Update the City's
website
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Program H4.7: Monitor Commercial Development in Mixed-Use Districts. The City will continue monitoring commercial development in mixed-use districts and if the City find that the trends are shifting or incentivizing 100% commercial, the City will review and take action as necessary.
 Q4: Analyze
development trends
 Q4: Analyze
development trends
 Q4: Analyze
development trends
 Q4: Analyze
development trends
 Q4: Analyze
development trends
 Q4: Analyze
development trends
 Q4: Analyze
development trends
 Q4: Analyze
development trends
Program H5.1: Update Website to Improve Access to Fair Housing Information and Housing Services. Increase community outreach and availability of fair housing resources and other housing services in multiple languages through the City’s Housing webpage. Advertise two existing HIP Housing programs with a track record of assisting Belmont residents and workers: 1) The Self Sufficiency Program provides subsidized rent and support services to low-income parents or emancipated foster youth who are in school to increase their earning power and become financially self-sufficient within 1-5 years; and 2) The Housing Readiness Program supports people who contact HIP to help them become more “housing ready” including housing resources, assistance completing housing applications, and offering activities that help prepare people to access housing.  Q1: Complete best
practices review
 Q2: Complete
website update,
update quarterly
thereafter
 Update website
quarterly
 Update website
quarterly
 Update website
quarterly
 Update website
quarterly
 Update website
quarterly
 Update website
quarterly
Program H5.2: Coordinate with other jurisdictions and agencies in the County to advance AFFH goals. San Mateo County has a proven track record of collaboration between jurisdictions. As cities move towards more active efforts to further fair housing, there are new opportunities to collaborate.
 Ongoing  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing Program H5.3: Modify the Inclusionary Housing Program. Adjust the City's Below Market Rate (Inclusionary) Program to provide pathways for the construction of affordable units that address the needs of residents with extremely low and very low incomes who face very high rates of cost burden in the city.  Q4: Complete
feasibility analysis
 Q1: Adopt
redesigned program
Program H5.4: Work with Housing Developers to Affirmatively Market Housing to Households with Disproportionate Housing Needs. The City actively supports collaboration between the private sector and service providers to connect persons in need of housing with new housing opportunities. Special attention will be paid to Black and Hispanic households that are more cost burdened and persons with disabilities.
 Q4: Establish list of
service providers
 Review developer
marketing plans to
ensure affirmative
marketing is
included
 Q4: Review list of
service providers
 Review developer
marketing plans to
ensure affirmative
marketing is
included
 Q4: Review list of
service providers
 Review developer
marketing plans to
ensure affirmative
marketing is
included
 Q4: Review list of
service providers
 Review developer
marketing plans to
ensure affirmative
marketing is
included
 Q4: Review list of
service providers
 Review developer
marketing plans to
ensure affirmative
marketing is
included
 Q4: Review list of
service providers
 Review developer
marketing plans to
ensure affirmative
marketing is
included
 Q4: Review list of
service providers
 Review developer
marketing plans to
ensure affirmative
marketing is
included
 Q4: Review list of
service providers
 Review developer
marketing plans to
ensure affirmative
marketing is
included
Program H5.5: Provide Fair Housing Training for Landlords and Tenants. Partner with Project Sentinel to provide training with a focus on tenant’s rights, racebased discrimination, and reasonable accommodations.  Provide training
 Q3: Provide a City
Council Study
Session on tenant’s
rights and available
resources.
 Provide training  Provide training  Provide training Program H5.6: Expand Tenant Protections. The City will extend tenant protections to address displacement and relocation costs.  Q4: Draft extended
tenant protections
provisions and
research policy
provisions for
substantial remodel
exemptions and
right of return
policies
 Conduct proactive
outreach to tenants
and tenant groups
 Q1: Bring
recommended
tenant protection
language to City
Council
 Conduct proactive
outreach to tenants
and tenant groups
 Conduct proactive
outreach to tenants
and tenant groups
 Conduct proactive
outreach to tenants
and tenant groups
bi-annually
Program H5.7: Continue Financial Support of Existing Home Sharing Program.

The City will continue to provide financial support for the HIP Housing Home Sharing Program that matches individuals seeking housing with people who have a room or ADU to rent.
 Ongoing  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing  Ongoing Program H5.8: Facilitate Development of Housing on Institutional Properties.

Conduct direct outreach and provide technical assistance to religious institutions and private schools to encourage development of housing on their sites.  Conduct annual
outreach to
religious/institution
site owners or
operators
 Conduct annual
outreach to
religious/
institution site
owners or operators
 Conduct annual
outreach to
religious/
institution site
owners or operators
 Conduct annual
outreach to
religious/
institution site
owners or operators
 Conduct annual
outreach to
religious/
institution site
owners or operators
 Conduct annual
outreach to
religious/
institution site
owners or operators
 Conduct annual
outreach to
religious/
institution site
owners or operators
310

7. HOUSING GOALS, POLICIES, AND PROGRAMS
B ELMONT H OUSING E LEMENT 2023 - 2031 7-29
Program H5.9: Amend Zoning Code to Facilitate Production of ADUs and SB9 units. Adopt zoning code amendments to facilitate production of additional ADUs and SB9 units in single-family neighborhoods.
 Complete zoning
ordinance
amendments and
establish policies and
procedures to
facilitate these types
of projects
Program H5.10: Provide Financial Support for ADUs that Serve Lower-Income Households. Establish a grant or loan program to support low-income homeowners to construct ADUs or incentivize homeowners to construct ADUs affordable to lower income households.
 Participate in
Countywide process
 Q4: Establish a grant
or loan program
Program H5.11: Conduct Outreach to Encourage ADU and SB9 Unit Production.

Strengthen ADU and SB9 outreach programs to encourage a range of unit sizes, with a demographic range of occupants, that are geographically dispersed throughout the city.
 Q3: Join ADU
Resource Center and
launch online plans
gallery
 Q1: Create new
outreach materials
 Q2: Conduct analysis
and outreach related
to units on sloped
sites
 Conduct outreach to
all ADU/JADU/SB9
owners
 Conduct outreach to
all ADU/JADU/SB9
owners
 Conduct outreach to
all ADU/JADU/SB9
owners
 Conduct outreach to
all ADU/JADU/SB9
owners
 Conduct outreach to
all ADU/JADU/SB9
owners
 Conduct outreach to
all ADU/JADU/SB9
owners
 Conduct outreach to
all ADU/JADU/SB9
owners
Program H5.12: Create an AFFH Monitoring Program. Create an AFFH Monitoring Program to encourage units with a demographic range of occupants that are geographically dispersed throughout the city.
 Q1: Create a list and
map of existing
ADUs, JADUs and
SB9 units
 Participate in
regional process to
establish an ADU
monitoring program
 If ADU production
does not meet
target, consider
additional strategies
311
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APPENDIX A: NEEDS ANALYSIS
312
APPENDIX A: NEEDS ANALYSIS
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B ELMONT H OUSING E LEMENT 2023 - 2031 i

TABLE OF CONTENTS

1. Introduction...................................................................................................................... 1

2. Key Statistics ....................................................................................................................2

3. Looking to the Future: Regional Housing Needs ...............................................................5

3.1 Regional Housing Needs Determination.................................................................. 5

3.2 Regional Housing Needs Allocation.........................................................................6

4. Population, Employment and Household Characteristics.................................................. 7

4.1 Population............................................................................................................... 7

4.2 Age..........................................................................................................................8

4.3 Race and Ethnicity...................................................................................................9

4.4 Employment Trends.............................................................................................. 10 Balance of Jobs and Workers ................................................................................. 10 Sector Composition............................................................................................... 14 Unemployment ..................................................................................................... 15

4.5 2018-2028 Occupation Projections........................................................................ 16

4.6 Extremely Low-Income Households .......................................................................17 Resources for Extremely Low-income Households ................................................ 19

4.7 Tenure................................................................................................................... 21

4.8 Displacement ........................................................................................................ 25

5. Housing Stock Characteristics......................................................................................... 27

5.1 Housing Types, Year Built, Vacancy, and Permits.................................................. 27

5.2 Assisted Housing Developments At-Risk of Conversion ........................................ 30

5.3 Substandard Housing.............................................................................................33

5.4 Home and Rent Values .......................................................................................... 35

5.5 Housing Affordability ............................................................................................ 38

5.6 Overpayment and Overcrowding .......................................................................... 39

6. Special Housing Needs.................................................................................................... 47

6.1 Large Households.................................................................................................. 47 Resources for Large Households............................................................................48

6.2 Female-Headed Households.................................................................................. 48 Resources for Single Parent Households................................................................50

6.3 Seniors .................................................................................................................. 50 Resources for Seniors ............................................................................................ 51

6.4 People with Disabilities ......................................................................................... 52 Resources for Persons with Developmental Disabilities......................................... 57

6.5 Homelessness........................................................................................................ 58 Resources for Persons Experiencing Homelessness ...............................................64

6.6 Farmworkers ......................................................................................................... 65 Resources for Migrant and/or Farm Workers .........................................................66

6.7 Non-English Speakers ...........................................................................................66 314
APPENDIX A: NEEDS ANALYSIS
i i
TABLES
Table 1: Income Limits for San Mateo County (2022)..............................................................6 Table 2: Illustrative Regional Housing Needs Allocation from Draft Methodology ..................6 Table 3: Population Growth Trends.........................................................................................7 Table 4: Occupations with the Most Job Openings (2018-2028)............................................16 Table 5: Household Distribution by Race/Ethnicity and Income ............................................20 Table 6: City of Belmont Housing Permitting (2015-2021).....................................................29 Table 7: Assisted Units at Risk of Conversion ........................................................................30 Table 8: City of Belmont Inventory of Publicly Assisted Housing Projects (2023)...................32 Table 9: Age of Housing Stock and Estimated Rehabilitation Needs.....................................34 Table 10: Housing Opportunity Index (First Quarter, 2021).....................................................38 Table 11: Affordable Rents for Two- and Three-Person Households .......................................39 Table 12: Cost Burden by Tenure and Income .........................................................................42 Table 13: Population with Developmental Disabilities by Age.................................................55 Table 14: Population with Developmental Disabilities by Residence.......................................55 Table 15: Growth in Population of San Mateo County Adults with Developmental Disabilities ...............................................................................................................56 Table 16: Students in Local Public Schools Experiencing Homelessness .................................63 Table 17: Migrant Worker Student Population........................................................................65 315
APPENDIX A: NEEDS ANALYSIS
B ELMONT H OUSING E LEMENT 2023 - 2031 iii

FIGURES
Figure 1: Population Growth Trends ........................................................................................ 7 Figure 2: Population by Age (2000-2019).................................................................................8 Figure 3: Senior and Youth Population by Race .......................................................................9 Figure 4 Population by Race (2000-2019).............................................................................. 10 Figure 5: Jobs in Belmont (2002-2018)....................................................................................11 Figure 6: Workers by Earnings and Jurisdiction as Place of Work and Place of Residence ...... 12 Figure 7: Jobs-Worker Ratios by Wage Group.........................................................................13 Figure 8: Jobs-Household Ratio ..............................................................................................13 Figure 9: Resident Employment by Industry .......................................................................... 14 Figure 10: Resident Employment by Occupation..................................................................... 15 Figure 11: Unemployment Rate............................................................................................... 16 Figure 12: Households by Household Income Level ................................................................. 18 Figure 13: Household Income Level by Tenure ........................................................................ 20 Figure 14: Poverty Status by Race ........................................................................................... 21 Figure 15: Housing Tenure....................................................................................................... 22 Figure 16: Housing Tenure by Race of Householder................................................................. 23 Figure 17: Housing Tenure by Age........................................................................................... 24 Figure 18: Housing Tenure by Year Moved to Current Residence............................................. 24 Figure 19: Housing Tenure by Housing Type............................................................................ 25 Figure 20: Households by Displacement Risk and Tenure ........................................................ 26 Figure 21: Housing Type Trends .............................................................................................. 27 Figure 22: Housing Units by Year Structure Built..................................................................... 28 Figure 23: Vacant Units by Type .............................................................................................. 29 Figure 24: Substandard Housing Issues.....................................................................................33 Figure 25: Home Values of Owner-Occupied Units .................................................................. 35 Figure 26: Zillow Home Value Index (ZHVI).............................................................................. 36 Figure 27: Contract Rents for Renter-Occupied Units ...............................................................37 Figure 28: Median Contract Rent..............................................................................................37 Figure 29: Cost Burden by Tenure............................................................................................ 40 Figure 30: Cost Burden by Income Level.................................................................................. 41 Figure 31: Cost Burden by Race ............................................................................................... 41 Figure 32: Cost Burden by Household Size............................................................................... 43 Figure 33: Cost-Burdened Senior Households by Income Level ............................................... 44 Figure 34: Overcrowding by Tenure and Severity .................................................................... 44 Figure 35: Overcrowding by Income Level and Severity........................................................... 45 Figure 36: Overcrowding by Race ............................................................................................46 Figure 37: Household Size by Tenure....................................................................................... 47 Figure 38: Housing Units by Number of Bedrooms .................................................................. 48 Figure 39: Household Type ......................................................................................................49 Figure 40: Female-Headed Households by Poverty Status.......................................................49 Figure 41: Senior Households by Income and Tenure .............................................................. 51 Figure 42: Disability by Type.................................................................................................... 53 Figure 43: Homelessness by Household Type and Shelter Status, San Mateo County ............. 61 316
APPENDIX A: NEEDS ANALYSIS
i v
Figure 44: Racial Group Share of General and Homeless Populations, San Mateo County........61 Figure 45: Latinx Share of General and Homeless Populations, San Mateo County..................62 Figure 46: Characteristics for the Population Experiencing Homelessness, San Mateo County.....................................................................................................................63 Figure 47: Farm Operations and Farm Labor by County, San Mateo County............................66 Figure 48: Population with Limited English Proficiency............................................................67 317
B ELMONT H OUSING E LEMENT 2023 - 2031 1

1. INTRODUCTION
The Bay Area continues to see growth in both population and jobs, which means more housing of various types and sizes is needed to ensure that residents across all income levels, ages, and abilities have a place to call home. While the number of people drawn to the region over the past 30 years has steadily increased, housing production has stalled, contributing to the housing shortage that communities are experiencing today. In many cities, this has resulted in residents being priced out, increased traffic congestion caused by longer commutes, and fewer people across incomes being able to purchase homes or meet surging rents.

The 2023-2031 Housing Element update provides a roadmap for how to meet local growth and housing challenges. Required by the state, the Housing Element identifies existing housing conditions and community, reiterates housing goals, and creates a plan for housing creation.

The Housing Element is an integral part of the General Plan, which guides the policies of the City of Belmont.
318
2 2. KEY STATISTICS
 Population – Generally, the population of the Bay Area continues to grow due to natural growth as well as a strong economy that draws new residents to the region. The population of Belmont increased by 6.7% from 2000 to 2020, which is below the growth rate of the Bay Area as a whole.
 Age – In 2019, Belmont’s youth population under the age of 18 was 6,233 and its senior population 65 and older was 4,538. These age groups represent 23.0% and 16.7%, respectively, of Belmont’s population.
 Race/Ethnicity – In 2020, 53.9% of Belmont’s population was White, 1.0% was African American, 28.3% was Asian, and 12.1% was Latinx. People of color in Belmont comprise a proportion below the proportion in the Bay Area as a whole.1  Employment – Belmont residents most commonly work in the Financial & Professional Servicesindustry. From January 2010 to January 2021, the unemployment rate in Belmont decreased by 3.0%. Since 2010, the number of jobs located in the jurisdiction increased by 560 (9.5%). Additionally, the jobs-household ratio in Belmont decreased from 0.75 in 2002 to 0.62 in 2018.
 Number of Homes – The number of new homes built in the Bay Area has not kept pace with the demand, resulting in longer commutes, increasing prices, and exacerbating issues of displacement and homelessness. From 2010 to 2020, the number of homes in Belmont increased by 0.6%, which is below the growth rate for San Mateo County and below the growth rate of the region’s housing stock at this time.  Home Prices – A diversity of homes at all income levels creates opportunities for all Belmont residents to live and thrive in the community.
 Ownership – The largest proportion of homes had a value in the range of $1M to $2M in 2019. Home prices increased by 123.6% from 2010 to 2020.  Rental Prices – In 2019, the typical contract rent for an apartment in Belmont was $2,250. From 2009 to 2019, rental prices increased by 76.8%. To rent a typical apartment without cost burden, a household would need to make $90,040 per year. 2  Housing Type – It is important to have a variety of housing types to meet the current and future needs of the community. In 2020, 58.0% of Belmont homes were single-family 1 The Census Bureau’s American Community Survey accounts for ethnic origin separate from racial identity. The numbers reported here use an accounting of both such that the racial categories are shown exclusive of Latinx status, to allow for an accounting of the Latinx population regardless of racial identity. The term Hispanic has historically been used to describe people from numerous Central American, South American, and Caribbean countries. In recent years, the term Latino or Latinx has become preferred. This report generally uses Latinx, but occasionally when discussing US Census data, we use Hispanic or Non-Hispanic, to clearly link to the data source. 2 Note that contract rents may differ significantly from, and often being lower than, current listing prices. 319
APPENDIX A: NEEDS ANALYSIS
B ELMONT H OUSING E LEMENT 2023 - 2031 3
detached, 6.0% were single-family attached, 3.1% were small multi-family (2-4 units), and

32.9% were medium or large multi-family (5+ units). From 2010 to 2020, the number of single-family units increased more than the number of multi-family units. Generally, the share of the housing stock that is detached single-family homes is above that of other jurisdictions in the region.
 Cost Burden – The U.S. Department of Housing and Urban Development considers housing to be affordable for a household if the household spends less than 30% of its income on housing costs. A household is considered “cost-burdened” if it spends more than 30% of its monthly income on housing costs, while those who spend more than 50% of their income on housing costs are considered “severely cost-burdened.” In Belmont, 18.1% of households are cost-burdened, while 15.0% are severely cost-burdened.  Displacement/Gentrification – According to research from The University of California, Berkeley, no households in Belmont live in neighborhoods that are susceptible to or experiencing displacement, and none live in areas at risk of or undergoing gentrification. In Belmont, 45.5% of households live in neighborhoods where low-income households are likely excluded due to prohibitive housing costs. There are various ways to address displacement including ensuring new housing is built at all income levels.  Neighborhood – In Belmont, 100.0% of residents live in neighborhoods identified as “highest resource” or “high resource” by State-commissioned research. By comparison,

0.0% of residents live in areas identified by this research as “low resource” or “high segregation and poverty.” These neighborhood designations are based on a range of indicators such as education, poverty, proximity to jobs and economic opportunities, low pollution levels, and other factors.3
 Special Housing Needs – Some population groups may have special housing needs that require specific program responses, and these groups may experience barriers to accessing stable housing due to their specific housing circumstances. In Belmont, 9.0% of residents have a disability of any kind and may require accessible housing. Additionally, 5.2% of Belmont households are larger households with five or more people, likely needing larger housing units with three bedrooms or more, while 6.7% of households are female-headed families, which are often at a greater risk of housing insecurity. 3 For more information on the “opportunity area” categories developed by HCD and the California Tax Credit Allocation Committee, see this website: https://www.treasurer.ca.gov/ctcac/opportunity.asp. The degree to which different jurisdictions and neighborhoods have access to opportunity will likely need to be analyzed as part of new Housing Element requirements related to affirmatively furthering fair housing. ABAG/MTC will be providing jurisdictions with technical assistance on this topic this summer, following the release of additional guidance from HCD.
320
APPENDIX A: NEEDS ANALYSIS
4 NOTE ON DATA
Many of the tables in this report are sourced from data from the Census Bureau’s American Community Survey or U.S. Department of Housing and Urban Development’s Comprehensive Housing Affordability Strategy (CHAS) data, both of which are samples and as such, are subject to sampling variability. This means that data is an estimate, and that other estimates could be possible if another set of respondents had been reached. We use the five-year release to get a larger data pool to minimize this “margin of error” but particularly for the smaller cities, the data will be based on fewer responses, and the information should be interpreted accordingly.

NOTE ON FIGURES
Any figure that does not specify geography in the figure name represents data for Belmont.
321
B ELMONT H OUSING E LEMENT 2023 - 2031 5

3. LOOKING TO THE FUTURE:

REGIONAL HOUSING NEEDS

3.1 REGIONAL HOUSING NEEDS DETERMINATION
The Plan Bay Area 20504 Final Blueprint forecasts that the nine-county San Francisco Bay Area will add 1.4 million new households between 2015 and 2050. For the eight-year time frame covered by this Housing Element Update, the Department of Housing and Community Development (HCD) has identified the region’s housing need as 441,176 units. The total number of housing units assigned by HCD is separated into four income categories that cover housing types for all income levels, from very low-income households to market rate housing.

Every year, the US Department of Housing and Urban Development, in conjunction with the State of California, establish income categories based on the median income in each county.

Based on new requirements for the completion of the Housing Element, jurisdictions must now report on the following income categories.
 Extremely Low-Income: 0-30% of Area Median Income, or AMI  Very Low-Income: 30-50% AMI
 Low-Income: 50-80% AMI
 Moderate-Income: 80-120% AMI
 Above Moderate-Income: 120%+ AMI
Table 1 illustrates the income categories for San Mateo County in 2022. The median income for a family of four is $166,000.

The Regional Housing Needs Determination (RHND) is based on population projections produced by the California Department of Finance as well as adjustments that incorporate the region’s existing housing needs. The adjustments result from recent legislation requiring HCD to apply additional adjustment factors to the baseline growth projection from California Department of Finance, for the regions to get closer to healthy housing markets. To this end, adjustments focus on the region’s vacancy rate, level of overcrowding, and share of costburdened households, seeking to bring the region more in line with comparable ones.5 These new laws governing the methodology for how HCD calculates the RHND resulted in a significantly higher number of housing units for which the Bay Area must plan compared to previous RHNA cycles.
4 Plan Bay Area 2050 is a long-range plan charting the course for the future of the nine-county San Francisco Bay Area. It covers four key issues: the economy, the environment, housing and transportation 5 For more information on HCD’s RHND calculation for the Bay Area, see this letter sent to ABAG from HCD on June 9, 2020: https://www.hcd.ca.gov/community-development/housing-element/docs/abagrhna-final060920(r).pdf 322
APPENDIX A: NEEDS ANALYSIS
6 TABLE 1: INCOME LIMITS FOR SAN MATEO COUNTY (2022)
Number of
Persons in Household 1 2 3 4 5 6 7 8
San Mateo
County
Area Median
Income:
$166,000
Acutely LowIncome $17,450 $19,900 $22,400 $24,900 $26,900 $28,900 $30,900 $32,850 Extremely LowIncome $39,150 $44,750 $50,350 $55,900 $60,400 $64,850 $69,350 $73,800 Very Low-Income $65,250 $74,600 $83,900 $93,200 $100,700 $108,150 $115,600 $123,050 Low-Income $104,400 $119,300 $134,200 $149,100 $161,050 $173,000 $184,900 $196,850 Median Income $116,200 $132,800 $149,400 166,000 $179,300 $192,550 $205,850 $219,100 Moderate-Income $139,450 $159,350 $179,300 $199,200 $215,150 $231,050 $247,000 $262,950 Source: State of California Department of Housing and Community Development, May 13, 2022, https://www.hcd.ca.gov/grantsfunding/income-limits/state-and-federal-income-limits.shtml.

3.2 REGIONAL HOUSING NEEDS ALLOCATION
A starting point for the Housing Element update process for every California jurisdiction is the Regional Housing Needs Allocation (RHNA), which is also the share of the RHND assigned to each jurisdiction by the Association of Bay Area Governments (ABAG). State Housing Element Law requires that ABAG develop a methodology calculating the number of housing units assigned to each city and county and distribute each jurisdiction’s housing unit allocation among four affordability levels. For this RHNA cycle, the RHND increased by 135%, from 187,990 to 441,776. For more information on the RHNA process this cycle, see ABAG’s website:
https://abag.ca.gov/our-work/housing/rhna-regional-housing-needs-allocation Almost all Bay Area jurisdictions received a larger RHNA this cycle compared to the prior cycle, primarily due to changes in state law that led to a considerably higher RHND compared to previous cycles.

In January 2022, HCD approved ABAG’s RHNA Methodology. For Belmont, the RHNA to be planned for this cycle is 1,785 units, a slated increase from the last cycle. The allocation Belmont received from the RHNA Methodology is broken down by income category as follows, including an estimate of the number of extremely low-income units needed.

TABLE 2: ILLUSTRATIVE REGIONAL HOUSING NEEDS ALLOCATION FROM DRAFT METHODOLOGY Income Group
Belmont
Units
San Mateo
County
Units
Bay Area
Units
Belmont
Percent
San Mateo
County
Percent
Bay Area
Percent
Very Low-Income (<50% of AMI) 488 12,196 114,442 27.3% 25.6% 25.9% Estimated Extremely Low-Income
(0-30% of AMI) 241 N/A N/A 13.5% N/A N/A
Low-Income (50%-80% of AMI) 281 7,023 65,892 15.7% 14.7% 14.9% Moderate-Income (80%-120% of AMI) 283 7,937 72,712 15.9% 16.6% 16.5% Above Moderate-Income (>120% of AMI) 733 20,531 188,130 41.1% 43.1% 42.6% Total 1,785 47,687 441,176 100.0% 100.0% 100.0%
323
B ELMONT H OUSING E LEMENT 2023 - 2031 7

4. POPULATION, EMPLOYMENT AND

HOUSEHOLD CHARACTERISTICS

4.1 POPULATION
The Bay Area is the fifth-largest metropolitan area in the nation and has seen a steady increase in population since 1990, apart from a dip during the Great Recession. Many cities in the region have experienced significant growth in jobs and population. While these trends have led to a corresponding increase in demand for housing across the region, the regional production of housing has largely not kept pace with job and population growth. Since 2000, Belmont’s population has increased by 6.7%, while the region as a whole has experienced an increase of

14.8%. Approximately 13.5% of Belmont’s population moved during 2020, a number 0.1% greater than the regional rate of 13.4%.

TABLE 3: POPULATION GROWTH TRENDS
Geography 1990 1995 2000 2005 2010 2015 2020
Belmont 24,165 24,752 25,123 25,382 25,835 26,896 26,813 San Mateo County 649,623 685,354 707,163 719,844 718,451 761,748 773,244 Bay Area 6,020,147 6,381,961 6,784,348 7,073,912 7,150,739 7,595,694 7,790,537 Universe: Total population.

Source: California Department of Finance, E-5 series.

For more years of data, please refer to the Data Packet Workbook, Table POPEMP-01.

Figure 1: Population Growth Trends
Source: California Department of Finance, E-5 series Note: The data shown on the graph represents population for the jurisdiction, county, and region indexed to the population in the first year shown. The data points represent the relative population growth in each of these geographies relative to their populations in that year. DOF uses the decennial census to benchmark subsequent population estimates. For the data table behind this figure, please refer to the Data Packet Workbook, Table POPEMP-01. 324
APPENDIX A: NEEDS ANALYSIS
8 In 2020, the population of Belmont was estimated at 26,813, or 3.5% of San Mateo County’s population. From 1990 to 2000, the City’s population increased by 4.0%; from 2000 to 2010, it increased by 2.8%; and from 2010 to 2020, it increased by 3.8%.

4.2 AGE
The distribution of age groups in a city shapes the types of housing the community may need soon. For example, an increase in the older population may mean there is a need to develop more senior housing, while higher numbers of children and young families can point to a need for more family housing and related services. There has also been a move by many to age-inplace or downsize to stay within their communities, which can mean more multi-family and accessible units are also needed.

In Belmont, the median age in 2000 was 38.5. By 2019, this figure increased to approximately 40 years old. More specifically, the population of those under 14 and those 65-and-over has increased since 2010 (see Figure 2).

Figure 2: Population by Age (2000-2019)
Universe: Total population.

Source: U.S. Census Bureau, Census 2000 SF1, Table P12; U.S. Census Bureau, Census 2010 SF1, Table P12; U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B01001 For the data table behind this figure, please refer to the Data Packet Workbook, Table POPEMP-04.

Looking at the youth and senior populations by race can add an additional layer of understanding, as families and seniors of color are even more likely to experience challenges 325
APPENDIX A: NEEDS ANALYSIS
B ELMONT H OUSING E LEMENT 2023 - 2031 9
finding affordable housing. In Belmont, people of color6 constitute 41.6% of youth under 18 and

28.8% of seniors (see Figure 3).

Figure 3: Senior and Youth Population by Race
Universe: Total population.

Notes: In the sources for this table, the Census Bureau does not disaggregate racial groups by Hispanic/Latinx ethnicity, and an overlapping category of Hispanic / non-Hispanic groups has not been shown to avoid double counting in the stacked bar chart.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B01001(A-G) For the data table behind this figure, please refer to the Data Packet Workbook, Table SEN-02.

4.3 RACE AND ETHNICITY
Understanding the racial makeup of a city and region is important for designing and implementing effective housing policies and programs. These patterns are shaped by both market factors and government actions, such as exclusionary zoning, discriminatory lending practices, and displacement that have occurred over time and continue to impact communities of color today.
7 Since 2000, the percentage of residents in Belmont identifying as White has decreased–and by the same token, the percentage of residents of all other races and ethnicities has increased–by

18.9%, with the 2019 population standing at 14,611 (see Figure 4). During this period, the Asian/API, Non-Hispanic population increased the most while the White, Non-Hispanic population decreased the most.
6 Here, we count all non-white racial groups.
7 See, for example, Rothstein, R., 2017. The Color of Law: a Forgotten History of How our Government Segregated America. New York, NY & London, UK: Liveright Publishing. 326
APPENDIX A: NEEDS ANALYSIS
10 Figure 4 Population by Race (2000-2019)
Universe: Total population.

Notes: Data for 2019 represents 2015-2019 ACS estimates. The Census Bureau defines Hispanic/Latinx ethnicity separate from racial categories. For the purposes of this graph, the “Hispanic or Latinx” racial/ethnic group represents those who identify as having Hispanic/Latinx ethnicity and may also be members of any racial group. All other racial categories on this graph represent those who identify with that racial category and do not identify with Hispanic/Latinx ethnicity.

Source: U.S. Census Bureau, Census 2000, Table P004; U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B03002
For the data table behind this figure, please refer to the Data Packet Workbook, Table POPEMP-02.

4.4 EMPLOYMENT TRENDS

BALANCE OF JOBS AND WORKERS
A city houses employed residents who either work in the community where they live or work elsewhere in the region. Conversely, a city may have job sites that employ residents from the same city, but more often employ workers commuting from outside of it. Smaller cities typically have more employed residents than jobs and “export” workers, while larger cities tend to have a surplus of jobs and “import” workers.

To some extent, the regional transportation system is set up for the flow of workers to the region’s core job centers. At the same time, as the housing affordability crisis has illustrated, local imbalances may be severe, where local jobs and worker populations are out of sync at a sub-regional scale. One measure of this is the relationship between workers and jobs. From 2002 to 2018, the number of jobs in Belmont decreased by 16.7% (see Figure 5). 327
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B ELMONT H OUSING E LEMENT 2023 - 2031 11
Figure 5: Jobs in Belmont (2002-2018)
Universe: Jobs from unemployment insurance-covered employment (private, state and local government) plus United States Office of Personnel Management-sourced Federal employment.

Notes: The data is tabulated by place of work, regardless of where a worker lives. The source data is provided at the census block level.

These are crosswalked to jurisdictions and summarized.

Source: U.S. Census Bureau, Longitudinal Employer-Household Dynamics, Workplace Area Characteristics (WAC) files, 2002-2018 For the data table behind this figure, please refer to the Data Packet Workbook, Table POPEMP-11.

From 2002-2018, the largest-growing job sectors were Information (100%), followed by Health and Educational Services(32%), Government (31%), and Professional and Managerial Services (22%). By contrast, Transportation and Utilities(-34%), and Retail (-28%) saw substantial decreases during this period. In Belmont, there are 13,688 employed residents and 7,867 jobs8 and the ratio of jobs to resident workers is 0.57; therefore, Belmont is a net exporter of workers.

Figure 6 shows the balance when comparing jobs to workers, broken down by wage group and offering additional insights into local dynamics. A community may offer employment for relatively low-income workers but have relatively few housing options for those workers, or conversely, it may house residents who are low wage workers but offer few employment opportunities for them. Such relationships may cast extra light on potentially pent-up demand for housing in particular price categories.

A relative surplus of jobs relative to residents in each wage group suggests the need to import those workers while surpluses of workers in a wage group means the community will export workers to other jurisdictions. Such flows are not inherently bad, but over time, sub-regional imbalances may result. Belmont has more low-wage jobs (paying less than $25,000) than low8 Employed residents in a jurisdiction is counted by place of residence (they may work elsewhere) while jobsin a jurisdiction are counted by place of work (they may live elsewhere). The jobs may differ from those reported in Figure 5 as the source for the time series is from administrative data, while the cross-sectional data is from a survey. 328
APPENDIX A: NEEDS ANALYSIS
12 wage residents. The city also has more high-wage residents than high-wage jobs (paying more than $75,000) (see Figure 6).9
Figure 6: Workers by Earnings and Jurisdiction as Place of Work and Place of Residence
Universe: Workers 16 years and over with earnings.

Source: U.S. Census Bureau, American Community Survey 5-Year Data 2015-2019, B08119, B08519 For the data table behind this figure, please refer to the Data Packet Workbook, Table POPEMP-10.

Figure 7 shows the balance of a jurisdiction’s resident workers to the jobs located there for different wage groups as a ratio instead. A value of 1 means that a city has the same number of jobs as residents in a given wage group. Values above 1 indicate a jurisdiction will need to import workers. At the regional scale, the ratio is 1.04 jobs for each worker, implying a modest import of workers from outside the region (see Figure 7).

Such balances between jobs and workers may directly influence the housing demand in a community. New jobs may draw new residents, and when there is high demand for housing relative to supply, many workers may be unable to afford to live where they work, particularly where job growth has been in relatively lower wage jobs. This dynamic means many workers endure long commutes; it also contributes to traffic congestion and time lost for all road users.

When there are more jobs than employed residents, it means a city is relatively jobs-rich, typically also with a high jobs to household ratio. Thus, bringing housing into the measure, the jobsto household ratio in Belmont has decreased from 0.75 in 2002 to 0.62 in 2018 (see Figure 8).
9 The source table is top-coded at $75,000, precluding more fine grained analysis at the higher end of the wage spectrum.
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Figure 7: Jobs-Worker Ratios by Wage Group
Universe: Jobs in a jurisdiction from unemployment insurance-covered employment (private, state and local government) plus United States Office of Personnel Management-sourced Federal employment.

Notes: The ratio compares job counts by wage group from two tabulations of LEHD data: Counts by place of work relative to counts by place of residence. See text for details.

Source: U.S. Census Bureau, Longitudinal Employer-Household Dynamics, Workplace Area Characteristics (WAC) files (Jobs); Residence Area Characteristics (RAC) files (Employed Residents), 2010-2018. For the data table behind this figure, please refer to the Workbook, Table PO PEMP-14.

Figure 8: Jobs-Household Ratio
Universe: Jobs in a jurisdiction from unemployment insurance-covered employment (private, state and local government) plus United States Office of Personnel Management-sourced Federal employment; households in a jurisdiction.

Notes: The data is tabulated by place of work, regardless of where a worker lives. The source data is provided at the census block level.

These are crosswalked to jurisdictions and summarized. The ratio compares place of work wage and salary jobs with households, or occupied housing units. A similar measure is the ratio of jobs to housing units. However, this jobs-household ratio serves to compare the number of jobs in a jurisdiction to the number of housing units that are actually occupied. The difference between a jurisdiction’s jobshousing ratio and jobs-household ratio will be most pronounced in jurisdictions with high vacancy rates, a high rate of units used for seasonal use, or a high rate of units used as short-term rentals.

Source: U.S. Census Bureau, Longitudinal Employer-Household Dynamics, Workplace Area Characteristics (WAC) files (Jobs), 2002- 2018; California Department of Finance, E-5 (Households).

For the data table behind this figure, please refer to the Data Packet Workbook, Table POPEMP-13. 330
APPENDIX A: NEEDS ANALYSIS
14 SECTOR COMPOSITION
In terms of sectoral composition, the largest industry in which Belmont residents work is Financial & Professional Services, while the Health & Educational Servicesindustry employs the most San Mateo County and Bay Area residents (see Figure 9).

Figure 9: Resident Employment by Industry
Universe: Civilian employed population age 16 years and over.

Notes: The data displayed shows the industries in which jurisdiction residents work, regardless of the location where those residents are employed (whether within the jurisdiction or not). Categories are derived from the following source tables: Agriculture & Natural Resources: C24030_003E, C24030_030E; Construction: C24030_006E, C24030_033E; Manufacturing, Wholesale & Transportation:

C24030_007E, C24030_034E, C24030_008E, C24030_035E, C24030_010E, C24030_037E; Retail: C24030_009E, C24030_036E; Information: C24030_013E, C24030_040E; Financial & Professional Services: C24030_014E, C24030_041E, C24030_017E, C24030_044E; Health & Educational Services: C24030_021E, C24030_024E, C24030_048E, C24030_051E; Other: C24030_027E, C24030_054E, C24030_028E, C24030_055E.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table C24030.

For the data table behind this figure, please refer to the Data Packet Workbook, Table POPEMP-06.

Looked at a different way, Management, Business, Science, and Arts occupations constitute approximately 66% of Belmont residents’ employment, which is substantially higher than both San Mateo County and the Bay Area as a whole.
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Figure 10: Resident Employment by Occupation
Universe: Civilian employed population age 16 years and over.

Notes: The data displayed shows the occupations of jurisdiction residents, regardless of the location where those residents are employed (whether within the jurisdiction or not).

Categories are derived from the following source tables: management, business, science, and arts occupations: C24010_003E, C24010_039E; service occupations: C24010_019E, C24010_055E; sales and office occupations: C24010_027E, C24010_063E; natural resources, construction, and maintenance occupations: C24010_030E, C24010_066E; production, transportation, and material moving occupations: C24010_034E, C24010_070E.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table C24010.

For the data table behind this figure, please refer to the Data Packet Workbook, Table POPEMP-07.

UNEMPLOYMENT
In Belmont, there was a 3.0% decrease in the unemployment rate between January 2010 and January 2021. Jurisdictions throughout the region experienced a sharp rise in unemployment in 2020 due to the impacts of the COVID-19 pandemic, though there was a general improvement and recovery in the later months of 2020.

As of May 2021, the State Employment Development Department estimated Belmont’s unemployment rate at 3.8%. By contrast, the rate for all of San Mateo County was estimated at

4.8%.
66%
50% 50%
3%
6% 7%
4%
8% 9%
17%
20% 19%
10% 17% 16%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%
100.0%
Belmont San Mateo County Bay Area
Share of Employed Residents
Service Occupations
Sales And Office Occupations
Production, Transportation, And Material Moving Occupations Natural Resources, Construction, And Maintenance Occupations Management, Business, Science, And Arts Occupations
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APPENDIX A: NEEDS ANALYSIS
16 Figure 11: Unemployment Rate
Universe: Civilian noninstitutional population ages 16 and older.

Notes: Unemployment rates for the jurisdiction level is derived from larger-geography estimates. This method assumes that the rates of change in employment and unemployment are exactly the same in each sub-county area as at the county level. If this assumption is not true for a specific sub-county area, then the estimates for that area may not be representative of the current economic conditions. Since this assumption is untested, caution should be employed when using these data. Only not seasonally-adjusted labor force (unemployment rates) data are developed for cities and CDPs.

Source: California Employment Development Department, Local Area Unemployment Statistics (LAUS), Sub-county areas monthly updates, 2010-2021. For the data table behind this figure, please refer to the Data Packet Workbook, Table POPEMP-15.

4.5 2018-2028 OCCUPATION PROJECTIONS
The State Employment Development Department published job projections for the period of 2018 to 2028. Although the data included both San Mateo and San Francisco counties, some assumptions can be made about the impact of the number of jobs and corresponding wages in the region.

Many of the occupations with the most job openings will earn the employee less than $35,000 annually. Based on 2021 State income limits, such individuals are considered extremely lowincome.

TABLE 4: OCCUPATIONS WITH THE MOST JOB OPENINGS (2018-2028) Occupational Title
Total Job
Openings
Median Hourly
Wage
Median Annual
Wage
Personal Care Aides 62,650 $12.16 $25,283
Combined Food Prep and Servers, incl. Fast Food 52,090 $13.71 $28,524 Wait Staff 48,580 $14.73 $30,632
Software Developers, Applications 38,710 $67.39 $140,175 Cashiers 37,140 $13.54 $28,161
Janitors and Cleaners, Except Maids and Housekeeping Cleaners 28,060 $14.81 $30,807 333
APPENDIX A: NEEDS ANALYSIS
B ELMONT H OUSING E LEMENT 2023 - 2031 17
Occupational Title
Total Job
Openings
Median Hourly
Wage
Median Annual
Wage
Cooks, Restaurant 26,840 $16.35 $34,016
Retail Salespersons 25,280 $14.28 $29,700
Market Research Analysis/Marketing Specialists 24,060 $42.60 $88,609 Taxi Drivers and Chauffeurs 21,540 $18.57 $38,644
Notes: Total job openings are the sum of numeric change, exits, and transfers projected between 2018 and 2028. Wages are from the 2020 first quarter and do not include self-employed or unpaid family workers. If an estimate could not be provided for wages, they are excluded from this table. Excludes "All Other" categories. These are residual codes that do not represent a detailed occupation.

Sources: U.S. Bureau of Labor Statistics' Current Employment Statistics (CES) March 2019 benchmark and Quarterly Census of Employment and Wages (QCEW) industry employment, https://www.labormarketinfo.edd.ca.gov/data/employmentprojections.html.

4.6 EXTREMELY LOW-INCOME HOUSEHOLDS
Despite the economic and job growth experienced throughout the region since 1990, the income gap has continued to widen. California is one of the most economically unequal states in the nation, and the Bay Area has the highest income inequality between high- and lowincome households in the State. 10 In Belmont, 59.5% of households make more than 100% of the Area Median Income (AMI),11 compared to 11.1% making less than 30% of AMI, which is considered extremely low-income (see Figure 12).

Regionally, more than half of all households make more than 100% AMI, while 15% make less than 30% AMI. In San Mateo County, 30% AMI is the equivalent to the annual income of $44,000 for a family of four. Many households with multiple wage earners–including food service workers, full-time students, teachers, farmworkers, and healthcare professionals–can fall into lower AMI categories due to relatively stagnant wages in many industries.

State law requires jurisdictions to estimate the number of extremely low-income households– those earning less than 30% of median income. According to the data illustrated in Figure 12, 2,318 of Belmont’s households are 0-50% AMI, while 1,143 are extremely low-income.

Therefore, extremely low-income households represent 49.3% of households who are 0-50% AMI. Figure 12 represents a tabulation of Census Bureau Data, in keeping with HCD’s guidance 10 Bohn, S.et al. 2020. Income Inequality and Economic Opportunity in California. Public Policy Institute of California.
11 Income groups are based on HUD calculations for Area Median Income (AMI). HUD calculates the AMI for different metropolitan areas, and the nine county Bay Area includes the following metropolitan areas: Napa Metro Area (Napa County), Oakland-Fremont Metro Area (Alameda and Contra Costa Counties), San Francisco Metro Area (Marin, San Francisco, and San Mateo Counties), San Jose-Sunnyvale-Santa Clara Metro Area (Santa Clara County), Santa Rosa Metro Area (Sonoma County), and Vallejo-Fairfield Metro Area (Solano County). The AMI levels in this chart are based on the HUD metro area where this jurisdiction is located. Households making between 80 and 120 percent of the AMI are moderate-income, those making 50 to 80 percent are low-income, those making 30 to 50 percent are very low-income, and those making less than 30 percent are extremely low-income. This is then adjusted for household size.
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APPENDIX A: NEEDS ANALYSIS
18 to use U.S. Census data to calculate the percentage of very low-income RHNA that qualifies for extremely low-income households.

Figure 12: Households by Household Income Level
Universe: Occupied housing units.

Notes: Income groups are based on HUD calculations for Area Median Income (AMI). HUD calculates the AMI for different metropolitan areas, and the nine county Bay Area includes the following metropolitan areas: Napa Metro Area (Napa County), Oakland-Fremont Metro Area (Alameda and Contra Costa Counties), San Francisco Metro Area (Marin, San Francisco, and San Mateo Counties), San Jose-Sunnyvale-Santa Clara Metro Area (Santa Clara County), Santa Rosa Metro Area (Sonoma County), and Vallejo-Fairfield Metro Area (Solano County). The AMI levels in this chart are based on the HUD metro area where this jurisdiction is located. The data that is reported for the Bay Area is not based on a regional AMI but instead refers to the regional total of households in an income group relative to the AMI for the county where that household is located. Local jurisdictions are required to provide an estimate for their projected extremely low-income households (0-30% AMI) in their Housing Elements. HCD’s official Housing Element guidance notes that jurisdictions can use their RHNA for very low-income households (those making 0-50% AMI) to calculate their projected extremely low-income households. As Bay Area jurisdictions have not yet received their final RHNA numbers, this document does not contain the required data point of projected extremely low-income households. The report portion of the housing data needs packet contains more specific guidance for how local staff can calculate an estimate for projected extremely low-income households once jurisdictions receive their 6th cycle RHNA numbers.

Source: U.S. Department of Housing and Urban Development (HUD), Comprehensive Housing Affordability Strategy (CHAS) ACS tabulation, 2013-2017 release.

For the data table behind this figure, please refer to the Data Packet Workbook, Table ELI-01.

Extremely low-income (ELI) households are more likely to experience housing problems and cost burden. In Belmont, there are approximately 365 ELI owner-households, representing

5.9% of owners throughout the City, and 779 ELI renter-households, representing 12.6% of renters. A nearly equal portion of ELI renter households experience cost burden greater than 30% compared to ELI owner-households, at 70.7% and 70.8%, respectively. However, as a group, renters in the extremely low-income category are disproportionately represented in cost burden–ELI renters represent 32.6% of all renter households with a cost burden, while ELI owners represent 25.2% of all owners with a cost burden. Similarly, 52.8% of renter households with a severe cost burden earn extremely low incomes, while that figure is just 43.6% for owner households.
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B ELMONT H OUSING E LEMENT 2023 - 2031 19
Overall, 11.1% of households in Belmont are ELI. By comparison, 13.3% of households countywide are in the extremely low-income category. While White households make up the bulk of the ELI households (61.2%), many households of color also earn extremely low incomes.

For example, Asian/Pacific Islander households make up 15.7% of extremely low-income households in Belmont, while Hispanic/Latinx make up 12.7% (while only representing 8.7% of the total population). Racial/ethnic, income, and housing problem demographics are further described in Appendix D, Affirmatively Furthering Fair Housing, of this Housing Element.

RESOURCES FOR EXTREMELY LOW-INCOME HOUSEHOLDS
The City remains committed to assisting in the development and preservation of existing affordable housing and will continue to focus on lifting residents out of poverty by providing a safe, attractive, and affordable place to live. While housing alone does not eliminate poverty, access to adequate shelter must be provided before people can strive for self-sufficiency.

The Housing Choice Voucher Program managed by San Mateo County also serves very low- and extremely low-income families, senior households, and persons with disabilities. The City aims to provide additional resources for ELI households through programs outlined in this Housing Element’s Implementation Plan, Appendix G. This includes additional fair housing actions from the AFFH. While there are County resources available for ELI households, this group remains vulnerable throughout the City and the region.

Understanding households by income and race/ethnic group can shed light on the challenges faced by people of color in terms of access to affordable housing. Table 5 illustrates the disparities between White and other racial/ethnic groups. Although 11% of households are extremely low-income citywide, 30% of Black/African American households are in this income category.
12 There are also regional disparities between the incomes of homeowners and renters. Typically, the number of low-income renters greatly outpaces the amount of housing available that is affordable for these households.
12These figures are somewhat skewed because White households make up the vast majority of households in the City but are illustrative of differences.
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APPENDIX A: NEEDS ANALYSIS
20 TABLE 5: HOUSEHOLD DISTRIBUTION BY RACE/ETHNICITY AND INCOME Racial / Ethnic Group
0%-30%
of AMI
31%-50%
of AMI
51%-80%
of AMI
81%-100%
of AMI
Greater
than 100%
of AMI
American Indian or Alaska Native, Non-Hispanic 14% 0% 0% 0% 86% Asian / API, Non-Hispanic 7% 6% 9% 4% 74%
Black or African American, Non-Hispanic 30% 0% 20% 7% 43% White, Non-Hispanic 11% 12% 12% 8% 56%
Other Race or Multiple Races, Non-Hispanic 25% 14% 7% 5% 48% Hispanic or Latinx 16% 25% 8% 9% 42%
Total 11% 11% 11% 7% 59%
Universe: Occupied housing units.

For the purposes of this graph, the “Hispanic or Latinx” racial/ethnic group represents those who identify as having Hispanic/Latinx ethnicity and may also be members of any racial group. All other racial categories on this graph represent those who identify with that racial category and do not identify with Hispanic/Latinx ethnicity.

Source: U.S. Department of Housing and Urban Development (HUD), Comprehensive Housing Affordability Strategy (CHAS) ACS tabulation, 2013-2017 release.

For the data table behind this figure, please refer to the Data Packet Workbook, Table ELI-02.

In Belmont, the largest proportion of renters and homeowners fall into the Greater than 100% of AMI income group (see Figure 13).

Figure 13: Household Income Level by Tenure
Universe: Occupied housing units.

Source: U.S. Department of Housing and Urban Development (HUD), Comprehensive Housing Affordability Strategy (CHAS) ACS tabulation, 2013-2017 release.

For the data table behind this figure, please refer to the Data Packet Workbook, Table POPEMP-21. 337
APPENDIX A: NEEDS ANALYSIS
B ELMONT H OUSING E LEMENT 2023 - 2031 21
Currently, people of color are more likely to experience poverty and financial instability because of federal and local housing policies that have historically excluded them from the same opportunities extended to White residents.
13 These economic disparities also leave
communities of color at higher risk for housing insecurity, displacement, and homelessness.

In Belmont, American Indian or Alaska Native (Hispanic and Non-Hispanic) residents experience the highest poverty rates, followed by Black or African American (Hispanic and Non-Hispanic) residents (see Figure 14).

Figure 14: Poverty Status by Race
Universe: Population for whom poverty status is determined.

Notes: The Census Bureau uses a federally defined poverty threshold that remains constant throughout the country and does not correspond to Area Median Income. For this table, the Census Bureau does not disaggregate racial groups by Hispanic/Latinx ethnicity.

However, data for the white racial group is also reported for white householders who are not Hispanic/Latinx. Since residents who identify as white and Hispanic/Latinx may have very different experiences within the housing market and the economy from those who identify as white and non-Hispanic/Latinx, data for multiple white sub-groups are reported here. The racial/ethnic groups reported in this table are not all mutually exclusive. Therefore, the data should not be summed as the sum exceeds the population for whom poverty status is determined for this jurisdiction. However, all groups labelled “Hispanic and Non-Hispanic” are mutually exclusive, and the sum of the data for these groups is equivalent to the population for whom poverty status is determined.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B17001(A-I). For the data table behind this figure, please refer to the Data Packet Workbook, Table ELI-03.

4.7 TENURE
The number of residents who own their homes compared to those who rent their homes can help identify the level of housing insecurity, or the ability for individuals to stay in their homes, within a city and region. Generally, renters may be displaced more quickly if prices increase. In Belmont, there are 10,285 housing units, and fewer residents rent (39.2%) than own (60.8%). As 13 Moore, E., Montojo, N. and Mauri, N., 2019. Roots, Race & Place: A History of Racially Exclusionary Housing the San Francisco Bay Area. Hass Institute.
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APPENDIX A: NEEDS ANALYSIS
22 seen in Figure 15, this is similar to San Mateo County, though in the Bay Area as a whole, a greater percentage rent (43.9%).

Figure 15: Housing Tenure
Universe: Occupied housing units.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B25003.

For the data table behind this figure, please refer to the Data Packet Workbook, Table POPEMP-16.

Homeownership rates often vary considerably across race/ethnicity in the Bay Area and throughout the country. These disparities not only reflect differences in income and wealth but also stem from federal, state, and local policies that limited access to homeownership for communities of color while facilitating homebuying for White residents. While many of these policies, such as redlining, have been formally disbanded, the impacts of race-based policies are still evident across Bay Area communities.
14 In Belmont, 14.8% of Black households owned their homes, while homeownership rates were

43.2% for Latinx households, 62.3% for Asian households, and 63.8% for White households.

Recent changes to State law require local jurisdictions to examine these dynamics and other fair housing issues when updating their Housing Elements.

The age of residents who rent or own their home can also signal housing challenges. Younger households tend to rent and may struggle to buy a first home in the Bay Area due to high housing costs, while senior homeowners seeking to downsize may have limited options in an expensive housing market.
14 See, for example, Rothstein, R. (2017). The color of law: a forgotten history of how our government segregated America. New York, NY & London, UK: Liveright Publishing. 339
APPENDIX A: NEEDS ANALYSIS
B ELMONT H OUSING E LEMENT 2023 - 2031 23
Figure 16: Housing Tenure by Race of Householder
Universe: Occupied housing units.

Notes: For this table, the Census Bureau does not disaggregate racial groups by Hispanic/Latinx ethnicity. However, data for the white racial group is also reported for white householders who are not Hispanic/Latinx. Since residents who identify as white and Hispanic/Latinx may have very different experiences within the housing market and the economy from those who identify as white and non-Hispanic/Latinx, data for multiple white sub-groups are reported here. The racial/ethnic groups reported in this table are not all mutually exclusive. Therefore, the data should not be summed as the sum exceeds the total number of occupied housing units for this jurisdiction. However, all groups labelled “Hispanic and Non-Hispanic” are mutually exclusive, and the sum of the data for these groups is equivalent to the total number of occupied housing units.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B25003(A-I).

For the data table behind this figure, please refer to the Data Packet Workbook, Table POPEMP-20.

In Belmont, 58.4% of householders between the ages of 25 and 44 are renters, while 25.0% of householders over 65 are (see Figure 17).

Information regarding the year in which a household moved to their current residence further illustrates the differences between long-term residents, who tend to trend older, and newer residents. As shown in Figure 18, 93% of households that moved in in 1989 or earlier are owner occupied, whereas only 22% of households that moved in in 2017 or later are owner occupied.

In many cities, homeownership rates for households in single-family homes are substantially higher than the rates for households in multi-family housing. In Belmont, 91.1% of households in detached single-family homes are homeowners, while 11.3% of households in multi-family housing are homeowners (see Figure 19).
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APPENDIX A: NEEDS ANALYSIS
24 Figure 17: Housing Tenure by Age
Universe: Occupied housing units.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B25007.

For the data table behind this figure, please refer to the Data Packet Workbook, Table POPEMP-18.

Figure 18: Housing Tenure by Year Moved to Current Residence Universe: Occupied housing units.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B25038.

For the data table behind this figure, please refer to the Data Packet Workbook, Table POPEMP-19. 93% 89%
70%
44% 34%
22%
7% 11%
30%
56% 66%
78%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Moved In
1989 Or
Earlier
Moved In
1990 To
1999
Moved In
2000 To
2009
Moved In
2010 To
2014
Moved In
2015 To
2016
Moved In
2017 Or
Later
Percent of Households
Owner Occupied Renter Occupied
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APPENDIX A: NEEDS ANALYSIS
B ELMONT H OUSING E LEMENT 2023 - 2031 25
Figure 19: Housing Tenure by Housing Type
Universe: Occupied housing units.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B25032. For the data table behind this figure, please refer to the Data Packet Workbook, Table POPEMP-22.

4.8 DISPLACEMENT
Due to increasing housing prices, displacement is a major concern in the Bay Area.

Displacement has the most severe impacts on low- and moderate-income residents. When individuals or families are forced to leave their homes and communities, they also lose their support network.

The University of California (UC), Berkeley has mapped all neighborhoods in the Bay area, identifying their risk for gentrification. They found that in Belmont, no households are Susceptible to or Experiencing Displacement or are At Risk of or Undergoing Gentrification.

Equally important, some Bay Area neighborhoods do not have housing appropriate for a broad section of the workforce. UC Berkeley estimates that 45.5% of households in Belmont live in neighborhoods where low-income households are likely to be excluded due to prohibitive housing costs.
15 15 More information about this gentrification and displacement data is available at the Urban Displacement Project’s webpage: https://www.urbandisplacement.org/. Specifically, one can learn more about the different gentrification/displacement typologies shown in Figure 20 at this link: https://www.urbandisplacement. org/sites/default/files/typology_sheet_2018_0.png. Additionally, one can view maps that show which typologies correspond to which parts of a jurisdiction here: https://www.urbandisplacement.org/san-francisco/sf-bay-areagentrification-and-displacement. 342
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26 Figure 20: Households by Displacement Risk and Tenure Universe: Households.

Notes: Displacement data is available at the census tract level. Staff aggregated tracts up to jurisdiction level using census 2010 population weights, assigning a tract to jurisdiction in proportion to block level population weights. Total household count may differ slightly from counts in other tables sourced from jurisdiction level sources. Categories are combined as follows for simplicity: At risk of or Experiencing Exclusion: At Risk of Becoming Exclusive; Becoming Exclusive; Stable/Advanced Exclusive At risk of or Experiencing Gentrification: At Risk of Gentrification; Early/Ongoing Gentrification; Advanced Gentrification Stable Moderate/Mixed Income: Stable Moderate/Mixed Income Susceptible to or Experiencing Displacement: Low-Income/Susceptible to Displacement; Ongoing Displacement Other: High Student Population; Unavailable or Unreliable Data.

Source: Urban Displacement Project for classification, American Community Survey 5-Year Data (2015-2019), Table B25003 for tenure.

For the data table behind this figure, please refer to the Data Packet Workbook, Table POPEMP-25. 343
B ELMONT H OUSING E LEMENT 2023 - 2031 27

5. HOUSING STOCK CHARACTERISTICS

5.1 HOUSING TYPES, YEAR BUILT, VACANCY, AND PERMITS
In recent years, most housing produced in the region and across the State has consisted of single-family homes and larger multi-unit buildings. However, some households are increasingly interested in “missing middle housing” –including duplexes, triplexes, townhomes, cottage clusters, and accessory dwelling units (ADUs). These housing types may open more options across incomes and tenure, from young households seeking homeownership to seniors looking to downsize and age-in-place.

The 2020 Belmont housing stock was made up of 58.0% single-family detached homes, 32.9% multi-family homes with five or more units, 6.0% single-family attached homes, 3.1% multifamily homes with two to four units, and 0.0% mobile homes (see Figure 21). From 2010 to 2020, the housing type that experienced the most growth was Single-Family Home: Detached.

Figure 21: Housing Type Trends
Universe: Housing units.

Source: California Department of Finance, E-5 series.

For the data table behind this figure, please refer to the Data Packet Workbook, Table HSG-01.

For several decades, Bay Area housing production has not kept pace with the demand; the total number of units built and available has not yet neared the regional population and job growth.

In Belmont, the largest proportion of the housing stock (5,131 units) was built from 1960 to 1979 (see Figure 22). Since 2010, 1.4% (or 149 units) of the current housing stock has been built. 344
APPENDIX A: NEEDS ANALYSIS
28 Figure 22: Housing Units by Year Structure Built
Universe: Housing units.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B25034.

For the data table behind this figure, please refer to the Data Packet Workbook, Table HSG-04.

Vacant units constitute 6.5% of Belmont’s overall housing stock. The rental vacancy rate stands at 10.0%, while the ownership vacancy rate is 0.8%. Of the vacant units, the most common type of vacancy is For Rent (see Figure 23).16
Throughout the Bay Area, vacancies make up 2.6% of the total housing units, with homes listed for rent; units for seasonal, recreational, or occasional use; and units not otherwise classified (other vacant) making up the majority of vacancies. The Census Bureau classifies a unit as vacant if no one is occupying it when census interviewers are conducting the American Community Survey or Decennial Census. Units classified as for seasonal, recreational, or occasional use are those held for short-term periods of use throughout the year, such as vacation rentals and short-term rentals like AirBnB.

The Census Bureau classifies units as other vacant when vacancy occurs due to foreclosure, personal/ family reasons, legal proceedings, repairs/renovations, abandonment, preparation for being rented or sold, or an extended absence for reasons such as a work assignment, military duty, or incarceration.17 In a region with a thriving economy and housing market like the Bay Area, units being renovated/repaired and prepared for rental or sale are also likely to represent a large portion of this category. Additionally, the need for seismic retrofitting in older housing 16 The vacancy rates by tenure is for a smaller universe than the total vacancy rate first reported, which in principle includes the full stock (6.5%). The vacancy by tenure counts are rates relative to the rental stock (occupied and vacant) and ownership stock (occupied and vacant) - but exclude a significant number of vacancy categories, including the numerically significant other vacant.
17 For more information, see pages 3 through 6 of this list of definitions prepared by the Census Bureau, https://www.census.gov/housing/hvs/definitions.pdf.
345
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B ELMONT H OUSING E LEMENT 2023 - 2031 29
stock could influence other vacant rates.
18 In Belmont, the State Department of Finance
currently estimates the vacancy rate is approximately 5.7%. Countywide, it is estimated at

5.5%.

Figure 23: Vacant Units by Type
Universe: Vacant housing units.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B25004.

For the data table behind this figure, please refer to the Data Packet Workbook, Table HSG-03.

From 2015 to 2021, Belmont issued permits for 508 housing units. Of these, 70% were for above moderate-income housing, 10% were for moderate-income housing, and 20% were for low- or very low-income housing (see Table 6).

TABLE 6: CITY OF BELMONT HOUSING PERMITTING (2015-2021) Income Group Number of Permits Issued
Above Moderate-income Permits 378
Moderate-income Permits 0
Low-income Permits 84
Very Low-income Permits 46
Universe: Housing permits issued between 2015 and 2021.

Notes: HCD uses the following definitions for the four income categories: Very Low-income: units affordable to households making less than 50% of the Area Median Income for the county in which the jurisdiction is located. Lowincome: units affordable to households making between 50% and 80% of the Area Median Income for the county in which the jurisdiction is located. Moderate Income: units affordable to households making between 80% and 120% of the Area Median Income for the county in which the jurisdiction is located. Above Moderate-income: units affordable to households making above 120% of the Area Median Income for the county in which the jurisdiction is located.

Source: California Department of Housing and Community Development (HCD), 5th Cycle Annual Progress Report Permit Summary (2020).
18 See Dow, P. (2018). Unpacking the Growth in San Francisco’s Vacant Housing Stock: Client Report for the San Francisco Planning Department. University of California, Berkeley. 346
APPENDIX A: NEEDS ANALYSIS
30 5.2 ASSISTED HOUSING DEVELOPMENTS AT-RISK OF CONVERSION While there is an immense need to produce new affordable housing units, ensuring that the existing affordable housing stock remains affordable is equally important. It is typically faster and cheaper to preserve existing affordable units that are at risk of converting to market-rate than it is to build new affordable housing.

The California Housing Partnership Corporation’s (CHPC) Preservation Database provides comprehensive data available on at-risk units. Table 7 shows the number of subsidized affordable housing at risk of losing their affordable status and converting to market-rate in Belmont, the County, and the region. However, this database does not include all deedrestricted affordable units in the State, so there may be at-risk assisted units in a jurisdiction that are not captured in this table.

TABLE 7: ASSISTED UNITS AT RISK OF CONVERSION
Risk Level Belmont San Mateo County Bay Area
Low 84 4,656 110,177
Moderate 0 191 3,375
High 0 359 1,854
Very High 0 58 1,053
Total Assisted Units in Database 84 5,264 116,459
Universe: HUD, Low-income Housing Tax Credit (LIHTC), USDA, and CalHFA projects. Subsidized or assisted developments that do not have one of the aforementioned financing sources may not be included.

Notes: While California Housing Partnership’s Preservation Database is the state’s most comprehensive source of information on subsidized affordable housing at risk of losing its affordable status and converting to market-rate housing, this database does not include all deed-restricted affordable units in the state. Consequently, there may be at-risk assisted units in a jurisdiction that are not captured in this data table. Per HCD guidance, local jurisdictions must also list the specific affordable housing developments atrisk of converting to market rate uses. This document provides aggregate numbers of at-risk units for each jurisdiction, but local planning staff should contact Danielle Mazzella with the California Housing Partnership at [email protected] to obtain a list of affordable properties that fall under this designation.

Source: California Housing Partnership, Preservation Database (2020).

This table is included in the Data Packet Workbook as Table RISK-01.

According to the CHPC Perseveration Database, there are 84 assisted units in Belmont and of these units, none are at High Risk or Very High Risk of conversion. 19 19 California Housing Partnership uses the following categories for assisted housing developments in its database:

Very-High Risk: affordable homes that are at-risk of converting to market rate within the next year that do not have a known overlapping subsidy that would extend affordability and are not owned by a large/stable non-profit, mission-driven developer.

High Risk: affordable homes that are at-risk of converting to market rate in the next 1-5 years that do not have a known overlapping subsidy that would extend affordability and are not owned by a large/stable non-profit, missiondriven developer. 347
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B ELMONT H OUSING E LEMENT 2023 - 2031 31
As of 2023, Belmont had a total of 302 affordable units, rather than the 84 noted by CHPC; this discrepancy is partially due to the City funding a few projects solely through the now-dissolved Redevelopment Agency.

As Table 8 indicates, there are a total of 106 units that are potentially at risk of conversion during this Housing Element planning period, which includes 104 units located in the Bonnie Brae Terrace complex and two single family properties at Oxford Place. The Bonnie Brae Terrace property has been purchased by a new owner who has stated their commitment to maintaining the unit affordability. The Oxford Place units are owned by moderate-income households who can either remain in the property or sell it after 2030. Any proceeds above a calculated moderate-income sales price would be taken by the City, which incentivizes an owner to sell to another qualifying purchaser. Belmont has confirmed that it does not have any publicly assisted housing units at-risk of conversion in the next ten years; however, annual monitoring as part of the Housing Element Annual Progress Report is still an important tool to ensure unit affordability.

This Housing Element includes Program H2.1, Support Retention of Existing Lower-income Units, which directs the City to continue monitoring all units potentially at risk of conversion to market rate annually.

Moderate Risk: affordable homes that are at-risk of converting to market rate in the next 5-10 years that do not have a known overlapping subsidy that would extend affordability and are not owned by a large/stable non-profit, mission-driven developer.

Low Risk: affordable homes that are at-risk of converting to market rate in 10+ years and/or are owned by a large/stable non-profit, mission-driven developer.
348
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32 TABLE 8: CITY OF BELMONT INVENTORY OF PUBLICLY ASSISTED HOUSING PROJECTS (2023) Project Name
Building
Type
Total
Units
Affordable
Units Household Type Funding Sources Conversion Risk
Expiration
Date
Bonnie Brae Terrace
(formerly Lesley Terrace):
2400 Carlmont Dr
Apartment 164 164
All lower-income groups Section 8 (60 units) Low Section 8 - 2039 Disabled; Seniors Program 236
(104 units) Medium
2031 (operator has indicated
rents will remain below market
rate)
Horizons:
825 Old County Rd Apartment 24 24 Very low-income
Families; Disabled
Section 8; City Housing
Successor Loan;
Program 202/162
Low; Non-profit
manages
2039
Belmont House:
730 El Camino Real Group Home 6 6 Low-income Disabled City RDA; City Housing Successor Low; City-owned No expiration; City-owned property Crestview Group Home:
503 Crestview Group Home 6 6 Low- and moderateincome Disabled County CDBG & State
deferred loan; City
Housing Successor
Low; City-owned No expiration; City-owned
property
Sterling Point:
935 Old County Rd
Townhomes
(BMR) 48 7 Moderate-income Firsttime home buyers City RDA Medium; Units owned by residents 2039, 2041, 2041, 2041, 2042,
2042, 2042
Waltermire Apartments:
631 Waltermire St Apartment 10 2 Moderate-income Families City RDA Medium 2039 Belmont Apartments:
800 F St Apartment 24 24 Very low-income
Disabled
City RDA; HOME;
Mental Health
Association of SMC
Low; MHA Owned 2058
Oxford Place:
25 and 41 Oxford Place
Single-family
detached 21 2 Moderate-income
Families City RDA Medium; BMR units
owned by residents
2030
(30-year term renews when
property sold)
Emmett House, 1000
O’Neill Duplex 2 2 Moderate-income Families City RDA Low; City-owned No expiration; City-owned property Firehouse Square, 1300 El
Camino Real Apartment 66 65 All lower-income groups; AHF, County, City, TCAC Low; Non-profit
manages
2090
Total 371 302
Source: City of Belmont, 2024.
349
B ELMONT H OUSING E LEMENT 2023 - 2031 33

5.3 SUBSTANDARD HOUSING
Regional housing costs are among the highest in the country, which could result in households—particularly renters—living in substandard conditions to afford housing. Generally, there is limited data on the extent of substandard housing in a community; however, the Census Bureau data included in Figure 24 provides a sense of some substandard conditions that may be present in Belmont. For example, 6.6% of Belmont renters reported lacking a complete kitchen and 0.3% of renters lacked complete plumbing, compared to 0.6% of owners who lack a complete kitchen and 0.0% of owners who lacked complete plumbing.

Figure 24: Substandard Housing Issues
Universe: Occupied housing units.

Notes: Per HCD guidance, this data should be supplemented by local estimates of units needing to be rehabilitated or replaced based on recent windshield surveys, local building department data, knowledgeable builders/developers in the community, or nonprofit housing developers or organizations.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B25053, Table B25043, Table B25049.

For the data table behind this figure, please refer to the Data Packet Workbook, Table HSG-06.

Another measure of housing condition is the age of housing. In general, the older the unit, the greater it can be assumed to need some level of rehabilitation. A general rule in the housing industry is that structures older than 20 years begin to show signs of deterioration and require renovation to maintain their quality. Unless properly maintained, homes older than 50 years can pose health, safety, and welfare problems for occupants.

Consistent with State law, Table 9 estimates the number of units in need of rehabilitation or replacement in Belmont. Although the exact number of units in need of rehab is not currently known, the State accepts estimates based on a formula that assumes the older the unit, the more likely the rehab is in need. Rehabilitation needs can range from minor repairs to major structural replacements.

By applying an increasing percentage to the housing stock in each age category, it is estimated that there are approximately 1,311 units in need of some level of rehabilitation in Belmont, 350
APPENDIX A: NEEDS ANALYSIS
34 representing 12% of the housing stock. It is estimated that nearly all units in need of rehabilitation can be repaired without replacement.

TABLE 9: AGE OF HOUSING STOCK AND ESTIMATED REHABILITATION NEEDS Net #
of Units
Percent
of Total
Units Needing
Rehab, %
Units Needing
Rehab, Total
Built 2014 or Later 87 0%
Built 2010 to 2013 62 0%
Built 2000 to 2009 395 1% 0.50% 2
Built 1990 to 1999 674 2% 1% 7
Built 1980 to 1989 909 2% 3% 27
Built 1970 to 1979 2,165 5% 5% 108
Built 1960 to 1969 2,966 7% 10% 297
Built 1950 to 1959 2,525 6% 20% 505
Built 1940 to 1949 833 2% 30% 250
Built 1939 or Earlier 384 1% 30% 115
Total 11,000 26% 1,311
Percentage of Total Units 12%
Units that Can Be Repaired 99.50% 1,304
Units that Must Be Replaced 0.50% 7
Source: American Community Survey 5-year estimates, 2019.

The most common code enforcement activities, as provided by Belmont’s Code Enforcement Officer, includes residential yard and tree maintenance, illegal dumping, construction without permits, abandoned/inoperable vehicles, smoking in multi-family residential units (which is prohibited in Belmont), trash and debris in public view, rodent infestation, and dilapidated property fences. None of these frequent violation types provides insight into the estimated number of housing units in need of rehabilitation. Additionally, the code enforcement officer has confirmed that estimating rehabilitation needs based on age of housing stock is a reasonable measure. There do not appear to be any visual housing stock trends (i.e., boarded up windows/doors, roof or other structural damage, or significant external damage) in Belmont that would further guide housing rehabilitation needs/services.

Housing Program H3.3 directs the City of Belmont to conduct a best practice review of local housing rehabilitation programs that the City can help provide to residents, and to research rehabilitation service providers that could target special needs groups. 351
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B ELMONT H OUSING E LEMENT 2023 - 2031 35

5.4 HOME AND RENT VALUES
Home prices reflect a complex mix of supply and demand factors, including an area’s demographic profile, labor market, prevailing wages, and job outlook, coupled with land and construction costs. In the San Francisco Bay Area, the costs of housing have long been among the highest in the nation. According to Zillow, the typical home value in Belmont in December 2020 was estimated at $1,876,610, while the largest proportion of homes were valued between $1M to $2M (see Figure 25). By comparison, the typical home value was $1,418,330 in San Mateo County and $1,077,230 in the Bay Area, with the largest share of units valued at $1M to $1.5M (County) and $500k to $750k (region).

The region’s home values have increased steadily since 2000, apart from a decrease during the Great Recession. The rise in home prices has been especially steep since 2012, with the median Bay Area home value nearly doubling. In Belmont, the typical home value has increased 166.7% between 2001 and 2020, from $703,600 to $1,876,610. Generally, the increase in home value has been greater in Belmont than in the County and the region (see Figure 26).

Figure 25: Home Values of Owner-Occupied Units
Universe: Owner-occupied units.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B25075.

For the data table behind this figure, please refer to the Data Packet Workbook, Table HSG-07. 352
APPENDIX A: NEEDS ANALYSIS
36 Figure 26: Zillow Home Value Index (ZHVI)
Universe: Owner-occupied housing units.

Notes: Zillow describes the ZHVI as a smoothed, seasonally adjusted measure of the typical home value and market changes across a given region and housing type. The ZHVI reflects the typical value for homes in the 35th to 65th percentile range. The ZHVI includes all owner-occupied housing units, including both single-family homes and condominiums. More information on the ZHVI is available from Zillow. The regional estimate is a household-weighted average of county-level ZHVI files, where household counts are yearly estimates from DOF’s E-5 series For unincorporated areas, the value is a population weighted average of unincorporated communities in the county matched to census-designated population counts.

Source: Zillow, Zillow Home Value Index (ZHVI). Refer to the Workbook, Table HSG-08.

Like home values, rents have increased dramatically across the Bay Area in recent years. Many renters have been priced out, evicted, or displaced, particularly communities of color. Residents finding themselves in one of these situations may have had to choose between commuting long distances to their jobs and schools or moving out of the region, or even state.

In Belmont, from 2015 to 2019, the largest proportion (27.6%) of rental units fell into the Rent $2,000-$2,500 category (see Figure 27). During this period, 18.7% of units were in the Rent $2,500-$3,000 category. Looking beyond the city, the largest share of units is in the $3,000 or more category (County), or $1,500-$2,000 category (region).

From 2009 to 2019, the median rent increased by 76.8% in Belmont, from $1,520 to $2,250 monthly (see Figure 28). In San Mateo County, the median rent increased 41.1%, from $1,560 to $2,200. The median rent in the region was lower, but also increased significantly during this time, from $1,200 to $1,850, a 54% increase.20
20 While the data on home values shown in Figure 26 comes from Zillow, Zillow does not have data on rent prices available for most Bay Area jurisdictions. To have a more comprehensive dataset on rental data for the region, the rent data in this document comes from the U.S. Census Bureau’s American Community Survey, which may not fully reflect current rents. Local jurisdiction staff may want to supplement the data on rents with local realtor data or other sources for rent data that are more current than Census Bureau data. 353
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B ELMONT H OUSING E LEMENT 2023 - 2031 37
Figure 27: Contract Rents for Renter-Occupied Units
Universe: Renter-occupied housing units paying cash rent.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B25056.

For the data table behind this figure, please refer to the Data Packet Workbook, Table HSG-09.

Figure 28: Median Contract Rent
Universe: Renter-occupied housing units paying cash rent.

Notes: For unincorporated areas, median is calculated using distribution in B25056.

Source: U.S. Census Bureau, American Community Survey 5-Year Data releases, starting with 2005-2009 through 2015-2019, B25058, B25056 (for unincorporated areas). County and regional counts are weighted averages of jurisdiction median using B25003 rental unit counts from the relevant year.

For the data table behind this figure, please refer to the Data Packet Workbook, Table HSG-10. 354
APPENDIX A: NEEDS ANALYSIS
38 5.5 HOUSING AFFORDABILITY
The National Association of Homebuilders reports that California cities have some of the lowest homeowner affordability rates in the Country, defined as the percentage of homes affordable to a median income family. Despite high median incomes, many in the Bay Area cannot afford to purchase a home. The San Francisco-Redwood City Division, of which Belmont is a part, ranked 230th out of 233 metropolitan areas studied in the first quarter of 2021.

TABLE 10: HOUSING OPPORTUNITY INDEX (FIRST QUARTER, 2021) Homes
Affordable to
Median Income
Households
Median
Family Income
(1,000s)
Median
Sales Price
(1,000s)
National
Affordability
Rank
Los Angeles-Long Beach-Glendale, CAa 11.6% 78.7 729 233 Salinas, CA 15.1% 80.9 725 232
San Francisco-Redwood City-South SFa 17.4% 143.4 1,305 230 Anaheim-Santa Ana-Irvine, CAa 18.2% 104.8 825 229
Napa, CA 22.1% 101.5 691 228
San Diego-Carlsbad, CA 22.4% 95.1 665 227
San Luis Obispo-Paso Robles-Arroyo Grande, CA 26.0% 97.8 675 226 Oxnard-Thousand Oaks-Ventura, CA 27.4% 98.8 650 225
Santa Cruz-Watsonville, CA 28.5% 111.9 850 224
Santa Maria-Santa Barbara, CA 28.8% 90.1 678 223
Stockton-Lodi, CA 29.6% 74.0 462 222
San Jose-Sunnyvale-Santa Clara, CA 29.9% 151.3 1,120 220 Oakland-Hayward-Berkeley, CAa 31.2% 121.3 795 219
a Indicate Metropolitan Divisions. All others are MSAs.

Source: National Association of Homebuilders, 2021, https://www.nahb.org/news-and-economics/housing-economics/indices/ housing-opportunity-index.

Trulia—an online residential real estate site for homebuyers, sellers, renters, and real estate professionals—provides statistics based on actual sales of housing by location. According to a study conducted by zip code in 2019, only 0.2% of homes were affordable to the metropolitan median income of $101,000. The median home value reported by Trulia was $1,570,186. See https://www.trulia.com/research/affordable-neighborhoods/ for more information.

The high cost of housing means people wanting to own a home in Belmont must have significant incomes, even for the relatively less-expensive condominiums. In Belmont, a household must earn more than $400,000 annually to afford the Trulia-documented median priced home.

The decreasing supply of affordable rental units is a countywide phenomenon; it can include Ellis Act evictions (where an owner of a rental property decides to leave the rental business) to owner move-in evictions. Until additional construction of rental units occurs, the combination 355
APPENDIX A: NEEDS ANALYSIS
B ELMONT H OUSING E LEMENT 2023 - 2031 39
of strong demand and low vacancies will contribute to create an increasingly severe shortage of rental units, decreasing their affordability.

Table 11 illustrates affordable rents by income category. In the case of an extremely lowincome household of two people (for example, a single parent with a child), the annual income of $43,850 translates to a full-time job paying $21.08 per hour. In this scenario, the maximum rent they could afford would be approximately $1,096 per month–far below average rents in Belmont, even for studios. According to statistics on RentCafe.com, an online data aggregator, the average rent for an apartment was $2,401 as of June 2021, a decrease of 14% from the previous year but still much higher than what a lower-income household can afford. A household must earn at least $96,040 annually to afford the average rent.

TABLE 11: AFFORDABLE RENTS FOR TWO- AND THREE-PERSON HOUSEHOLDS Income Category
Percent
of Median
Income Limit
(Two-Person
Household)
Two-Person
Affordable
Rent
Income Limit
(Three-Person
Household)
Three-Person
Affordable Rent
Extremely Low-income 30% $43,850 $1,096 $49,350 $1,234
Very Low-income 50% $73,100 $1,828 $82,250 $2,056
Low-income 80% $117,100 $2,928 $131,750 $3,294
Median-income 100% $119,700 $2,993 $134,650 $3,366
Moderate-income 120% $143,600 $3,590 $161,550 $4,039
Notes: Affordable rents are calculated based on 30% of annual income divided by 12 months.

Source: State Department of Housing and Community Development and City of Belmont, 2021.

Through Section 8 and other housing programs, the Department of Housing and Community Development (HUD) provides rental housing assistance to lower-income households.

According to HUD, 62 households in Belmont currently receive Section 8 rental assistance, in the form of Housing Choice Vouchers.

5.6 OVERPAYMENT AND OVERCROWDING
A household is considered “cost-burdened” if it spends more than 30% of its monthly income on housing costs, while those who spend more than 50% of their income on housing costs are considered “severely cost-burdened.” Low-income residents are the most impacted by high housing costs and experience the highest rates of cost burden. Spending such large portions of their incomes on housing puts low-income households at higher risk of displacement, eviction, or homelessness.

Renters are often more cost-burdened than owners. While home prices have increased dramatically, homeowners often have mortgages with fixed rates, whereas renters are more likely to be impacted by ongoing market increases.

Looking at cost burden by tenure in Belmont, 23.6% of renters spend 30% to 50% of their income on housing compared to 12.5% of those who own (see Figure 29). In addition, 20.7% of 356
APPENDIX A: NEEDS ANALYSIS
40 renters are severely cost-burdened (spending 50% or more of their income on housing), while only 7.5% of owners fall into this category.

Figure 29: Cost Burden by Tenure
Universe: Occupied housing units.

Notes: Cost burden is the ratio of housing costs to household income. For renters, housing cost is gross rent (contract rent plus utilities).

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B25070, B25091.

For the data table behind this figure, please refer to the Data Packet Workbook, Table OVER-06.

In Belmont, 15% of households spend 50% or more of their income on housing, while 18.1% spend 30% to 50% (see Figure 30). However, these rates vary greatly across income categories; for example, 76.4% of Belmont households making less than 30% of AMI spend most of their income on housing. For Belmont residents making more than 100% of AMI, just 0.3% are severely cost-burdened, and 89.9% of those making more than 100% of AMI spend less than 30% of their income on housing.

Currently, people of color are more likely to experience poverty and financial instability because of federal and local housing policies that have historically excluded them from the same opportunities extended to White residents. As a result, they often spend a greater percentage of their income on housing and are at a greater risk of housing insecurity.

American Indian or Alaska Native, Non-Hispanic residents are the most cost burdened with

50.0% spending 30% to 50% of their income on housing, and Black or African American, NonHispanic residents are the most severely cost burdened with 30% spending more than 50% of their income on housing (see Figure 31).
357
APPENDIX A: NEEDS ANALYSIS
B ELMONT H OUSING E LEMENT 2023 - 2031 41
Figure 30: Cost Burden by Income Level
Universe: Occupied housing units.

Notes: Cost burden is the ratio of housing costs to household income. For renters, housing cost is gross rent (contract rent plus utilities).

For owners, housing cost is “select monthly owner costs”, which includes mortgage payment, utilities, association fees, insurance, and real estate taxes. HUD defines cost-burdened households as those whose monthly housing costs exceed 30% of monthly income, while severely cost-burdened households are those whose monthly housing costs exceed 50% of monthly income. Income groups are based on HUD calculations for Area Median Income (AMI). HUD calculates the AMI for different metropolitan areas, and the nine county Bay Area includes the following metropolitan areas: Napa Metro Area (Napa County), Oakland-Fremont Metro Area (Alameda and Contra Costa Counties), San Francisco Metro Area (Marin, San Francisco, and San Mateo Counties), San Jose-Sunnyvale-Santa Clara Metro Area (Santa Clara County), Santa Rosa Metro Area (Sonoma County), and Vallejo-Fairfield Metro Area (Solano County). The AMI levels in this chart are based on the HUD metro area where this jurisdiction is located.

Source: U.S. Department of Housing and Urban Development (HUD), Comprehensive Housing Affordability Strategy (CHAS) ACS tabulation, 2013-2017 release.

For the data table behind this figure, please refer to the Data Packet Workbook, Table OVER-05.

Figure 31: Cost Burden by Race
Universe: Occupied housing units.

Notes: Cost burden is the ratio of housing costs to household income. For renters, housing cost is gross rent (contract rent plus utilities).

For owners, housing cost is “select monthly owner costs”, which includes mortgage payment, utilities, association fees, insurance, and real estate taxes. HUD defines cost-burdened households as those whose monthly housing costs exceed 30% of monthly income, while severely cost-burdened households are those whose monthly housing costs exceed 50% of monthly income. For the purposes of this graph, the “Hispanic or Latinx” racial/ethnic group represents those who identify as having Hispanic/Latinx ethnicity and may also be members of any racial group. All other racial categories on this graph represent those who identify with that racial category and do not identify with Hispanic/Latinx ethnicity.

Source: U.S. Department of Housing and Urban Development (HUD), Comprehensive Housing Affordability Strategy (CHAS) ACS tabulation, 2013-2017 release.

For the data table behind this figure, please refer to the Data Packet Workbook, Table OVER-08. 358
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42 Cost burden by tenure and income category reveals the extent to which lower-income groups, especially renters, pay too much for housing costs. Table 12 below provides data on extremely low-, very low, and low-income households compared with higher-income groups. Both extremely low-income renters and owners have high rates of cost burden, as do other lowerincome groups. However, overall, owners are much less impacted by cost burdens than renters:
in total, 18% of owners have a cost burden of more than 30%, and only 8% have burdens over 50%. By contrast, 42% of all renters have a cost burden of more than 30%, and 20% have the severe cost burden of over 50%. Although renters account for about 39% of all households, they represent more than 60% of cost-burdened households.

Large family households often have special housing needs due to a lack of adequately sized affordable housing. The higher costs required for homes with multiple bedrooms can result in larger families experiencing a disproportionate cost burden when compared to the rest of the population, increasing their risk of housing insecurity.

In Belmont, 9.8% of large family households experience a cost burden of 30% to 50%, while

11.4% of households spend more than half of their income on housing (see Figure 32).

Approximately 18.6% of all other households have a cost burden of 30% to 50%, with 15.2% of households spending more than 50% of their income on housing.

TABLE 12: COST BURDEN BY TENURE AND INCOME
Income by Cost Burden (Renters Only) Cost Burden > 30% Cost Burden > 50% Total Household Income <= 30% HAMFI 555 425 785
Household Income >30% to <=50% HAMFI 585 315 625
Household Income >50% to <=80% HAMFI 375 65 775
Household Income >80% to <=100% HAMFI 120 0 385
Household Income >100% HAMFI 70 0 1,455
Total 1,705 805 4,030
Income by Cost Burden (Owners only)
Household Income <= 30% HAMFI 255 205 360
Household Income >30% to <=50% HAMFI 165 105 410
Household Income >50% to <=80% HAMFI 190 100 550
Household Income >80% to <=100% HAMFI 195 45 505
Household Income >100% HAMFI 315 15 4,435
Total 1,120 470 6,255
Source: CHAS Databook, https://www.huduser.gov/portal/datasets/cp.html. 359
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Figure 32: Cost Burden by Household Size
Universe: Occupied housing units.

Notes: Cost burden is the ratio of housing costs to household income. For renters, housing cost is gross rent (contract rent plus utilities).

Source: U.S. Department of Housing and Urban Development (HUD), Comprehensive Housing Affordability Strategy (CHAS) ACS tabulation, 2013-2017 release.

For the data table behind this figure, please refer to the Data Packet Workbook, Table OVER-09.

When cost-burdened seniors are no longer able to make house payments or pay rents, displacement from their homes can occur, placing further stress on the local rental market or forcing residents out of the community they call home. Understanding how seniors might be cost-burdened is of particular importance due to their special housing needs, particularly for low-income seniors.

71.1% of seniors making less than 30% of AMI are spending most of their income on housing (see Figure 33). For seniors making more than 100% of AMI, 93.5% are not cost-burdened and spend less than 30% of their income on housing.

Overcrowding occurs when the number of people living in a household is greater than the home was designed to hold. There are several different standards for defining overcrowding, but this report uses the Census Bureau definition, which is more than one occupant per room (not including bathrooms or kitchens). Additionally, the Census Bureau considers units with more than 1.5 occupants per room to be severely overcrowded.

Overcrowding is often related to the cost of housing and can occur when demand in a city or region is high. In many cities, overcrowding is seen more amongst those who are renting, with multiple households sharing a unit to make it possible to stay in their communities.

In Belmont, 4.8% of households that rent are severely overcrowded (more than 1.5 occupants per room), compared to 0.5% of households that own (see Figure 34). 4.7% of renters experience moderate overcrowding (1 to 1.5 occupants per room), compared to 0.8% for those who own.
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44 Figure 33: Cost-Burdened Senior Households by Income Level Universe: Senior households.

Notes: For the purposes of this graph, senior households are those with a householder who is aged 62 or older. Cost burden is the ratio of housing costs to household income. For renters, housing cost is gross rent (contract rent plus utilities). For owners, housing cost is “select monthly owner costs”, which includes mortgage payment, utilities, association fees, insurance, and real estate taxes. HUD defines costburdened households as those whose monthly housing costs exceed 30% of monthly income, while severely cost-burdened households are those whose monthly housing costs exceed 50% of monthly income. Income groups are based on HUD calculations for Area Median Income (AMI). HUD calculates the AMI for different metropolitan areas, and the nine county Bay Area includes the following metropolitan areas: Napa Metro Area (Napa County), Oakland-Fremont Metro Area (Alameda and Contra Costa Counties), San Francisco Metro Area (Marin, San Francisco, and San Mateo Counties), San Jose-Sunnyvale-Santa Clara Metro Area (Santa Clara County), Santa Rosa Metro Area (Sonoma County), and Vallejo-Fairfield Metro Area (Solano County). The AMI levels in this chart are based on the HUD metro area where this jurisdiction is located.

Source: U.S. Department of Housing and Urban Development (HUD), Comprehensive Housing Affordability Strategy (CHAS) ACS tabulation, 2013-2017 release.

For the data table behind this figure, please refer to the Data Packet Workbook, Table SEN-03.

Figure 34: Overcrowding by Tenure and Severity
Universe: Occupied housing units.

Source: U.S. Department of Housing and Urban Development (HUD), Comprehensive Housing Affordability Strategy (CHAS) ACS tabulation, 2013-2017 release.

For the data table behind this figure, please refer to the Data Packet Workbook, Table OVER-01. 361
APPENDIX A: NEEDS ANALYSIS
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Overcrowding often disproportionately impacts low-income households. 0.9% of very lowincome households (below 50% AMI) experience severe overcrowding, while 0.6% of households above 100% experience this level of overcrowding (see Figure 35).

Figure 35: Overcrowding by Income Level and Severity
Universe: Occupied housing units.

Notes: The Census Bureau defines an overcrowded unit as one occupied by 1.01 persons or more per room (excluding bathrooms and kitchens), and units with more than 1.5 persons per room are considered severely overcrowded. Income groups are based on HUD calculations for Area Median Income (AMI). HUD calculates the AMI for different metropolitan areas, and the nine county Bay Area includes the following metropolitan areas: Napa Metro Area (Napa County), Oakland-Fremont Metro Area (Alameda and Contra Costa Counties), San Francisco Metro Area (Marin, San Francisco, and San Mateo Counties), San Jose-Sunnyvale-Santa Clara Metro Area (Santa Clara County), Santa Rosa Metro Area (Sonoma County), and Vallejo-Fairfield Metro Area (Solano County). The AMI levels in this chart are based on the HUD metro area where this jurisdiction is located.

Source: U.S. Department of Housing and Urban Development (HUD), Comprehensive Housing Affordability Strategy (CHAS) ACS tabulation, 2013-2017 release.

For the data table behind this figure, please refer to the Data Packet Workbook, Table OVER-04.

Communities of color are more likely to experience overcrowding as well as poverty, financial instability, and housing insecurity. People of color tend to experience overcrowding at higher rates than White residents.

In Belmont, the racial group with the largest rate of overcrowding is Other Race or Multiple Races (Hispanic and Non-Hispanic) (see Figure 36).
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46 Figure 36: Overcrowding by Race
Universe: Occupied housing units.

Notes: The Census Bureau defines an overcrowded unit as one occupied by 1.01 persons or more per room (excluding bathrooms and kitchens), and units with more than 1.5 persons per room are considered severely overcrowded. For this table, the Census Bureau does not disaggregate racial groups by Hispanic/Latinx ethnicity. However, data for the white racial group is also reported for white householders who are not Hispanic/Latinx. Since residents who identify as white and Hispanic/Latinx may have very different experiences within the housing market and the economy from those who identify as white and non-Hispanic/Latinx, data for multiple white sub-groups are reported here. The racial/ethnic groups reported in this table are not all mutually exclusive. Therefore, the data should not be summed as the sum exceeds the total number of occupied housing units for this jurisdiction. However, all groups labelled “Hispanic and Non-Hispanic” are mutually exclusive, and the sum of the data for these groups is equivalent to the total number of occupied housing units.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B25014.

For the data table behind this figure, please refer to the Data Packet Workbook, Table OVER-03. 363
47 6. SPECIAL HOUSING NEEDS

6.1 LARGE HOUSEHOLDS
Large households often have different housing needs than smaller households. If a city’s rental housing stock does not include larger apartments, large households that rent could end up living in overcrowded conditions.

In Belmont, for large households with five or more people, most units (65.2%) are owneroccupied (see Figure 37). In 2017, 13.8% of large households were very low-income, earning less than 50% of the area median income (AMI).

Figure 37: Household Size by Tenure
Universe: Occupied housing units.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B25009.

For the data table behind this figure, please refer to the Data Packet Workbook, Table LGFEM-01.

In addition to overcrowding, large households also often have a cost burden. In Belmont, most large households paying too much for housing are lower-income households. Although this is principally because there are very few large renter households, there are disproportionately fewer large renter households than large owner-occupied households.

The unit sizes available in a community affect the household sizes that can access that community. Large families are generally served by housing units with three or more bedrooms, of which there are 6,175 units in Belmont. Among these large units with three or more bedrooms, 10.8% are renter-occupied while 89.2% are owner occupied (see Figure 38). 364
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48 Figure 38: Housing Units by Number of Bedrooms
Universe: Housing units.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B25042.

For the data table behind this figure, please refer to the Data Packet Workbook, Table HSG-05.

RESOURCES FOR LARGE HOUSEHOLDS
Finding rental housing with more than two bedrooms is a typical problem for large families, particularly renters with lower income levels. Of the approximately 6,175 housing units in Belmont with three or more bedrooms, only 10.8% (665) are occupied by renters. Due to the limited supply of adequately-sized rental units and affordable homeownership opportunities to accommodate large family households, large families face additional difficulty in locating housing that is adequately sized and affordably priced. While Belmont has a large proportion of housing units with three or more bedrooms, the issue is with mismatch between availability and affordability. The Housing Choice Voucher is one program that can assist very low-income large renter-households in accessing adequately sized housing.

6.2 FEMALE-HEADED HOUSEHOLDS
Households headed by one person are often at a greater risk of housing insecurity. This is particularly true of female-headed households, where the female may be supporting children or other family with a single income. In Belmont, the largest proportion of households is Marriedcouple Family Households(61.8%), while Female-Headed Households make up 6.7% of households.
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Figure 39: Household Type
Universe: Households.

Notes: For data from the Census Bureau, a “family household” is a household where two or more people are related by birth, marriage, or adoption. “Non-family households” are households of one person living alone, as well as households where none of the people are related to each other.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B11001.

For the data table behind this figure, please refer to the Data Packet Workbook, Table POPEMP-23.

Female-headed households with children may face elevated housing challenges, with pervasive gender inequality resulting in lower wages for women. Moreover, the added need for childcare can make finding a home that is affordable more challenging. In Belmont, 5.3% of femaleheaded households with children fall below the Federal Poverty Line, while 2.0% of femaleheaded households without children live in poverty (see Figure 40).

Figure 40: Female-Headed Households by Poverty Status
Universe: Female households.

Notes: The Census Bureau uses a federally defined poverty threshold that remains constant throughout the country and does not correspond to Area Median Income.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B17012.

For the data table behind this figure, please refer to the Data Packet Workbook, Table LGFEM-05. 366
APPENDIX A: NEEDS ANALYSIS
50 The 2015-2019 American Community Survey showed that single parents comprised approximately 9.7% of Belmont households. Of these, the vast majority were female-headed, single-parent households (68.3% of single-parent households). Female-headed families have a higher incidence of poverty when compared to all households and are more likely renters than owners. Of the female headed households in Belmont, 57.6% were renters.

RESOURCES FOR SINGLE PARENT HOUSEHOLDS
Female-headed households often need affordable housing in areas suitable for child-rearing and with access to transit networks, schools, parks, and daily services. The City will also be looking at developing a policy for affirmative marketing to lower-income special needs groups, which may involve a preference system for below market rate (BMR) units to ensure special needs groups are given opportunities to access housing that is affordable to them.

6.3 SENIORS
Senior households often experience a combination of factors that can make accessing or keeping affordable housing a challenge. They often live on fixed incomes and are more likely to have disabilities, chronic health conditions, and reduced mobility.

Seniors who rent may be at an even greater risk for housing challenges than those who own, due to income differences between these groups. The largest proportion of senior households who rent make 0%-30% of AMI, while the largest proportion of senior households who are homeowners falls in the income group Greater than 100% of AMI (see Figure 41).

According to American Community Survey 5-year data (2015-2019), of the approximately 10,285 households in Belmont, 2,809 or 27.3% are senior households. While many earn incomes over 100% of median income, a significant percentage earns lower incomes. Approximately 1,444 senior households earn incomes less than 80% of median, or about 51%. Of the lowerincome households, 54.4% are homeowners and 45.6% are renters.

Cost burden is prevalent amongst elderly households, especially those earning the lowest incomes. For example, although extremely low-income senior households represent 21% of total senior households, they represent more than 49.5% of senior households with a cost burden. Of all senior households, 445 (15.8%) are cost-burdened, and 644 (22.9%) are severely cost-burdened.

Aside from overpayment problems faced by seniors due to their relatively fixed incomes, many seniors are faced with various disabilities. Among all disabilities, the most common are ambulatory disabilities (14.4%), independent living disabilities (10.5%), and hearing disabilities (9.4%).
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Figure 41: Senior Households by Income and Tenure
Universe: Senior households.

Notes: For the purposes of this graph, senior households are those with a householder who is aged 62 or older. Income groups are based on HUD calculations for Area Median Income (AMI). HUD calculates the AMI for different metropolitan areas, and the nine county Bay Area includes the following metropolitan areas: Napa Metro Area (Napa County), Oakland-Fremont Metro Area (Alameda and Contra Costa Counties), San Francisco Metro Area (Marin, San Francisco, and San Mateo Counties), San Jose-Sunnyvale-Santa Clara Metro Area (Santa Clara County), Santa Rosa Metro Area (Sonoma County), and Vallejo-Fairfield Metro Area (Solano County). The AMI levels in this chart are based on the HUD metro area where this jurisdiction is located.

Source: U.S. Department of Housing and Urban Development (HUD), Comprehensive Housing Affordability Strategy (CHAS) ACS tabulation, 2013-2017 release.

For the data table behind this figure, please refer to the Data Packet Workbook, Table SEN-01.

RESOURCES FOR SENIORS
Housing resources available for seniors include senior apartments and residential care facilities for the elderly (RCFE). Residential facilities such as assisted living or board and care facilities are non-medical facilities that provide a level of care that includes assistance with activities of daily living. RCFEs provide room, board, housekeeping, supervision, and personal care assistance with basic activities like personal hygiene, dressing, eating, and walking for persons 60 years and older. According to the State Department of Social Services (CDSS), Belmont has 297 beds in 11 licensed RCFEs.

In addition to funding programs that serve seniors, the County also provides information on a wide variety of services to seniors. These include, but are not limited to:
211BAYAREA.ORG
211 provides free and confidential information and referrals. Call 2-1-1 for help with food, housing, employment, health care, counseling, and more. 211 in San Mateo County can help locate food, housing, health care, senior services, childcare, legal aid, and much more. 368
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52 SAN MATEO COUNTY AGING AND ADULT SERVICES
San Mateo County Aging and Adult provides a wide range of services to keep seniors, people with disabilities, and dependent adults living safely and as independently as possible in the community.

SAN MATEO COUNTY NETWORK OF CARE
San Mateo County Network of Care is a website sponsored by San Mateo County and providing information on a wide array of services for seniors and persons with disabilities.

T.I.E.S(COUNTY OF BELMONT)
Phone Hotline 1-800-675-8437 Teamwork Insuring Elderly Support (T.I.E.S.) provides general information on all senior services. TIES features a 24-hour hotline and is designed to assist vulnerable elderly and dependent adults who need help but may be unable to get it for themselves.

HELP AT HOME
Help at Home is a mini-reference guide published by the San Mateo County Commission on Aging. This guide contains a wide variety of information designed to assist San Mateo County adults of all incomes to remain safely in their homes.

6.4 PEOPLE WITH DISABILITIES
People with disabilities face additional housing challenges. Encompassing a broad group of individuals living with a variety of physical, cognitive, and sensory impairments, many people with disabilities live on fixed incomes and need specialized care, yet often rely on family members for assistance due to the high cost of care.

When it comes to housing, people with disabilities are not only in need of affordable housing but accessibly designed housing, which offers greater mobility and opportunity for independence. Unfortunately, this need typically outweighs availability, particularly in a housing market with such high demand. People with disabilities are at a high risk for housing insecurity, homelessness, and institutionalization, particularly when they lose aging caregivers.

Figure 42 shows the rates at which different disabilities are present among residents of Belmont. Overall, 9% of people in Belmont have a disability of any kind.21 21 These disabilities are counted separately and are not mutually exclusive, as an individual may report more than one disability. These counts should not be summed. 369
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Figure 42: Disability by Type
Universe: Civilian noninstitutionalized population 18 years and over.

Notes: These disabilities are counted separately and are not mutually exclusive, as an individual may report more than one disability.

These counts should not be summed. The Census Bureau provides the following definitions for these disability types: Hearing difficulty:
deaf or has serious difficulty hearing. Vision difficulty: blind or has serious difficulty seeing even with glasses. Cognitive difficulty: has serious difficulty concentrating, remembering, or making decisions. Ambulatory difficulty: has serious difficulty walking or climbing stairs. Self-care difficulty: has difficulty dressing or bathing. Independent living difficulty: has difficulty doing errands alone such as visiting a doctor’s office or shopping.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B18102, Table B18103, Table B18104, Table B18105, Table B18106, Table B18107. For the data table behind this figure, please refer to the Data Packet Workbook, Table DISAB-01.

In Belmont and elsewhere, persons with disabilities have a wide range of different housing needs, which vary depending on the type and severity of the disability as well as personal preference and lifestyle. Physical, mental, and/or developmental disabilities may prevent a person from working, restrict one’s mobility, or make it difficult to care for oneself. “Barrierfree design” housing, accessibility modifications, proximity to services and transit, and group living opportunities represent some of the types of considerations and accommodations that are important in serving this group. Also, some residents suffer from disabilities that require living in a supportive or institutional setting.

RESOURCES FOR PERSONS WITH DISABILITIES
In addition to housing and community development programs provided by the City, San Mateo County provides a variety of services and information for older adults and people with disabilities through its Network of Care efforts. Its website contains links to service providers on the following topics.

In addition, the Center for Independence of Individuals with Disabilities (CID) is a private, nonprofit corporation located in San Mateo, California. Incorporated in 1979, CID is a consumerdriven, community-based, services and advocacy organization serving San Mateo County and beyond. By federal mandate, the majority of its Staff, Management, and Board of Directors 370
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54 consists of people with disabilities. Annually, CID provides direct and indirect services to more than 2,000 individuals with disabilities.

CID is one of 29 Independent Living Centers in the State of California and over 400 Independent Living Centers in the United States. It is affiliated with other ILCs through its membership and participation in the California Foundation of Independent Living Centers and the National Council of Independent Living. CID is affiliated with other nonprofit agencies through its membership in the California Association of Non-Profits.

CID services include Housing Accessibility Modification (HAM), which involves installing grab bars, rails, ramps, hand-held showers, etc. for low-income San Mateo County residents. It also provides Peer Counseling (individual and group) by licensed, trained persons with disabilities, and Financial Benefits Counseling (regarding applications or appeals for SSI, SSDI, or MediCal).

The Assistive Technology (AT) Program is designed to educate and train the public concerning technology that can assist people with disabilities. CID maintains an information database of community resources and have links to the California statewide AT Network in Sacramento.

State law also requires Housing Elements examine the housing needs of people with developmental disabilities. People with developmental disabilities have a disability that emerged before age 18, is expected to be lifelong, and is of sufficient severity to require a coordinated program of services and support to live successfully in the community.

Developmental disabilities include intellectual disability, autism, Down Syndrome, epilepsy, cerebral palsy, and other disabling conditions similar in their functional impact to an intellectual disability. Under California’s Developmental Disabilities Services Act and the U.S. Supreme Court’s 1999 decision in Olmstead v. L.C., people with developmental disabilities are entitled to receive community-based services that allow them to live in the least restrictive community setting. This shift to de-institutionalization has led to the closure of the most restrictive segregated settings and to the requirement that local jurisdictions in their Housing Elements assess and plan specifically for the housing needs of people with developmental disabilities who receive services from the Regional Center to live in their home community.

Many developmentally disabled persons can live and work independently within a conventional housing environment. More severely disabled individuals require a group living environment where supervision is provided. The most severely affected individuals may require an institutional environment where medical attention and physical therapy are provided. Because developmental disabilities exist before adulthood, the first issue in supportive housing for the developmentally disabled is the transition from the person’s living situation as a child to an appropriate level of independence as an adult.

The family home is the most prevalent living arrangement for Belmont’s adults with developmental disabilities, with 35% of adults living in the family home in 2021, lower than the San Mateo County average of 56%. Belmont has a higher percentage of adults living in their own apartment than San Mateo County because of the presence of a 24-unit HUD 811 apartment complex specifically for people with developmental disabilities, which accounts for many of the adults with developmental disabilities now living independently. 371
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In Belmont, of the population with a developmental disability, children under the age of 18 make up 31.1%, while adults account for 68.9%.

TABLE 13: POPULATION WITH DEVELOPMENTAL DISABILITIES BY AGE Age Group Number
Age 18+ 111
Age Under 18 50
Universe: Population with developmental disabilities.

Notes: The California Department of Developmental Services is responsible for overseeing the coordination and delivery of services to more than 330,000 Californians with developmental disabilities including cerebral palsy, intellectual disability, Down syndrome, autism, epilepsy, and related conditions. The California Department of Developmental Services provides ZIP code level counts. To get jurisdiction-level estimates, ZIP code counts were cross-walked to jurisdictions using census block population counts from Census 2010 SF1 to determine the share of a ZIP code to assign to a given jurisdiction.

Source: California Department of Developmental Services, Consumer Count by California ZIP Code and Age Group (2020).

This table is included in the Data Packet Workbook as Table DISAB-04.

Access to deeply affordable rents coordinated with on-site supportive services provided by the Golden Gate Regional Center (such as found in Belmont’s single HUD 811 apartment property) is critical to helping Belmont adults with developmental disabilities remain stably housed in high-cost San Mateo County.

TABLE 14: POPULATION WITH DEVELOPMENTAL DISABILITIES BY RESIDENCE Residence Type Number
Home of Parent /Family /Guardian 88
Independent /Supported Living 35
Community Care Facility 29
Other 5
Foster /Family Home 5
Intermediate Care Facility 5
Universe: Population with developmental disabilities.

Notes: The California Department of Developmental Services is responsible for overseeing the coordination and delivery of services to more than 330,000 Californians with developmental disabilities including cerebral palsy, intellectual disability, Down syndrome, autism, epilepsy, and related conditions. The California Department of Developmental Services provides ZIP code level counts. To get jurisdiction-level estimates, ZIP code counts were crosswalked to jurisdictions using census block population counts from Census 2010 SF1 to determine the share of a ZIP code to assign to a given jurisdiction.

Source: California Department of Developmental Services, Consumer Count by California ZIP Code and Residence Type (2020).

This table is included in the Data Packet Workbook as Table DISAB-05.

According to Housing Choices, a nonprofit organization that has supported people with developmental disabilities find and retain affordable housing in their communities for 25 years in San Mateo County, there are several statistics that have impacted the need for housing to support this population. These include the following.

Increase of Autism Diagnosis Reflected in Increase in Adults in their 20s and 30s. Growth in the Belmont adult population with developmental disabilities correlates with a significant 372
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56 annual increase in the diagnosis of autism that began in the mid-1980s and did not level out until after 2015. The cumulative impact of this trend is already seen in the growth in the San Mateo County population age 18 to 41 with developmental disabilities.

TABLE 15: GROWTH IN POPULATION OF SAN MATEO COUNTY ADULTS WITH DEVELOPMENTAL

DISABILITIES
Age Band 2015 Number 2021 Number % Change
18 to 31 1,023 1,189 16%
32 to 41 397 457 15%
41 to 52 382 335 -12%
52 to 61 385 348 -10%
62 plus 327 435 33%
Total Adults 2,514 2,764 10%
Longer Life Spans. The California Department of Developmental Services reports that the number of San Mateo County residents with developmental disabilities age 62 and older grew by 33% between September 2015 and June 2021. With longer life expectancies, more adults with developmental disabilities will outlive their parents and family members who are the single largest source of housing for adults with developmental disabilities in Belmont. Longer life spans also slow the pace of resident turnover in the County’s shrinking supply of licensed care facilities, which further reduces opportunities for people with developmental disabilities to secure a space in a licensed care facility.

Decline in Licensed Care Facilities. The California Department of Developmental Services reports that between September 2015 and June 2021, San Mateo County lost 5% of its supply of licensed care facilities for people with developmental disabilities (including Community Care Facilities, Intermediate Care Facilities, and Skilled Nursing Facilities). The greatest contributing factor to this loss of supply is the high cost of housing making it more financially beneficial for retiring owners to sell the facilities as residences rather than as a business, thereby increasing the need for affordable housing options coordinated with supportive services funded by the Golden Gate Regional Center.

Displacement. The California Department of Developmental Services has documented a 12% decline in the age group 42 to 51 and a 10% decline in the age group 52 to 61 in San Mateo County between September 2015 and June 2021. Considering gains in life expectancy, this loss can reasonably be attributed to displacement from the County because of the lack of residential living options (either licensed facilities or affordable housing) when an elderly parent caregiver passes away or becomes unable to house and care for the adult. Displacement takes a particular toll on adults with developmental disabilities who depend on familiarity with transit routes, shopping, and services, as well as support from community-based services and informal networks built up over years of living in Belmont. In February 2022, the City of Belmont adopted a Housing Preference Policy that was structured to address housing displacement. The 373
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preference policy offers priority for publicly funded affordable units to people who live or work in San Mateo County, and to people who have been displaced from a San Mateo County housing unit in the last three years.

Higher Rates of Physical Disabilities. People with developmental disabilities are more likely than the general population to have an accompanying physical disability. Twenty-seven percent (27%) of San Mateo County residents with developmental disabilities have limited mobility and 13% have a vision or hearing impairment. The need for an accessible unit coupled with the need for coordinated supportive services compounds the housing barriers faced by those with co-occurring intellectual and physical disabilities.

Ineligibility for Many Affordable Rental Units. Some adults with developmental disabilities depend on monthly income of around $1,000 from the Supplemental Security Income (SSI) program, pricing them out of even the limited number of extremely low-income affordable housing units in Belmont. Those with employment tend to work part-time in the lowest paid jobs and struggle to income-qualify for many of the affordable housing units for rent in Belmont.

Transit-Dependent. Most adults with developmental disabilities do not drive or own a car and rely on public transit to integrate into the larger community.

RESOURCES FOR PERSONS WITH DEVELOPMENTAL DISABILITIES
Services for persons with disabilities are typically provided by both public and private agencies.

State and Federal legislation regulate the accessibility and adaptability of new or rehabilitated multi-family apartment complexes to ensure accommodation for individuals with limited physical mobility. Housing options for persons with disabilities include various community care facilities. Many individuals continue to live with parents.

Housing Choices (HC) is a nonprofit that advocates for the housing needs of people with developmental disabilities. It is committed to educating local elected officials, City and County housing staff, and housing developers about the opportunity to plan for and include people with developmental and other disabilities in their local housing plans. It supports and promotes the voices of people with developmental and other disabilities and encourages them to become effective self-advocates. Along with clients, their parents, and other members of the community, HC frequently attends and testifies at City Council and other relevant meetings with the goal of creating cities and neighborhoods which are inclusive of people with developmental and other disabilities.

The single largest component of HC’s work is helping individuals with developmental and other disabilities find housing that suits their specific needs and priorities. Every year, their Housing Coordinators help more than 1,800 people with developmental and other disabilities create a housing plan and apply for affordable housing.

Each client has unique housing needs, constraints, and preferences. When a person is referred to Housing Choices, a Housing Coordinator helps to create an individual housing plan with input 374
APPENDIX A: NEEDS ANALYSIS
58 from the individual with disabilities and everyone in that person’s “Circle of Support.” Housing Coordinators help clients with their decision-making by discussing their finances, credit history, supportive service needs, household composition, and other background relevant to their housing choices. HC helps its clients identify and apply for rental properties for which they can income-qualify and that are in the right location. Depending on each person’s income and existing support network, this could involve applying for multiple waiting lists and monitoring waiting list statuses for several years.

The Golden Gate Regional Center (GGRC), noted above, provides services and support to individuals with developmental disabilities in Marin, San Francisco, and San Mateo Counties. A resident of Marin, San Francisco, or San Mateo Counties who falls into any of the following four categories is eligible for GGRC services.
 Is an individual with a developmental disability
 Is an infant or toddler (up to 36 months of age) who has a developmental delay  Is an infant or toddler (up to 36 months of age) for whom there are established risk conditions that could lead to a developmental delay
 Is an infant or toddler (up to 36 months of age) at high risk of having a development disability due to a combination of biomedical factors
Individuals eligible under the first category are served by GGRC's Lanterman Act services program; infants and toddlers eligible under the latter three categories are served by the regional center's Early Start program.

There are several housing types appropriate for people living with a development disability:
rent subsidized homes, licensed and unlicensed single-family homes, inclusionary housing, Section 8 vouchers, special programs for home purchase, HUD housing, and permanent supportive housing (PSH). The design of housing-accessibility modifications, the proximity to services and transit, and the availability of group living opportunities represent some of the types of considerations that are important in serving this need group. Incorporating “barrierfree” design in all, new multi-family housing (as required by California and Federal Fair Housing laws) is especially important to provide the widest range of choices for disabled residents.

Special consideration should also be given to the affordability of housing, as people with disabilities may be living on a fixed income.

6.5 HOMELESSNESS
Homelessness remains an urgent challenge in many communities across the State, reflecting a range of social, economic, and psychological factors. Rising housing costs result in increased risks of community members experiencing homelessness. Far too many residents who have found themselves housing insecure have ended up unhoused or homeless in recent years, either temporarily or longer term. Addressing the specific housing needs for the unhoused population remains a priority throughout the region, particularly since homelessness is disproportionately 375
APPENDIX A: NEEDS ANALYSIS
B ELMONT H OUSING E LEMENT 2023 - 2031 59
experienced by people of color, people with disabilities, those struggling with addiction, and those dealing with traumatic life circumstances.

The San Mateo County Human Services Agency (HSA), in close collaboration with community partners, conducts the bi-annual One Day Homeless Count and Survey (count). The purpose of the count is to gather and analyze information to help the community understand homelessness in the County. This is one data set, among others, which provides information for effective planning of services to assist people experiencing homelessness and people at risk of homelessness. HSA’s Center on Homelessness and the San Mateo County Continuum of Care (CoC) Steering Committee are responsible for overseeing this data collection effort, with assistance from a broad group of community partners, including non-profit social service providers, city and town governments, and people who have former or current homelessness experiences.

The One Day Homeless Count and Survey (count) was designed to meet two related sets of data needs. The first is the requirement of the United States Department of Housing and Urban Development (HUD) that communities applying for McKinney-Vento Homelessness Assistance funds (i.e., Continuum of Care funds) must conduct a point-in-time count of homeless people a minimum of every two years. These counts are required to take place in the last ten days of January. The count was last conducted in January 2019 to meet this HUD requirement. The previous HUD-mandated count was conducted in January 2017. The second set of data needs is for local homeless system planning, as the count provides information about people experiencing homelessness and trends over time.

The 2019 count determined that there were 1,512 people experiencing homelessness in San Mateo County on the night of January 30, 2019. This comprised of the following.  901 unsheltered homeless people (living on streets, in cars, in recreational vehicles (RVs), in tents/encampments), and
 611 sheltered homeless people (in emergency shelters and transitional housing programs).

This finding of 1,512 people was higher than the 2017 and 2015 counts, but lower than the 2011 and 2013 counts. The number of people living in shelters in 2019 remained similar to the number counted in 2017. The overall increase in homelessness from 2017 to 2019 was driven primarily by a significant increase in the number of people living in RVs (127% increase). There was also an increase in the number of people sleeping on the street (24% increase). However, compared to 2017, the 2019 count found a decrease in people estimated to be sleeping in cars (7% decrease) and in tents/encampments (31% decrease).

While no unsheltered families were directly observed during the 2019 count, the number of families with children experiencing unsheltered homelessness was estimated to have been 16 (in cars, tents/ encampments, and/or RVs). This number represents a 16% decrease in families from the 19 families estimated to be unsheltered in the 2017 count. 376
APPENDIX A: NEEDS ANALYSIS
60 The count found seven unsheltered individuals in the City of Belmont. This was an increase from 2017, when one homeless individual was located, but lower than in 2013, when 43 people were counted. Although demographic data are not available for each individual jurisdiction, several key findings were made.

The 2019 One Day Homeless Count and Survey counted 1,018 households comprised of 1,110 single adults and 119 family households comprised of 401 adults and children.

A person in an adult only household was most likely to be unsheltered (75.5%), over 25 years old (95.1%), male (75.6%), non-Hispanic (64.9%), Caucasian (70.5%), and not experiencing chronic homelessness (71.4%). Family households were most likely to be in transitional housing (67.6%), have more children than adults (59.1% vs. 40.9% respectively), and be headed by a female (57.1%). People heading family households were also predominantly non-Hispanic (53.6%) and Caucasian (55.9%); however, race and ethnicity showed more variation in family households than adult only households.

Furthermore, the percentage of people experiencing chronic homelessness over time increased from 19% in 2017 to 21% in 2019, but this figure was substantially lower than in 2013, when 45% were chronically homeless. In 2019, veterans represented 5% of adults, a reduction from 11% in 2017. Severe mental illness, alcohol and/or drug use, and history of domestic violence were some of the self-reported conditions of those who were counted. For more information, see https://hsa.smcgov.org/2019-one-day-homeless-count.

In San Mateo County, the most common type of household experiencing homelessness is those without children in their care. Among households experiencing homelessness that do not have children, 75.5% are unsheltered. Of homeless households with children, most are sheltered in transitional housing (see Figure 43).

People of color are more likely to experience poverty and financial instability because of federal and local housing policies that have historically excluded them from the same opportunities extended to White residents. Consequently, people of color are often disproportionately impacted by homelessness, particularly Black residents of the Bay Area.

In San Mateo County, White (Hispanic and Non-Hispanic) residents represent the largest proportion of residents experiencing homelessness and account for 66.6% of the homeless population, while making up 50.6% of the overall population (see Figure 44). 377
APPENDIX A: NEEDS ANALYSIS
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Figure 43: Homelessness by Household Type and Shelter Status, San Mateo County
Universe: Population experiencing homelessness.

Source: U.S. Department of Housing and Urban Development (HUD), Continuum of Care (CoC) Homeless Populations and Subpopulations Reports (2019).

For the data table behind this figure, please refer to the Data Packet Workbook, Table HOMELS-01.

Figure 44: Racial Group Share of General and Homeless Populations, San Mateo County
Universe: Population experiencing homelessness.

Notes: This data is based on Point-in-Time (PIT) information provided to HUD by CoCs in the application for CoC Homeless Assistance Programs. The PIT Count provides a count of sheltered and unsheltered homeless persons on a single night during the last ten days in January. Each Bay Area county is its own CoC, and so the data for this table is provided at the county-level. Per HCD’s requirements, jurisdictions will need to supplement this county-level data with local estimates of people experiencing homelessness. HUD does not disaggregate racial demographic data by Hispanic/Latinx ethnicity for people experiencing homelessness. Instead, HUD reports data on Hispanic/Latinx ethnicity for people experiencing homelessness in a separate table. Accordingly, the racial group data listed here includes both Hispanic/Latinx and non-Hispanic/Latinx individuals.

Source: U.S. Department of Housing and Urban Development (HUD), Continuum of Care (CoC) Homeless Populations and Subpopulations Reports (2019); U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B01001 (A-I).

For the data table behind this figure, please refer to the Data Packet Workbook, Table HOMELS-02. 378
APPENDIX A: NEEDS ANALYSIS
62 In San Mateo County, Latinx residents represent 38.1% of the population experiencing homelessness, while Latinx residents comprise 24.7% of the general population (see Figure 45).

Figure 45: Latinx Share of General and Homeless Populations, San Mateo County Universe: Population experiencing homelessness.

Notes: This data is based on Point-in-Time (PIT) information provided to HUD by CoCs in the application for CoC Homeless Assistance Programs. The PIT Count provides a count of sheltered and unsheltered homeless persons on a single night during the last ten days in January. Each Bay Area county is its own CoC, and so the data for this table is provided at the county-level. Per HCD’s requirements, jurisdictions will need to supplement this county-level data with local estimates of people experiencing homelessness. The data from HUD on Hispanic/Latinx ethnicity for individuals experiencing homelessness does not specify racial group identity. Accordingly, individuals in either ethnic group identity category (Hispanic/Latinx or non-Hispanic/Latinx) could be of any racial background.

For the data table behind this figure, please refer to the Data Packet Workbook, Table HOMELS-03.

Many of those experiencing homelessness are dealing with severe issues–including mental illness, substance abuse, and domestic violence–that are potentially life-threatening and require additional assistance. In San Mateo County, homeless individuals are commonly challenged by severe mental illness, with 305 reporting this condition (see Figure 46). Of those, some 62% are unsheltered, further adding to the challenge of handling the issue.

In Belmont, the student population experiencing homelessness totaled 17 during the 2019-20 school year and none in the 2016-17 school year. By comparison, San Mateo County has seen a

37.5% decrease in the population of students experiencing homelessness since the 2016-17 school year, and the Bay Area population of students experiencing homelessness decreased by

8.5% during the same period. During the 2019-20 school year, there were still approximately 13,718 students experiencing homelessness in the region, adding undue burdens on learning and thriving, with the potential for longer-term negative effects. The number of students in Belmont experiencing homelessness in 2019 represented 1.4% of the San Mateo County total and 0.1% of the Bay Area total.
379
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B ELMONT H OUSING E LEMENT 2023 - 2031 63
Figure 46: Characteristics for the Population Experiencing Homelessness, San Mateo County
Universe: Population experiencing homelessness.

Notes: This data is based on Point-in-Time (PIT) information provided to HUD by CoCs in the application for CoC Homeless Assistance Programs. The PIT Count provides a count of sheltered and unsheltered homeless persons on a single night during the last ten days in January. Each Bay Area county is its own CoC, and so the data for this table is provided at the county-level. Per HCD’s requirements, jurisdictions will need to supplement this county-level data with local estimates of people experiencing homelessness. These challenges/characteristics are counted separately and are not mutually exclusive, as an individual may report more than one challenge/characteristic. These counts should not be summed.

Source: U.S. Department of Housing and Urban Development (HUD), Continuum of Care (CoC) Homeless Populations and Subpopulations Reports (2019).

For the data table behind this figure, please refer to the Data Packet Workbook, Table HOMELS-04.

TABLE 16: STUDENTS IN LOCAL PUBLIC SCHOOLS EXPERIENCING HOMELESSNESS Academic Year Belmont San Mateo County Bay Area
2016-17 0 1,910 14,990
2017-18 15 1,337 15,142
2018-19 23 1,934 15,427
2019-20 17 1,194 13,718
Universe: Total number of unduplicated primary and short-term enrollments within the academic year (July 1 to June 30), public schools.

Notes: The California Department of Education considers students to be homeless if they are unsheltered, living in temporary shelters for people experiencing homelessness, living in hotels/motels, or temporarily doubled up and sharing the housing of other persons due to the loss of housing or economic hardship. The data used for this table was obtained at the school site level, matched to a file containing school locations, geocoded and assigned to jurisdiction, and finally summarized by geography.

Source: California Department of Education, California Longitudinal Pupil Achievement Data System (CALPADS), Cumulative Enrollment Data (Academic Years 2016-2017, 2017-2018, 2018-2019, 2019-2020).

This table is included in the Data Packet Workbook as Table HOMELS-05. 380
APPENDIX A: NEEDS ANALYSIS
64 RESOURCES FOR PERSONS EXPERIENCING HOMELESSNESS
The County of San Mateo is the primary coordinator of services for people experiencing homelessness in the County. The City of Belmont will continue to provide support for strategic initiatives to help address the challenges faced by people experiencing homelessness in the City, as well as to support the implementation of the County’s 2022-2025 Continuum of Care (COC) Strategic Plan on Homelessness.

The City continues to support the work of non-profit organizations providing housing services, including homeless prevention, supportive and emergency housing, and other services identified as priority needs through the community engagement process. The COC guides the implementation of the County's housing and service system to meet the needs of homeless individuals and families. The City of Belmont participates in COC meetings and monitors decision-making to better understand the latest trends in homeless outreach. The COC coordinates the following activities.
 System planning (identifying gaps, developing strategies to fill gaps, responding to emerging best practices, etc.).
 Setting funding priorities for Emergency Solutions Grant and COC funds.  Assessing system performance and making system redesigns as needed.  Coordinating with other planning entities such as the Community Action Agency.  Undertakes a wide range of efforts to meet the needs of homeless individuals and families.

CHRONICALLY HOMELESS
COC has created a multi-disciplinary, bilingual, Homeless Outreach Team (HOT) to conduct intensive outreach and engagement with unsheltered and chronically homeless individuals and families located throughout the County, with specialized HOT teams in the Cities of Belmont, Redwood City, South San Francisco, Half Moon Bay, Pacifica, and East Palo Alto.

FAMILIES WITH CHILDREN
To reduce the number of unsheltered families, the COC has developed a rapid re- housing program. The San Mateo County Human Services Agency has provided funding for a motel voucher program to assist families with children who are waiting to access shelter.

VETERANS
Needs include housing and assistance for the homeless, employment and education services, and improved and increased liaisons with the Veterans Benefits Administration. 381
APPENDIX A: NEEDS ANALYSIS
B ELMONT H OUSING E LEMENT 2023 - 2031 65
YOUTH
Currently, HUD COC funds are provided to the San Mateo County Mental Health Association to operate its Support and Advocacy for Young Adults in Transition Program, which provides case management and housing search/stabilization services to homeless youth. The San Mateo County Housing Authority administers the Family Unification Program vouchers.

6.6 FARMWORKERS
Farmworkers are traditionally defined as persons whose primary incomes are earned through seasonal or permanent agricultural work. Farmworkers have special housing needs because they earn lower incomes than many other workers. In many parts of Northern California, agriculture production is an important contribution to local economies, especially in Napa and Sonoma Counties.

In Belmont, there are no known farmworkers, and it does not have any farm housing or land remaining in agricultural use. Furthermore, no land within Belmont is designated for agricultural use. According to American Community Survey’s 2019 five-year data, there could be an estimated 30 farmworkers in Belmont; however, the margin of error for this figure is +/- 42, indicating this information is unreliable. Even at 30 farmworkers, this represents only 0.1% of the total population in the City. Maps from the State of California Department of Conservation Farmland Mapping and Monitoring Program show no farmland in Belmont. Due to the low number of potential agricultural workers in the City, the housing needs of migrant and/or farmworker housing need can be met through general affordable housing programs.

As there are no known farmworkers in Belmont, there were no reported students of migrant workers in the 2019-20 school year. The trend for the region for the past few years has been a decline of 2.4% in the number of migrant worker students since the 2016-17 school year. The change at the county level is a 57.1% decrease in the number of migrant worker students since the 2016-17 school year.

TABLE 17: MIGRANT WORKER STUDENT POPULATION
Academic Year Belmont San Mateo County Bay Area
2016-17 0 657 4,630
2017-18 0 418 4,607
2018-19 0 307 4,075
2019-20 0 282 3,976
Universe: Total number of unduplicated primary and short-term enrollments within the academic year (July 1 to June 30), public schools.

Notes: The data used for this table was obtained at the school site level, matched to a file containing school locations, geocoded and assigned to jurisdiction, and finally summarized by geography.

Source: California Department of Education, California Longitudinal Pupil Achievement Data System (CALPADS), Cumulative Enrollment Data (Academic Years 2016-2017, 2017-2018, 2018-2019, 2019-2020). See Table FARM-01. 382
APPENDIX A: NEEDS ANALYSIS
66 According to the U.S. Department of Agriculture Census of Farmworkers, the number of permanent farm workers in San Mateo County has decreased since 2002, totaling 978 in 2017, while the number of seasonal farm workers has also decreased, totaling 343 in 2017 (see Figure 47).

RESOURCES FOR MIGRANT AND/OR FARM WORKERS
As mentioned above, there are no known persons employed in the farming, fishing, and forestry occupations. As such, no special programs target this population in Belmont, but they can be generally assisted with Housing Choice Vouchers or other affordable housing resources.

Figure 47: Farm Operations and Farm Labor by County, San Mateo County Universe: Hired farm workers (including direct hires and agricultural service workers who are often hired through labor contractors).

Notes: Farm workers are considered seasonal if they work on a farm less than 150 days in a year, while farm workers who work on a farm more than 150 days are considered to be permanent workers for that farm.

Source: U.S. Department of Agriculture, Census of Farmworkers (2002, 2007, 2012, 2017), Table 7: Hired Farm Labor.

For the data table behind this figure, please refer to the Data Packet Workbook, Table FARM-02.

6.7 NON-ENGLISH SPEAKERS
California has long been an immigration gateway to the U.S., which means many languages are spoken throughout the Bay Area. Since learning a new language is universally challenging, it is common for residents who have immigrated to the U.S. to have limited English proficiency.

This limit can lead to additional disparities if there is a disruption in housing, such as an eviction, because residents might not be aware of their rights, or they might be wary to engage due to immigration status concerns.

In Belmont, 3.6% of residents five years and older identify as speaking English “not well” or “not at all,” which is below the percentage in San Mateo County. Throughout the region, the proportion of residents five years and older with limited English proficiency is 8% (Figure 48). 383
APPENDIX A: NEEDS ANALYSIS
B ELMONT H OUSING E LEMENT 2023 - 2031 67
Figure 48: Population with Limited English Proficiency
Universe: Population 5 years and over.

Source: U.S. Census Bureau, American Community Survey 5-Year Data (2015-2019), Table B16005.

For the data table behind this figure, please refer to the Data Packet Workbook, Table AFFH-03. 384
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Table A: Housing Element Sites Inventory, Table Starts in Cell A2 For San Mateo County jurisdictions, please format the APNs as follows: 999-999-999 Jurisdiction Name Site Address/Intersection 5 Digit ZIP Code
Assessor Parcel
Number
Consolidated
Sites
General Plan Designation
(Current)
Zoning
Designation
(Current)
Minimum
Density
Allowed
(units/acre)
Maximum
Density
Allowed
(units/acre)
Parcel Size
(Acres)
Existing
Use/Vacancy Infrastructure Publicly-Owned Site Status Identified in Last/Last Two Planning Cycle(s) Lower Income Capacity
Moderate
Income
Capacity
Above
Moderate
Income
Capacity
Total
Capacity Optional Information1 Optional Information2 Optional Information3 BELMONT 210 EL CAMINO REAL 94002 044-152-100 A Corridor Mixed Use CMU 0 45 0.50 Commercial YES - Current NO - Privately-OwnedAvailable Used in Prior Housing Element - Non-Vacant 16 6 15 37 BELMONT 230 EL CAMINO REAL 94002 044-152-110 A Corridor Mixed Use CMU 0 45 0.09 Commercial YES - Current NO - Privately-OwnedAvailable Used in Prior Housing Element - Non-Vacant 3 1 3 7 BELMONT 240 EL CAMINO REAL 94002 044-152-120 A Corridor Mixed Use CMU 0 45 0.10 Commercial YES - Current NO - Privately-OwnedAvailable Used in Prior Housing Element - Non-Vacant 3 1 4 8 BELMONT 832 BELMONT AVENUE 94002 044-173-120 B Corridor Mixed Use CMU 0 45 0.15 Vacant YES - Potential NO - Privately-OwnedAvailable Used in Two Consecutive Prior Housing Elements - Vacant 2 1 2 5 BELMONT 832 BELMONT AVENUE 94002 044-173-190 B Corridor Mixed Use CMU 0 45 0.18 Vacant YES - Potential NO - Privately-OwnedAvailable Used in Two Consecutive Prior Housing Elements - Vacant 3 1 2 6 BELMONT 832 BELMONT AVENUE 94002 044-173-210 B Corridor Mixed Use CMU 0 45 0.09 Vacant YES - Potential NO - Privately-OwnedAvailable Used in Two Consecutive Prior Housing Elements - Vacant 1 1 1 3 BELMONT 832 BELMONT AVENUE 94002 044-173-220 B Corridor Mixed Use CMU 0 45 0.10 Vacant YES - Potential NO - Privately-OwnedAvailable Used in Two Consecutive Prior Housing Elements - Vacant 2 0 2 4 BELMONT ANITA AVENUE 94002 044-173-010 B Corridor Mixed Use CMU 0 45 0.21 Vacant YES - Potential NO - Privately-OwnedAvailable Not Used in Prior Housing Element 3 1 3 7 BELMONT 510 EL CAMINO REAL 94002 044-201-180 Corridor Mixed Use CMU 0 45 0.81 Commercial YES - Current NO - Privately-OwnedAvailable Used in Prior Housing Element - Non-Vacant 26 10 25 61 BELMONT 516 EL CAMINO REAL 94002 044-201-040 Corridor Mixed Use CMU 0 45 0.85 Commercial YES - Current NO - Privately-OwnedAvailable Used in Prior Housing Element - Non-Vacant 27 10 26 63 BELMONT 530 EL CAMINO REAL 94002 044-201-080 E Corridor Mixed Use CMU 0 45 0.87 Commercial YES - Current NO - Privately-OwnedAvailable Not Used in Prior Housing Element 28 10 27 65 BELMONT 530 EL CAMINO REAL 94002 044-201-070 E Corridor Mixed Use CMU 0 45 0.41 Commercial YES - Current NO - Privately-OwnedAvailable Not Used in Prior Housing Element 13 5 13 31 BELMONT 500 EL CAMINO REAL 94002 044-201-280 F Corridor Mixed Use CMU 0 45 0.45 Hotel/motel YES - Current NO - Privately-OwnedAvailable Used in Prior Housing Element - Non-Vacant 15 5 14 34 BELMONT 564 EL CAMINO REAL 94002 044-201-270 F Corridor Mixed Use CMU 0 45 0.31 Commercial YES - Current NO - Privately-OwnedAvailable Not Used in Prior Housing Element 10 4 9 23 BELMONT 690 EL CAMINO REAL 94002 044-222-210 Corridor Mixed Use CMU 0 45 0.44 Commercial YES - Current NO - Privately-OwnedAvailable Not Used in Prior Housing Element 6 2 5 13 BELMONT 780 EL CAMINO REAL 94002 044-222-180 Corridor Mixed Use CMU 0 45 0.12 Vacant YES - Potential YES - City-Owned Available Used in Two Consecutive Prior Housing Elements - Vacant 0 3 0 3 BELMONT 640 MASONIC WAY 94002 040-312-180 Village Station Core VSC 0 0 0.97 Public facilities YES - Current NO - Privately-OwnedAvailable Not Used in Prior Housing Element 31 12 30 73 BELMONT MASONIC WAY 94002 040-313-310 J Village Station Core VSC 0 0 0.33 Parking YES - Current NO - Privately-OwnedAvailable Used in Prior Housing Element - Non-Vacant 11 4 10 25 BELMONT 600 RALSTON AVENUE 94002 040-313-270 J Village Core Mixed Use VCMU 0 0 0.24 Commercial YES - Current NO - Privately-OwnedAvailable Used in Prior Housing Element - Non-Vacant 8 3 7 18 BELMONT 698 RALSTON AVENUE 94002 040-313-140 K Village Core Mixed Use VCMU 0 0 0.39 Commercial YES - Current NO - Privately-OwnedAvailable Used in Prior Housing Element - Non-Vacant 13 5 12 30 BELMONT 951 OLD COUNTY ROAD 94002 040-313-430 K Village Core Mixed Use VCMU 0 0 0.34 Commercial YES - Current NO - Privately-OwnedAvailable Used in Prior Housing Element - Non-Vacant 11 4 10 25 BELMONT 575 RALSTON AVENUE 94002 040-334-300 Village Core Mixed Use VCMU 0 0 0.36 Commercial YES - Current NO - Privately-OwnedAvailable Not Used in Prior Housing Element 5 2 4 11 BELMONT 601 RALSTON AVENUE 94002 040-332-220 Village Core Mixed Use VCMU 0 0 0.35 Commercial YES - Current NO - Privately-OwnedAvailable Not Used in Prior Housing Element 4 2 4 10 BELMONT 1075 OLD COUNTY ROAD 94002 040-332-270 Village Core Mixed Use VCMU 0 0 0.96 Commercial YES - Current NO - Privately-OwnedAvailable Not Used in Prior Housing Element 31 11 30 72 BELMONT 1141 OLD COUNTY ROAD 94002 040-332-260 O Village Core Mixed Use VCMU 0 0 0.54 Industrial YES - Current NO - Privately-OwnedAvailable Not Used in Prior Housing Element 17 6 17 40 BELMONT 1161 OLD COUNTY ROAD 94002 040-332-110 O Village Core Mixed Use VCMU 0 0 0.28 Industrial YES - Current NO - Privately-OwnedAvailable Not Used in Prior Housing Element 9 3 9 21 BELMONT 1000 EL CAMINO REAL 94002 045-182-250 P Village Core VC 0 0 0.94 Commercial YES - Current NO - Privately-OwnedAvailable Used in Prior Housing Element - Non-Vacant 30 11 29 70 BELMONT RALSTON AVENUE AT EL CAMINO 94002 045-182-260 P Village Core VC 0 0 0.07 Public facilities YES - Current YES - City-Owned Available Used in Prior Housing Element - Non-Vacant 3 1 2 6 BELMONT 883 RALSTON AVENUE 94002 045-182-270 Village Core VC 0 0 0.61 Commercial YES - Current NO - Privately-OwnedAvailable Used in Prior Housing Element - Non-Vacant 20 7 19 46 BELMONT 915 RALSTON AVENUE 94002 045-182-040 R Village Core VC 0 0 0.13 Commercial YES - Current NO - Privately-OwnedAvailable Used in Prior Housing Element - Non-Vacant 4 2 4 10 BELMONT 925 RALSTON AVENUE 94002 045-182-030 R Village Core VC 0 0 0.13 Parking YES - Current NO - Privately-OwnedAvailable Used in Prior Housing Element - Non-Vacant 4 2 4 10 BELMONT 940 EMMETT STREET 94002 045-182-200 R Village Core VC 0 0 0.17 Parking YES - Current NO - Privately-OwnedAvailable Used in Prior Housing Element - Non-Vacant 5 2 5 12 BELMONT 940 EMMETT STREET 94002 045-182-210 R Village Core VC 0 0 0.31 Commercial YES - Current NO - Privately-OwnedAvailable Used in Prior Housing Element - Non-Vacant 10 3 10 23 BELMONT 945 RALSTON AVENUE 94002 045-182-020 R Village Core VC 0 0 0.15 Commercial YES - Current NO - Privately-OwnedAvailable Used in Prior Housing Element - Non-Vacant 5 2 5 12 BELMONT 1085 SIXTH AVENUE 94002 045-182-220 S Village Core VC 0 0 0.17 Parking YES - Current YES - City-Owned Available Used in Prior Housing Element - Non-Vacant 6 2 5 13 BELMONT 995 RALSTON AVENUE 94002 045-182-010 S Village Core VC 0 0 0.36 Commercial YES - Current NO - Privately-OwnedAvailable Used in Prior Housing Element - Non-Vacant 12 4 11 27 BELMONT 1520 EL CAMINO REAL 94002 045-253-300 T Village Core Mixed Use VCMU 0 0 0.20 Commercial YES - Current NO - Privately-OwnedAvailable Not Used in Prior Housing Element 7 2 6 15 BELMONT 1538 EL CAMINO REAL 94002 045-253-290 T Corridor Mixed Use CMU 0 45 0.47 Commercial YES - Current NO - Privately-OwnedAvailable Not Used in Prior Housing Element 15 6 14 35 BELMONT 1501 EL CAMINO REAL 94002 045-252-080 Corridor Mixed Use CMU 0 45 1.02 Commercial YES - Current NO - Privately-OwnedAvailable Not Used in Prior Housing Element 33 12 31 76 BELMONT 1601 EL CAMINO REAL 94002 045-252-100 Corridor Mixed Use CMU 0 45 1.68 Commercial YES - Current NO - Privately-OwnedAvailable Not Used in Prior Housing Element 54 20 52 126 BELMONT 1477 EL CAMINO REAL 94002 045-247-030 Corridor Mixed Use CMU 0 45 0.15 Vacant YES - Current NO - Privately-OwnedPending Project Not Used in Prior Housing Element 0 0 5 5 BELMONT 580 MASONIC WAY 94002 040-315-010 Village Station Core VSC 0 0 1.24 Commercial YES - Current NO - Privately-OwnedPending Project Used in Prior Housing Element - Non-Vacant 11 11 117 139 BELMONT 678 RALSTON 94002 040-313-280 Village Core Mixed Use VCMU 0 0 0.36 Commercial YES - Current NO - Privately-OwnedPending Project Used in Prior Housing Element - Non-Vacant 64 0 1 65 BELMONT 0
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Table C: Land Use, Table Starts in A2
Zoning Designation
From Table A, Column G
and Table B, Columns L and N (e.g.,
"R-1")
General Land Uses Allowed (e.g.,
"Low-density residential")
CMU High-density mixed-use
VCMU High-density residential and mixed-use
VC High-intensity mixed-use
VSC High-density residential and low mixed-use
387
B ELMONT H OUSING E LEMENT 2023 - 2031
APPENDIX C: AFFH
388
389
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 1 AFFH Attachment C.1.

City of Belmont Fair Housing Assessment
What is AFFH?
The State of California’s 2018 Assembly Bill (AB 686) requires that all public agencies in the state affirmatively further fair housing (AFFH) beginning January 1, 2019. Public agencies receiving funding from the U.S. Department of Housing and Urban Development (HUD) are also required to demonstrate their commitment to AFFH. The federal obligation stems from the fair housing component of the federal Civil Rights Act mandating federal fund recipients to take “meaningful actions” to address segregation and related barriers to fair housing choice.

AB 686 requires all public agencies to “administer programs and activities relating to housing and community development in a manner that affirmatively furthers fair housing and take no action inconsistent with this obligation.”1 AB 686 also makes changes to Housing Element Law to incorporate requirements to AFFH as part of the housing element and general plan to include an analysis of fair housing outreach and capacity, integration and segregation, access to opportunity, disparate housing needs, and current fair housing practices.

Affirmatively Furthering Fair Housing
“Affirmatively furthering fair housing” means taking meaningful actions, in addition to combating discrimination, that overcome patterns of segregation and foster inclusive communities free from barriers that restrict access to opportunity based on protected characteristics. Taken together, these actions should address significant disparities in housing needs and in access to opportunity, replacing segregated living patterns with truly integrated and balanced living patterns, transforming racially and ethnically concentrated areas of poverty into areas of opportunity, and fostering and maintaining compliance with civil rights and fair housing laws. The duty to affirmatively further fair housing extends to all of a public agency’s activities and programs relating to housing and community development. (Gov Code, § 8899.50, subd. (a)(1).)” Source: California Department of Housing and Community Development Guidance, 2021, page 14. 1 California Department of Housing and Community Development Guidance, 2021, page 9. 390
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 2 History of segregation in the region. The
United States’ oldest cities have a history of
mandating segregated living patterns—and
Northern California cities are no exception. ABAG, in
its recent Fair Housing Equity Assessment,
attributes segregation in the Bay Area to historically
discriminatory practices—highlighting redlining and
discriminatory mortgage approvals—as well as
“structural inequities” in society, and “selfsegregation” (i.e., preferences to live near similar people).

Researcher Richard Rothstein’s 2017 book The Color
of Law: A Forgotten History of How Our Government
Segregated America chronicles how the public sector
contributed to the segregation that exists today.

Rothstein highlights several significant
developments in the Bay Area region that played a
large role in where the region’s non-White residents
settled.

Pre-civil rights San Mateo County faced resistance to racial integration, yet it was reportedly less direct than in some Northern California communities, taking the form of “blockbusting” and “steering” or intervention by public officials. These local discriminatory practices were exacerbated by actions of the Federal Housing Administration which excluded low-income neighborhoods, where the majority of people of color lived, from its mortgage loan program.

According to the San Mateo County Historical Association. San Mateo County’s early African Americans worked in a variety of industries, from logging, to agriculture, to restaurants and entertainment. Expansion of jobs, particularly related to shipbuilding during and after World War II attracted many new residents into the Peninsula, including the first sizable migration of African Americans. Enforcement of racial covenants after the war forced the migration of the county’s African Americans into neighborhoods where they were allowed to occupy housing—housing segregated into less desirable areas, next to highways, and concentrated in public housing and urban renewal developments.

The segregating effect of blockbusting activities is well-documented in East Palo Alto. In 1954, after a White family in East Palo Alto sold their home to an African American family, the then-president of the California Real Estate Association set up an office in East Palo Alto to scare White families into selling their homes (“for fear of declining property values”) to agents and speculators. These agents then sold these homes at over-inflated prices to African American buyers, some of whom had trouble making their payments. Within six years, East Palo Alto—initially established with “whites only” neighborhoods—became 82% African American. The FHA prevented re-integration by refusing to insure mortgages held by White buyers residing in East Palo Alto.

This history of segregation in
the region is important not
only to understand how
residential settlement
patterns came about—but,
more importantly, to explain
differences in housing
opportunity among residents
today. In sum, not all
residents had the ability to
build housing wealth or
achieve economic
opportunity. This historically
unequal playing field in part
determines why residents
have different housing needs
today.
391
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 3 Throughout the county, neighborhood associations and city leaders attempted to thwart the integration of communities. Although some neighborhood residents supported integration, most did not, and it was not unusual for neighborhood associations to require the acceptance of all new buyers. Builders with intentions to develop for all types of buyers (regardless of race) found that their development sites were rezoned by planning councils, required very large minimum lot sizes, and\or were denied public infrastructure to support their developments or charged prohibitively high amounts for infrastructure.

In addition to historical discriminatory practices that embedded segregation into living patterns throughout the Bay Area, it’s also necessary to recognize the historical impacts of colonization and genocide on Indigenous populations and how the effects of those atrocities are still being felt today. The original inhabitants of present-day San Mateo County are the Ramaytush Ohlone, who have “…lived on the San Francisco Peninsula for thousands of years and continue to live here as respectful stewards of the land.”2 However, “due to the devastating policies and practices of a succession of explorers, missionaries, settlers, and various levels of government over the centuries since European expansion, the Ramaytush Ohlone lost the vast majority of their population as well as their land.”3 The lasting influence of these policies and practices has contributed directly to the disparate housing and economic outcomes collectively experienced by Native populations today.4
The timeline of major federal Acts and court decisions related to fair housing choice and zoning and land use appears on the following page.

As shown in the timeline, exclusive zoning practices were common in the early 1900s.

Courts struck down only the most discriminatory and allowed those that would be considered today to have a “disparate impact” on classes protected by the Fair Housing Act.

For example, the 1926 case Village of Euclid versus Amber Realty Co. (272 U.S. 365) supported the segregation of residential, business, and industrial uses, justifying separation by characterizing apartment buildings as “mere parasite(s)” with the potential to “utterly destroy” the character and desirability of neighborhoods. At that time, multi-family apartments were the only housing options for people of color, including immigrants.

The Federal Fair Housing Act was not enacted until nearly 60 years after the first racial zoning ordinances appeared in U.S. cities. This coincided with a shift away from federal control over low-income housing toward locally-tailored approaches (block grants) and market-oriented choice (Section 8 subsidies)—the latter of which is only effective when adequate affordable rental units are available.
2 https://www.smcoe.org/for-communities/indigenous-people-of-san-mateo-county.html 3 https://www.smcoe.org/for-communities/indigenous-people-of-san-mateo-county.html 4 https://www.americanprogress.org/article/systemic-inequality-displacement-exclusion-segregation/ 392
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 4 Major Public and Legal Actions that Influence Fair Access to Housing 393
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 5 Report Content and Organization
This Fair Housing Assessment follows the April 2021 State of California State Guidance for AFFH. The study was conducted as part of the 21 Elements process, which facilitates the completion of Housing Elements for all San Mateo County jurisdictions. The figures that are referenced throughout this section are contained in Attachment C.4 Belmont AFFH Segregation Report and Attachment C.6 Maps and Data Packet. This supplemental attachment includes data tables comparing the jurisdiction to the county and broader region, in addition to HCD maps created to support the AFFH.

Section I. Fair Housing Enforcement and Outreach Capacity reviews lawsuits/enforcement actions/complaints against the jurisdiction; compliance with state fair housing laws and regulations; and jurisdictional capacity to conduct fair housing outreach and education.

Section II. Integration and Segregation identifies areas of concentrated segregation, degrees of segregation, and the groups that experience the highest levels of segregation.

Section III. Access to Opportunity examines differences in access to education, transportation, economic development, and healthy environments.

Section IV. Disproportionate Housing Needs identifies which groups have disproportionate housing needs including displacement risk.

Section V. AFFH Sites Inventory Analysis. AB 686 required analysis of sites identified to meet RHNA obligations for their ability to affirmatively further fair housing.

Section VI. Contributing Factors and Fair Housing Action Plan. Goals and Actions designed to address fair housing issues and contributing factors.

AFFH Attachments:
 C.2. AFFH Community Engagement - Resident survey results—findings from a survey of Belmont residents on their experience finding and remaining in housing, with comparisons to the experience of county residents overall.  C.3. Disparate Access to Education Opportunities—findings from a countywide analysis of access to education and educational outcomes by protected class.  C.4. Belmont AFFH Segregation Report—Prepared by UC Merced Urban Policy Lab and ABAG/MTC Staff, describes racial and income segregation in Bay Area jurisdictions.  C.5. State Fair Housing Laws and Regulations—a summary of key State laws and regulations related to mitigating housing discrimination and expanding housing choice.
394
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 6  C.6. Belmont Maps and Data Packet—This supplemental attachment includes data tables comparing the jurisdiction to the county and broader region, in addition to HCD maps created to support the AFFH.

Primary Findings
 Nine fair housing inquiries and two fair housing complaints were made by Belmont residents between 2017 and 2021. A complaint filed in 2017 concerned refusal to rent based on national origin; it was settled through a conciliation agreement. A 2021 complaint based on disability for failure to provide reasonable accommodations was withdrawn by the complainant.
 Fifty-four (54%) percent of Belmont’s population is non-Hispanic White; 28% is Asian; 12% is Hispanic/Latinx; and 4% is other races or mixed race. Belmont has proportionately fewer residents of color than in the county and the Bay area overall, although the city’s Asian population is on par with the proportion in the county and Bay area. Belmont has grown more racially and ethnically diverse since 2000 and 2010, largely due to growth in Asian residents (mostly occurring between 2010 and 2020) and a slight increase in Hispanic/Latinx residents (mostly between 2000 and 2010).
 Racial and ethnic minority populations in Belmont—with the exception of Asians— are more likely to be living in poverty and be housing cost burdened compared to the non-Hispanic White population. They are also slightly more likely to be denied a mortgage loan. On the positive side, residents living in Belmont—regardless of race and ethnicity—have strong access to highly resourced neighborhoods.  Although Asian residents are less likely than other residents to experience cost burden, they have relatively high rates of overcrowding, suggesting that some are doubling up to afford to live in Belmont.
o One-third of non-Hispanic White households are cost burdened, with 15% severely cost burdened. Only 2.8% live in overcrowded conditions. o One-quarter of Asian households are cost burdened with only 9% severely burdened. Yet 7.8% live in overcrowded conditions.
o Hispanic/Latinx households have much higher rates of cost burden—48% are burdened and 25% severely burdened—and one in ten lives in an overcrowded household.
o Nearly all of Belmont’s households earning 30% of AMI and less are burdened, with the vast majority severely burdened (Figure IV-10, Attachment C.6). The level of burden diminishes greatly once households earn 80% of AMI and more.  According to TCAC’s educational opportunity map, all census tracts in Belmont have schools with the most positive educational outcomes. Belmont offers a strong 395
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 7 educational environment citywide. Students with disabilities in the Belmont-Redwood Shores district do comparatively well.
 Educational outcomes vary for some racial and ethnic groups, and the school district could improve proficiency gaps and differences in suspension rates.

Specifically,
o 82% of students in Belmont’s district meet or exceed English language arts and literacy standards; 79% exceed math standards; both are higher than the county overall. These outcomes are much lower for some students of color: 44% of Black or African American students and 64% of Hispanic students meet or exceed state English language arts standards, and 37% of Black or African American students and 52% of Hispanic students meet or exceed state math standards. o Suspensions are disproportionately high for Hispanic students. Hispanic students make up 34% of the high school district student body yet account for 66% of suspensions.
 Belmont’s largest challenge lies in housing affordability. In two census tracts, between 40% and 60% of renter households face housing burden. Yet compared to surrounding cities, Belmont offers better rental affordability, according to the HCD Location Affordability Index (Figure IV-29, Attachment C.6). Just 18% of Belmont’s owner-occupied units are priced below $1 million, compared to 44% for the county and 65% for the Bay area overall.
 Belmont has not kept up with demand for new housing. The number of homes in Belmont increased by .6% from 2010 to 2020, below the growth rate for San Mateo County and the region’s housing stock. Between 2010 and 2020, Belmont built more single family than multifamily homes, and the city’s share of housing stock comprised of single family detached homes is above that of other jurisdictions in the region. 5

 Nine percent (9%) of Belmont’s residents have a disability, which is on par with the county and the Bay area overall.
 Belmont does not currently have a pattern of segregation or clustering based on race unlike nearby cities. The Racial Dot Map (Figure 1, Attachment C.4) provides a visual demonstration of the spatial distribution of residents based on race in Belmont while Figure 5 (Attachment C.4) includes the surrounding area for context.  Geospatially, lower-income residents are distributed throughout the City, without strong patterns of clustering. The Income Dot Map (Figure 8, Attachment C.4) shows that Belmont has a distribution of all income groups with a slight concentration of above-moderate income residents in the northwest portion of the City.
5 Housing Needs Data Report completed by ABAG/MTC staff and Baird + Driskell Planning. 396
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 8 SECTION I. Fair Housing Enforcement and
Outreach Capacity
This section discusses fair housing legal cases and inquiries, fair housing protections and enforcement, and outreach capacity.

Fair Housing Legal Cases and Inquiries. California fair housing law extends beyond the protections in the Federal Fair Housing Act (FHA). In addition to the FHA protected classes—race, color, ancestry/national origin, religion, disability, sex, and familial status—California law offers protections for age, sexual orientation, gender identity or expression, genetic information, marital status, military or veteran status, and source of income (including federal housing assistance vouchers).

The California Department of Fair Employment in Housing (DFEH) was established in 1980 and is now the largest civil rights agency in the United States. According to their website, the DFEH’s mission is “to protect the people of California from unlawful discrimination in employment, housing and public accommodations (businesses) and from hate violence and human trafficking in accordance with the Fair Employment and Housing Act (FEHA), Unruh Civil Rights Act, Disabled Persons Act, and Ralph Civil Rights Act”.6 DFEH receives, evaluates, and investigates fair housing complaints. DFEH plays a particularly significant role in investigating fair housing complaints against protected classes that are not included in federal legislation and therefore not investigated by HUD.

DFEH’s website provides detailed instructions for filing a complaint, the complaint process, appealing a decision, and other frequently asked questions.7 Fair housing complaints can also be submitted to HUD for investigation.

Additionally, San Mateo County has a number of local enforcement organizations including Project Sentinel, the Legal Aid Society of San Mateo County, and Community Legal Services of East Palo Alto. These organizations receive funding from the County and participating jurisdictions to support fair housing enforcement and outreach and education in the County.

From 2017 to 2021, 57 fair housing complaints in San Mateo County were filed with the U.S.

Department of Housing and Urban Development (HUD). Of these, two (3.5%) of complaints -- were in Belmont. Countywide, most complaints cited disability status as the bias (56%), followed by race (19%), and familial status (14%). In Belmont, the complaints alleged discrimination in the terms and conditions for renting and discriminatory refusal to rent. 6 https://www.dfeh.ca.gov/aboutdfeh/ 7 https://www.dfeh.ca.gov/complaintprocess/ 397
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 9 Countywide, no cause determination was found in 27 complaints followed by successful conciliation or settlement with 22 complaints. In Belmont, one of the complaints was withdrawn by the complainant and the other was successfully settled. Fair housing inquiries in 2020 were primarily submitted from the City of San Mateo, Redwood City, Daly City, and Menlo Park.

Fair housing complaints filed with HUD by San Mateo County residents have been on a declining trend since 2018, when 18 complaints were filed. In 2019, complaints dropped to 5, increased to 11 in 2020, and had reached 6 by mid-2021.

Nationally, the National Fair Housing Alliance (NFHA) reported a “negligible” decrease in the number of complaints filed between 2019 and 2020. The primary bases for complaints nationally were nearly identical to San Mateo County’s: disability (55%) and race (17%).

Familial status represented 8% of complaints nationally, whereas this basis comprised 14% of cases in the county.

NFHA identifies three significant trends in 2020 that are relevant for San Mateo County:
 First, fair lending cases referred to the Department of Justice from federal banking regulators have been declining, indicating that state and local government entities may want to play a larger role in examining fair lending barriers to homeownership.  Second, NFHA identified a significant increase in the number of complaints of harassment—1,071 complaints in 2020 compared to 761 in 2019.

Finally, NFHA found that 73% of all fair housing complaints in 2020 were processed by private fair housing organizations, rather than state, local, and federal government agencies—reinforcing the need for local, active fair housing organizations and increased funding for such organizations.8Although discrimination complaints in San Mateo County have progressively declined, findings from the 21 Elements Resident Survey suggest that residents still experience housing discrimination but do not report it. For the county overall, 19% of respondents felt they were discriminated against when looking for housing—this is highest among African American residents (62%), single parent households (44%), and precariously housed residents (39%). Households with incomes above $100,000 are least likely to experience housing discrimination—for example, only 11% of households in this income group reported housing discrimination. Rates of discrimination for the county are lower than respondents living in Belmont where 21% thought they had experienced discrimination (this is elaborated upon below). 8 https://nationalfairhousing.org/2021/07/29/annual-fair-housing-report-shows-increase-in-housing-harassment/ 398
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 10 Nearly half of residents in San Mateo County (45%) felt they were discriminated against in the last 2 to 5 years, 28% within the past year, 20% over 5 years ago, and 7% did not remember. Almost half (42%) did nothing about the incident because they were not sure what to do, 30% moved or found somewhere else to live, and 20% did nothing out of fear that they would be evicted or harassed. These results are similar to that reported by Belmont residents (described below).

Local Fair Housing Issues. As discussed above, some Belmont residents do feel they were discriminated against. Actions taken after the discrimination include: doing nothing for fear of harassment or eviction (50%) or did not report the event because they were unsure what to do (38%). For Belmont, it is important to take note of the large volume of respondents who did not report the incidence due to lack of information on reporting discrimination. These results suggest that there is a lack of fair housing information being 399
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 11 provided to city residents on housing rights and how/where to file a housing discrimination complaint.

Residents have also been denied housing while seriously looking for rentals or homes.

Overall, 62% of respondents living in Belmont had seriously looked for housing to rent or buy in the past five years. Of those who had looked for housing to rent or buy, 52% were denied housing. The top reasons for denial are listed below distinguished by prospective renters and homebuyers.

For Belmont respondents looking for rental housing, top reasons for denial include:
 33% reported that the landlord did not return their calls or emails asking about the unit;
 27% had been told by a landlord that the unit was available but when they showed up in person the unit was no longer available; and
 27% were denied because another renter/applicant was willing to pay more in rent.

Reasons for denial among those seeking to buy a home include:
 35% responded “none of the above;”
 21% had a real estate agent that told them they would need to show that they were prequalified with a bank; and
 15% were only shown homes in neighborhoods where most people were of the same race/ethnicity.

For both renters and homebuyers, denial reasons include:
 38% were denied housing because their income was too low; and  27% reported that they haven’t established credit history or have no credit history.

When considering patterns of housing discrimination in the city, it is particularly important that 15% of Belmont respondents were only shown homes in neighborhoods where most people were of the same race/ethnicity. This practice is called steering—a form of housing discrimination—where housing providers influence a renter or buyer’s choice of community based on protected characteristics under the Fair Housing Act and state fair housing law. Steering practices are illegal and violate both federal and state law. City officials must take note of these findings as steering presents legal challenges for the city— especially if Belmont is found to be incompliant with federal and state fair housing law.

Steering practices in housing activities also hinders the city’s fair housing progress and ability to provide city residents equal housing opportunity and housing choice. 400
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 12 Though less severe than steering practices, an additional fair housing obstacle for Belmont is local opposition to the city’s plan to create more housing. This is a fair housing issue as opposition can hinder Belmont’s ability to provide equal opportunity to access housing among protected classes. For the upcoming planning period (2023-2031), the city intends to surpass its RHNA allocation of 1,785 units by building 2,000 units at different affordability levels.

During the community outreach process for the Housing Element, residents in the Sterling Downs, Homeview, and El Camino neighborhoods expressed concern about the concentration of the housing development opportunity sites in their neighborhoods due to its potential impact on neighborhood character and traffic congestion. City officials specifically allocated projects in this area because of its designation as a local “Priority Development Area” with more transportation and public transit options for residents.9 In response to these concerns, staff worked with the residents of the community on revisions to the housing development opportunity sites and ultimately received their support for the adopted January 2023 Housing Element.

Importantly, local opposition is not unique to Belmont—opposition to housing elements present complications for jurisdictions throughout San Mateo County and Contra Costa County (specifically Lafayette). Overall Belmont Residents understand and support the need for new housing, including affordable housing, but support proposing housing development in all geographical areas of the City.

Local Enforcement and Capacity. Because Belmont is a relatively small jurisdiction with limited staff and funding resources, it relies on the assistance of outside providers to assist with fair housing enforcement, including Project Sentinel. When the City receives a complaint regarding a fair housing concern, it will reach out to Project Sentinel, a regional fair housing service provider for resolution. The City also maintains information on its website directing people who believe they have been discriminated against to Project Sentinel (https://www.housing.org/).

Compliance with Federal and State Fair Housing Laws. Belmont is compliant with the federal and state fair housing laws that stimulate housing development, advance housing choice, and further fair housing goals. There is no pending litigation against the City for fair housing violations.

Federal law. Belmont is in compliance with the Fair Housing Act (FHA). The city continuously ensures fair and equal housing opportunities for protected classes. Belmont also protects characteristics not covered by the FHA including marital status and ancestry.

In 2014, Belmont furthered its fair housing efforts by adopting Zoning Ordinance Section 9 California News staff, ‘New Housing Proposal Faces Backlash from East Belmont residents,’ California News, Sep. 24, 2022, https://darik.news/california/new-housing-proposal-faces-backlash-from-east-belmont-residents-scott-scoopnews/734006.html. 401
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 13 27 to create simple procedures for persons with disabilities seeking equal access to housing under the Fair Housing Act.

Belmont is also compliant with the Americans with Disabilities Act (ADA). In accordance with Title II, the city designated an ADA Coordinator to oversee and coordinate city efforts to remain compliant with the ADA. The city also adopted a grievance procedure to provide prompt and equitable resolutions of non-compliance complaints.

State law. The City of Belmont is in compliance with the following state laws and has not been found of violating such laws.
 Housing Accountability Act (Gov. Code Section 65589.5), requiring the adoption of a Housing Element and requiring compliance with RHNA allocations;  Not Net Loss Law (Gov. Code Section 65863, requiring that adequate sites be maintained to accommodate unmet RHNA allocations for all income levels;  Limits on Growth Controls Law (Gov. Code Section 65589.5), prohibiting local agencies from denying housing development projects for very low-, low-, and moderateincome households or emergency shelters. The law provides the following exceptions:
1) The city has a Housing Element approved by the state; 2) The city has met or exceeded its RHNA allocation;
3) The development would have an adverse impact on health or safety; 4) The development is not compliant with state law; and 5) The development is inconsistent with the jurisdiction’s zoning ordinance or General Plan.
 Assembly Bill 1866, requiring cities to allow second units in all single-family residential zones and single-family dwelling units located in other residential zoning districts;  Fair Employment and Housing Act, prohibiting discrimination in employment on the basis of numerous characteristics and discrimination in all housing activities (e.g., renting, leasing, terms and conditions) on the basis of disability status.

Housing Goals and Actions. Belmont’s 2015-2023 Housing Element established goals and action items for housing development, assistance, and fair housing in the city.

Many goal and action items proposed in the planning document have proven effective in addressing the unique needs of seniors, large families, disabled persons, single parents, and persons experiencing homelessness. Goals, policies, and actions are described indepth below.  Expand and protect housing opportunities for all economic segments and special needs groups in the community. Belmont has worked towards fulfilling this goal by:
402
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 14 o Using public financial resources to support the provision and production of housing for lower-income households and persons and families with special needs;
o Providing rental and homeownership assistance;
o Supporting the conservation of government subsidized and affordable housing; and
o Providing supportive services for special needs groups.  Establish emergency shelters. Belmont created the S-2 Emergency Shelter Combining District to allow emergency shelters by right in specific zoning districts. The city completed all proposed actions for this goal in December 2015.  Encourage housing developers to promote housing types for special needs populations. Actions the city has undertaken to achieve this are both ongoing and annual including working with special needs housing service providers to develop incentives for extremely low-income households and reaching out to supportive housing developers.
 Ensure fair and equal housing opportunity for all protected populations under the Fair Housing Act (FHA)—actions to support this goal are ongoing and include supporting fair housing services and ensuring residents are aware of their rights and responsibilities.
 Provide increased services and housing for disabled persons—Belmont completed its action items in 2014 by implementing a Reasonable Accommodation Ordinance and provided increased accessibility modifications.

Program and Service Review. The City of Belmont provides its residents various resources and programs related to affordable housing and fair housing. Programs and services currently provided by Belmont are listed below.  Below Market Rate (BMR) Housing program—Belmont requires the construction of housing units that are affordable housing to low- and moderate-income households.

Applications are considered on a “first come first serve” basis and BMR owners must occupy the home as their primary residence rather than renting the home.  Emergency Shelter Program—the city meets with representatives from Shelter Network to determine opportunities for program support.  Homesharing Services—Belmont partners with non-profits to facilitate homesharing to reduce housing costs, promote independence, and increase resident security. The city provides these services through the Home Investment Project for Housing (HIP), which receives annual financial assistance from the Belmont  First-time Homeowners Workshops—in collaboration with the Housing Endowment and Regional Trust (HEART) organization, Belmont launched workshops for first-time homeowners in 2019.
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ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 15  Special Needs and Extremely Low-income Housing—Belmont facilitates the creation of housing units for persons with developmental disabilities, homeless persons, and extremely low-income households. The city achieves this by providing financing for affordable housing developments that provide units for special needs populations and through leasing city-owned properties for group homes for special needs populations.
 Fair Housing Programs—the city provides annual financial support to the Peninsula Conflict-Resolution Center (PCRC) to establish city programs targeting conflict resolution, management, and resolution services for tenant-landlord disputes.  Fair Housing Workshops—Belmont offers residents the opportunity to attend city workshops on fair housing. These workshops provide information on fair housing requirements, rights, and how fair housing supports and protects people of color, low-income families, renters, seniors, and persons with disabilities.

Belmont works with the following organizations to provide housing assistance to city residents:
 HIP Housing
 Housing Endowment and Regional Trust (HEART), providing homebuyer assistance  San Mateo County Housing Search platform
 Renew Financial, providing residents energy efficient financing  Shelter Network
 The Center for Independence of the Disabled (CID)
 Let’s Talk Housing
 Kainos
 San Mateo County Homeless Outreach Team
 Second Unit Resources Center
Local Housing Policies. As described above, Belmont has made significant progress in implementing housing policies that promote housing production, funding for housing affordability, fair housing, and neighborhood stabilization.

For special needs populations—specifically disabled persons—the city adopted a Reasonable Accommodation Ordinance to allow for deviations from zoning regulations.

The city also streamlines the processing of applications for Accessory Dwelling Units (ADUs). Additional housing tools are included below.
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ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 16 Housing Tools Leveraged in Belmont
Form based codes. Zoning that focuses
on how a structure conforms to
surrounding structures. Allows more
flexibility in structure type and use.

Mixed use zoning. Zoning that allows
commercial, retail, community and
residential uses to occupy the same site.

Can facilitate affordable housing by
leveraging uses and encouraging onsite
services.

Inclusionary housing. Requires that
residential developments of 25 units or
more provide 15% of units at affordable
rents to low-income households.

In-lieu fees for inclusionary housing.

Allows developers to pay a fee in-lieu of
constructing affordable units required
under the inclusionary housing
ordinance.

Density bonuses. Allows residential
development with 5 or more dwelling
units providing low, very low, senior, or
moderate-income housing additional
density. Conforms to State Density Bonus
law.

Commercial linkage fees. An impact
fee for new commercial and residential
developments that typically levies a per
square foot fee that goes toward funding
to develop or preserve affordable
housing.

Results from the 2015-2023 Housing Element. Since the previous planning period, Belmont has achieved and fulfilled numerous goals and policy actions outlined in the city’s 2015-2023 Housing Element. This section analyzes Belmont’s progress in affordable housing development, new programs and ordinances implemented, and fair housing policies adopted. It also provides which actions included in the Housing Element were not achieved and the challenges that remain.

For the 2015-2023 cycle, Belmont surpassed its Regional Housing Needs Allocation (RHNA) obligations. This was largely due to the city’s issuance of building permits. Though all affordability levels have not been met, since 2015, the city permitted 715 housing units.

This is a significant achievement for the city—in eight years, Belmont had only built 31 units. Of these units, 510 are above market rate,75 are moderate, 84 are low-income units, 35 are very low-income units, and 11 were extremely low-income units. Since 2022, development projects that would add 499 units are currently in the review process or have been approved.

As proposed in the Housing Element, the city adopted an inclusionary housing ordinance in January 2017 and an inclusionary rental ordinance in 2018. Examples of projects the City 405
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 17 approved during the prior housing element cycle and that completed construction in 2024 include:
 1325 Old County Road—250 unit project with 38 low-income units (largely the result of the city’s recently adopted inclusionary zoning requirement);  815 Old Country Road—a 177 unit development with 27 low-income inclusionary housing units.

In addition, Belmont committed funding for the following 100% affordable housing projects:
 1300 El Camino built by Mid Pen Housing (66 affordable units);  Hill Street and El Camino across from the city’s train station (37 affordable units);  803 Belmont Avenue (125 units).

Belmont also changed its zoning terms from dwelling units per acre to floor area ratio (FAR)—this modification has increased project densities and created more affordable units.

To increase Accessory Dwelling Unit (ADU) production, the City adopted an ADU ordinance and removed its mandatory parking replacement policy. Since taking these actions, the city has added 16 new ADUs per year on average. For housing development, the City has since adopted new funding sources including housing impact fees, commercial linkage fees, and inclusionary housing in -lieu funds.

To further fair housing and address local fair housing issues, Belmont works closely with the Peninsula Conflict Resolution Center (PCRC) to improve its fair housing enforcement capacity and with Project Sentinel to promote services to city residents and publicize fair housing information at the city’s permit center.

While Belmont has seen numerous improvements since the previous planning period, some action items were not delivered. The city has attributed this to limited staff capacity and a lack of staffing resources. Policies and programs not implemented since the 2015- 2023 Housing Element include:
 Establish an Existing Conditions Survey for single-family properties;  Implement a two-year pilot Residential Records Request and Inspection Program;  Implement a legalization/amnesty program for ADUs—this was not completed despite receiving $160,000 in SB 2 Planning Grant Program funds; and  Develop and implement a housing rehabilitation outreach program. 406
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 18 According to the California Department of Housing and Community Development AFFH Data Viewer (HCD data viewer), Belmont does not have any public housing buildings (Figure I-6, Attachment C.6). HCD’s map of voucher holder locations shows Belmont as having three census tracts where less than 5% of units have voucher holders and two census tracts with no data (Figure I-7, Attachment C.6). This is a similar pattern in neighboring jurisdictions and in much of central San Mateo County. Voucher concentrations occur in and around Daly City, South San Francisco, and East Palo Alto.

Findings from the 21 Elements Resident Survey show 16% of survey respondents—who live in Belmont—as voucher holders. Of those who have a voucher, 64% of Belmont residents who responded to the survey indicated that it is somewhat difficult to find a landlord that accepts vouchers—this is significantly higher than those who reported that it is not difficult to find landlords who accept vouchers (14%) and those who believe it is very difficult (21%).

Respondents indicated why they found it difficult to find a landlord accepting vouchers, these results are presented below.
 64% indicated that they did not have enough time to find housing before the voucher expired;
 45% responded that the voucher did not cover the rent for places they wanted to live;  36% said that landlords have policies of not renting to voucher holders;  27% reported not being able to find information on landlords who accept vouchers; and
 9% reported facing other challenges in finding landlords accepting vouchers. 407
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 19 SECTION II. Integration and Segregation
This section discusses integration and segregation of the population by protected classes including race and ethnicity, disability status, familial status, and income status. The section concludes with an analysis of racially and ethnically concentrated areas of poverty and affluence.

Integration and Segregation
“Integration generally means a condition in which there is not a high concentration of persons of a particular race, color, religion, sex, familial status, national origin, or having a disability or a particular type of disability when compared to a broader geographic area.

Segregation generally means a condition in which there is a high concentration of persons of a particular race, color, religion, sex, familial status, national origin, or having a disability or a type of disability in a particular geographic area when compared to a broader geographic area.”
Source: California Department of Housing and Community Development Guidance, 2021, page 31.

Race and Ethnicity. Compared to San Mateo County, Belmont has a larger proportion of residents who identify as White, non-Hispanic and a smaller proportion of Hispanic residents. As shown in Figure II-1, Attachment C.6, 54% of Belmont residents are White, non-Hispanic versus 39% of the county and the Bay area overall. Twelve percent (12%) of Belmont residents are Hispanic, compared to 24% in the county and the Bay area overall 10 Belmont has become increasingly racially and ethnically diverse since 2000, largely due to growth in the Asian population (93% increase) and Hispanic population (57% increase) and a decline in the White, non-Hispanic population (17% decline).

Older residents are less diverse with 71% of the population older than 65 years identifying as White, compared to 58% of the population for children less than 18 years old.

By race and ethnic group in Belmont, poverty is highest for American Indian Alaskan Natives (41% live below the poverty line) and Black or African Americans (17%). These residents make up a very small proportion of the city (American Indian Alaskan Native residents totaled 61 in 2019 according to 5-year ACS data; Black or African Americans 10 In Belmont, the share of the population that identifies as American Indian or Alaska Native is less than 1% (61 residents); Black/African American is 1% (275 residents); and Other Races is 4% (1,192 residents). 408
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 20 totaled 275), and, as such, reflect a small number of people living in poverty (approximately 25 American Indian Alaskan Natives and 47 Black or African Americans).

When examined by income range, the data show a mixed picture with American Indian Alaskan Natives also showing a large proportion of high-income households—exhibiting a split income distribution with no middle-income households.11 Households with the most even income distribution include Black or African American and Hispanic or Latinx.

Geospatially, Belmont is split between census tracts with a sizeable gap of White majority residents, as shown in the White Majority Census Tracts map in Figure II-7, Attachment C.6.

The census tracts identified as “Predominant[ly]” White majority are located in the far northwest and far southeast parts of the city, with the latter directly adjacent to White majority tracts that comprise most of San Carlos. Compared to northern jurisdictions in the county, Belmont has more White majority tracts; compared to southern jurisdictions of San Carlos, Woodside, and Menlo Park, Belmont has far fewer White majority tracts. White majority census tracts in Belmont are likely the result of historical and existing land use policies and practices. Land use regulations often influence the type of housing that is built in specific areas/neighborhoods of the city as well as demographic shifts. High costs of living and property values in Belmont are also contributing factors to segregation patterns as income groups varies by race and ethnicity. The city has no Asian majority tracts, no Hispanic majority tracts, and only one segregated neighborhood, as defined by the state Census tract with less than an even balance of racial groups; the far northwestern city Census tract is mostly comprised of Asian and White residents (Figure II-10, Attachment C.6).12
Belmont’s diversity index is low to moderate. The census tract with the highest diversity abuts Highway 101. Data do not show this tract as having concentrations of vouchers or public housing, yet this tract does contain several apartment complexes.

Dissimilarity and Isolation Indices. The Dissimilarity Index, or DI, is a common tool that measures segregation in a community. The DI is an index that measures the degree to which two distinct groups are evenly distributed across a geographic area. The DI represents the percentage of a group’s population that would have to move for each area in the county to have the same percentage of that group as the county overall.

DI values range from 0 to 100—where 0 is perfect integration and 100 is complete segregation. Dissimilarity index values between 0 and 39 generally indicate low segregation, values between 40 and 54 generally indicate moderate segregation, and values between 55 and 100 generally indicate a high level of segregation. 11 A large margin of error due to the limited sampling of AIAN residents by the Census is also a factor. 12 Redlining maps, otherwise known as Home Owners’ Loan Corporation (HOLC) maps, are not available for San Mateo County.
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ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 21 In the Bay Area region, non-Hispanic White residents are more segregated than all other racial and ethnic groups, with the highest levels of segregation among Black and White residents. Segregation among Black and White residents in Belmont is similar to that of the Bay Area region, though rates of isolation among White residents have progressively decreased between 2000 and 2020. According to 2015 data, Belmont has a dissimilarity index of 0.165 among Black and White residents—this means that 16.5% of Black or White residents would need to move to a different neighborhood to create perfect integration among Black and White residents in Belmont.

The isolation index is interpreted as the probability that a randomly drawn minority resident shares an area with a member of the same minority. It ranges from 0 to 100 and higher values of isolation tend to indicate higher levels of segregation.

Isolation indexes among income groups in Belmont are similar to those among racial and ethnic groups. In Belmont, above moderate-income groups are the most isolated group with above moderate-income residents living in neighborhoods where 52.7% of residents are considered above moderate-income.

Segregation for income groups in Belmont is rather similar to segregation throughout the Bay Area region—though rates in Belmont are slightly lower. This is largely due to Belmont’s relatively low population of low-income residents. For example, in 2015 lowincome groups comprised 21.99% of Belmont’s overall population—this compares to 28.7% in the Bay Area region.

Disability Status. The share of the population living with at least one disability is 9% in Belmont compared to 8% in San Mateo County. There are two census tracts in the city that have a 10% to 20% share of the population living with a disability; both are located in the central part of Belmont (Figure II-14, Attachment C.6). Geographic concentrations of people living with a disability may indicate a need for increased access to services, amenities, and transportation that support this population.

For example, according to the Resident Survey, Belmont residents with a disability are more likely to experience ambulatory difficulties (3.6%), followed by an independent living difficulty (3.2%) and cognitive difficulties (3.2%). Disabled persons in Belmont are least likely to experience vision difficulties (1.2%)—these data are presented in Figure III-18, Attachment C.6. Similar to geographic concentrations, disability type is important to identifying needs. For example, persons with an ambulatory difficulty may require additional funding for transportation and programs to improve disabled persons’ ability to access public transit.

Familial Status. A majority of households in Belmont are made up of married-couples, and the city has a higher proportion of married-couple households (62%) than the county (55%) or Bay area overall (51%). Belmont has a similar share of single-person households as the county and Bay area but a smaller share of single parent households—10% in 410
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 22 Belmont versus 15% in the county and Bay area—as well as “other” household types, such as roommates (Figure II-17, Attachment C.6).

Familial status can indicate specific housing needs and preferences. A larger number of nonfamily or single person households indicates a higher share of seniors living alone, young adults living alone or with roommates, and unmarried partners. Higher shares of nonfamily households indicate an increased need for one and two bedroom units. Belmont is slowly aging (Figure II-15, Attachment C.6), yet the city does not have a disproportionately higher share of single-person households. This could change in the future—leading to increased demand for in-home care and supportive services—if Belmont’s older adults remain in their homes as they age.

Belmont’s owner-occupied homes are mostly 3 to 4 bedroom units, while rental units are mostly 1 to 2 bedroom (Figure II-20, Attachment C.6). This distribution aligns well with the distribution of household types. Compared to the county, Belmont has a smaller proportion of large (5 persons+) households (Figure II-16, Attachment C.6), which is partially due to the city’s limited number rental units with 5 or more bedrooms and, to a lesser extent, 3 to 4 bedrooms.

In its analysis of housing needs for Belmont, the Association of Bay Area Governments (ABAG) reports that between 2010 and 2020, the number of single-family units in Belmont increased more than multi-family units: 33 new single-family detached homes were built compared to 18 attached homes, and 18 multi-family units. Belmont’s share of singlefamily homes is about average for jurisdictions in the county, although there is a large variance in shares. For example, single-family homes comprise 58% of Belmont’s housing stock compared to 44% of the City of San Mateo’s, 56% of San Bruno’s, 68% of San Carlos’, and 98% of Atherton’s.

Single parent households often have unique needs and need targeted programs and policies to keep and maintain their housing. In Belmont, single parent households—both single male householders and single female householders—comprise a small portion of households overall. Female-headed family households only comprise 7% of households in the city while male-headed family households comprise 3%. These rates are similar to that of San Mateo County and the Bay area, though Belmont has a lower rate among both household types. There are no census tracts with a concentration of single females with children in the city, this is likely due to the low number of households headed by single females (Figure II-22, Attachment C.6).

Female headed family households are more likely than male headed family households to be renters. As shown in Figure II-19, Attachment C.6, there are 394 renter-occupied female headed family households compared to 146 of male family households. However, more female headed family households own their home. In Belmont, there are 290 units owned by single female households compared to 171 of male headed family households. 411
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 23 Household Income. Compared to San Mateo County, Belmont has:
 A much higher proportion of high-income households: 59% of households in Belmont earn 100% of the AMI and more, versus 49% in the county;  A similar share of very low-income households earning between 31% and 50% AMI and less (11% in Belmont, versus 11% in the county); and  A slightly lower share of extremely low-income households earning less than 30% of AMI (11% in Belmont versus 13% in the county);
 A much smaller share of middle-income households earning between 50% and 100% AMI (18% in Belmont, versus 26% in the county).

The city also has fewer 0-30% AMI households than the Bay area overall as a proportion of total households, fewer middle-income households, and more high-income households.

Belmont’s neighborhoods are all moderately high to very high-income, with no significantly concentrated low-income households (Figures II-26 and 27, Attachment C.6) or poverty 412
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 24 concentrations (Figure II-28, Attachment C.6). Compared to other jurisdictions, Belmont exhibits more variance in income distributions than others in the county when examined spatially by census block group (Figure II-27, Attachment C.6).

Racially or ethnically concentrated areas of poverty and affluence.

Racially Concentrated Area of Poverty or an Ethnically Concentrated Area of Poverty (R/ECAP) and Racially Concentrated Areas of Affluence (RCAAs) represent opposing ends of the segregation spectrum from racially or ethnically segregated areas with high poverty rates to affluent predominantly White neighborhoods. Historically, HUD has paid particular attention to R/ECAPs as a focus of policy and obligations to AFFH. Recent research out of the University of Minnesota Humphrey School of Public Affairs argues for the inclusion of RCAAs to acknowledge current and past policies that created and perpetuate these areas of high opportunity and exclusion.13
R/ECAPs
HCD and HUD’s definition of a Racially/Ethnically Concentrated Area of Poverty is:
 A census tract that has a non-White population of 50% or more (majorityminority) or, for non-urban areas, 20%, AND a poverty rate of 40% or more; OR  A census tract that has a non-white population of 50% or more (majorityminority) AND the poverty rate is three times the average tract poverty rate for the County, whichever is lower.

Source: California Department of Housing and Community Development Guidance, 2021.

It is important to note that R/ECAPs and RCAAs are not areas of focus because of racial and ethnic concentrations alone. This study recognizes that racial and ethnic clusters can be a part of fair housing choice if they occur in a non-discriminatory market. Rather, R/ECAPs are meant to identify areas where residents may have historically faced discrimination and continue to be challenged by limited economic opportunity, and conversely, RCAAs are meant to identify areas of particular advantage and exclusion.

For this study, the poverty threshold used was three times the average tract poverty rate for the County—or 19.1%. In addition to R/ECAPs that meet the HUD threshold, this study includes edge or emerging R/ECAPs which hit two thirds of the HUD defined threshold for poverty—emerging R/ECAPs in San Mateo County have two times the average tract poverty rate for the county (12.8%).
13 Goetz, E. G., Damiano, A., & Williams, R. A. (2019). Racially Concentrated Areas of Affluence: A Preliminary Investigation. Cityscape: A Journal of Policy Development and Research, 21(1), 99–124 413
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 25 In 2010 there were three Census Tracts that qualify as R/ECAPs (19.4% poverty rate) in the county and 11 that qualify as edge R/ECAPs (13% poverty rate). None of the 2010 R/ECAPs or edge R/ECAPs were located in Belmont.

In 2019 there were two Census Tracts that qualify as R/ECAPs (19.1% poverty rate) in the county and 14 that qualify as edge R/ECAPs (12.8% poverty rate). None of the 2019 R/ECAPs or edge R/ECAPs were located in Belmont.

RCAAs.

HCD’s definition of a Racially Concentrated Area of Affluence is:
 A census tract that has a percentage of total white population that is 1.25 times higher than the average percentage of total white population in the given COG region, and a median income that was two times higher than the COG AMI.

As shown above, the majority of Belmont is considered an RCAA. Interestingly, census tracts where cost burdened renters live (discussed in following sections) are not a RCAA.

Census tract 6086—which is not a RCAA—is surrounded by jurisdictions without RCAAs in their adjacent census tracts. Alternatively, census tract 6089 is surrounded by RCAAs. This suggests that Belmont residents in this tract are likely from lower-income and non-White households.

It is important to note that census tracts that are not RCAAs are located on the outer edges of the city. This geographic pattern in Belmont could suggest that lower-income and nonWhite households are being excluded. Contributing factors may include lack of civic participation in outlying areas. When dedicating funding and resources, geographic areas (and patterns) that are not a RCAA should be considered. 414
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 26 Figure C-1. Racially Concentrated Areas of Affluence (RCAAs), Belmont, 2015- 2019
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ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 27 SECTION III. Access to Opportunity
This section discusses disparities in access to opportunity among protected classes including access to quality education, employment, transportation, and environment.

Access to Opportunity
“Access to opportunity is a concept to approximate place-based characteristics linked to critical life outcomes. Access to opportunity oftentimes means both improving the quality of life for residents of low-income communities, as well as supporting mobility and access to ‘high resource’ neighborhoods. This encompasses education, employment, economic development, safe and decent housing, low rates of violent crime, transportation, and other opportunities, including recreation, food and healthy environment (air, water, safe neighborhood, safety from environmental hazards, social services, and cultural institutions).”
Source: California Department of Housing and Community Development Guidance, 2021, page 34.

The California Tax Credit Allocation Committee (TCAC), in collaboration with HCD, developed a series of opportunity maps that help to identify areas of the community with good or poor access to opportunity for residents. The opportunity maps highlight areas of highest resource, high resource, moderate resource, moderate resource (rapidly changing), low resource and high segregation and poverty. TCAC provides opportunity maps for access to opportunity in quality education, employment, transportation, and environment.

The TCAC opportunity maps are useful in comparing how well the sites identified for affordable housing and mixed-income development compare with opportunity access in a jurisdiction overall and against other neighborhoods. The overall goal of that analysis is to create a better balance in the siting of affordable housing among opportunity areas.

Education. TCAC’s education score is based on math proficiency, reading proficiency, high school graduation rates, and the student poverty rate. According to TCAC’s educational opportunity map, all Census Tracts in Belmont have schools with the most positive educational outcomes. Belmont offers a strong educational environment citywide.

The City of Belmont is served by the Sequoia Union High School District and the BelmontRedwood Shores Elementary School District. Sequoia Union is fed by eight elementary school districts in the county.

Enrollment. Overall enrollment in the high school district increased 18% between the 2010-2011 and 2020-2021 school years. Enrollment fluctuated significantly among 416
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 28 Elementary School Districts, however, with the Belmont-Redwood Shore district far outpacing any other district for enrollment increases.

Between the 2010-2011 and 2019-2020 school years, elementary school enrollment in the Belmont-Redwood Shores district increased by 35%, or more than 1,000 students.

Enrollment dropped slightly between the 2020 and 2021 school years (down 162 students), for an overall enrollment change of 30%.

Student diversity. The Belmont-Redwood Shores elementary student body has grown more racially and ethnically diverse since 2011, mostly due to an increase in Asian students (24% in 2010-2011 versus 32% in 2020-2021) and multi-race students (4% to 14%). The proportion of White students has declined (55% to 34%), while the proportion of Hispanic students has increased slightly (15% versus 12%).

Compared to the county overall, the Belmont-Redwood Shores Elementary School District has:
 A much larger share of Asian students (32% versus 17%),  A lower share of Filipino students (3% versus 8%),
 A much lower share of Hispanic students (12% versus 38%),  A slightly larger share of White students (34% versus 26%), and  A much larger share of mixed-race students (14% versus 8%).

Enrollment of special student groups in Belmont-Redwood Shores has been relatively stable over time: 7% of students qualify for free and reduced lunch (FRL) and 10% are English language learners (versus 6% and 8%, respectively, in 2011). Even during the early part of the pandemic, when the county experienced a loss of English Language Learners (decline of 5%), the Belmont-Redwood Shores school district was able to retain these students.

Many schools have sought to increase their diversity of teaching and administrative staff to improve inclusivity for students of color. The gap in student and staff/teacher Hispanic representation is higher in the Sequoia Union High School District than in other districts in the county.

Extenuating circumstances. The Belmont-Redwood Shores district reports no students who are in foster care, are experiencing homelessness, or are members of migrant families as of the 2020-2021 school year. Chronic absenteeism is low for students in the Belmont-Redwood Shores district overall, yet varies by student group, with Hispanic and Pacific Islander students having relatively high rates (12% and 17%, respectively), and students with disabilities at 10%.

Test proficiency. Students in the Belmont-Redwood Shores district score well on state tests: 82% meet or exceed English language arts and literacy standards; 79% exceed 417
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 29 math standards. This compares to 62% (English) and 52% (math) for the county overall.

However, this varies considerably by race and ethnicity, with 44% of Black or African American students and 64% of Hispanic students meeting or exceeding state English language arts standards and 37% of Black or African American students and 52% of Hispanic students meeting or exceeding state math standards.

Students with disabilities in the Belmont-Redwood Shores district do well compared to other districts: 43% of students with disabilities are proficient in math (only Hillsborough Elementary is higher at 48%), and 45% are proficient in English (Woodside is higher at 56%; Hillsborough at 47%).

College readiness. Many high schoolers in the county met admission standards for a University of California (UC) or California State University (CSU) school. Of the high school districts in San Mateo County, Sequoia Union had the highest rate of graduates who met such admission standards at 69% followed by San Mateo Union High with 68%. Pacific Islander, Hispanic, and Black students in the San Mateo Union district were less likely to meet the admission standards with rates of 29%, 46%, and 46% respectively.

Drop-out rates and suspensions. Although San Mateo Union High School has relatively low drop-out rates—4% of students—compared to other districts in the county, drop-out rates among Pacific Islander (20%), Hispanic (16%), and Black (12%) students are significantly higher.

Suspensions are disproportionately high for Hispanic students. Hispanic students make up 34% of the high school district student body, yet account for 66% of suspensions.

Employment. The professional and managerial services industry provides the largest number of jobs in Belmont and has increased the number of jobs faster than any other industry except for the information industry (Figure III-3, Attachment C.6). The health and educational services industry is the second largest provider of jobs in the city, with all other industries providing a much smaller share.

Belmont has a much lower job to household ratio when compared to the county, at 0.62 which is a decline from 0.75 in 2002. This compares to 1.59 for the county and 1.47 for the Bay area. The city is a net provider of workers to the region, mostly of high-wage workers, based on the jobs to workers ratio by wage (Figure III-5, Attachment C.6). The city also has a slightly lower unemployment rate than the county and Bay area.

TCAC’s economic opportunity score is comprised of poverty, adult educational attainment, employment, job proximity, and median home value. Except for the census tract abutting Highway 101 and the south central tract that borders San Carlos, Belmont’s neighborhoods are classified as having the most positive economic outcomes. These two outlier tracts have a higher incidence of lower-income households.
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ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 30 HUD’s job proximity, which measures how close residents in a census tract can access jobs in the regional employment market (with larger employment centers weighted more heavily) shows that Belmont’s proximity to jobs is about average—better than cities located further south but not as strong as cities to the north, who are closer to the City of San Francisco. According to the AARP Public Policy Institute, approximately 30,055 jobs in the city can be accessed by public transit while 108,262 jobs can only be accessed by car.

Employment accessibility can provide barriers to economic success, especially if public transportation costs exceed what residents can afford. In 2022, the AARP Public Policy Institute estimated that household transportation costs were $15,354 per year. Cost and severely cost burdened households will likely struggle to afford public transportation if yearly public transit expenses increase.

Economic outcomes are also reliant on broadband and internet access. In 2022, 99.8% of Belmont residents had access to high-speed internet—this likely contributes to positive scores in the city. However, Belmont does not have policies in place to remove barriers for residents without broadband access; however, County CDBG funding could be used for this purpose.14
As will be discussed below, persons with disabilities do not appear to face unique barriers in accessing employment and employment opportunities. According to ABAG data, employment and unemployment rates among disabled persons and persons without a disability are relatively similar.

Transportation. SamTrans provides bus services in San Mateo County including RediWheels paratransit service. The San Mateo County Transit District acts as the administrative body for transit and transportation programs in the county including SamTrans and the Caltrain commuter rail.

In 2018, the Metropolitan Transportation Commission (MTC), which covers the entire Bay Area, adopted a coordinated public transit and human services transportation plan. While developing the coordinated plan, the MTC conducted extensive community outreach about transportation within the area. That plan—which was developed by assessing the effectiveness of how well seniors, persons with disabilities, veterans, and people with low incomes are served—was reviewed to determine gaps in services in Belmont and the county overall15.

Although Belmont was not mentioned specifically in the plan, its residents with public transportation needs have not grown significantly. Even if public transportation needs have not grown, Belmont residents still face difficulty in accessing public transit options.

According to findings from the 21 Elements Resident Survey, 19% of Belmont respondents find it difficult to access public transit safely and easily (e.g., bus or light rail). This is 25% 14 https://livabilityindex.aarp.org/search/Belmont,%20California,%20United%20States. 15 https://mtc.ca.gov/sites/default/files/MTC_Coordinated_Plan.pdf 419
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 31 above that of the region. Accessing public transit is also difficult for residents in Brisbane (29%), Hillsborough (25%), Pacifica (21%), and Half Moon Bay (18%). Relatedly, 14% of Belmont respondents indicated that city buses/rails do not go where residents need to go or operate during the times they need. Thirty-one percent (31%) of Belmont residents also reported living in neighborhoods without adequate walking areas—this rate is 25% above that of the county overall.

Belmont has taken steps to remove barriers for disabled persons in accessing public transportation. For instance, 89% of public transit stations comply with regulations established by the Americans with Disabilities Act (ADA). San Mateo County and Belmont also have Transit Oriented Development (TOD) programs to improve walkability surrounding transit stations and access to transit stops.

In the county overall, the primary gaps in transportation access include:
 The “spatial gaps” in public transportation continue to be a challenge. Lack of connectivity can make it very difficult for populations reliant on public transit to access the region.
 Transit and paratransit systems lack service in the evenings, late at night, and on weekends—which can limit users’ access to jobs, education, and entertainment.  The areas in the region that are aging the fastest are suburban and rural in nature— and can be difficult to serve by fixed-route transit.
 Fees to access transit and paratransit are too high for many low- and fixed-income households.
 Funding needs are growing faster than revenues.

A partnership between the World Institute on Disability and the MTC created the research and community engagement project TRACS (Transportation Resilience, Accessibility & Climate Sustainability). The project’s overall goal is to, “stimulate connection and communication between the community of seniors and people with disabilities together with the transportation system– the agencies in the region local to the San Francisco bay, served by MTC.”16 TRACS highlights that improving accessibility requires engagement for the community because there are no “watch-dog” systems in place to hold agencies accountable.

As part of the TRACS outreach process, respondents were asked to share their compliments or good experiences with MTC transit. One respondent who had used multiple services said, “it is my sense that SamTrans is the best Bay Area transit provider in terms of overall disability accommodation.” 16 https://wid.org/transportation-accessibility/
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ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 32 The San Mateo County Transit District updated their Mobility Plan for Older Adults and People with Disabilities in 2018. According to the district, the county’s senior population is expected to grow more than 70% over the next 20 years and the district is experiencing unprecedented increases in paratransit ridership. The plan is targeted at developing effective mobility programs for residents with disabilities and older adults including viable alternatives to paratransit, partnerships, and leveraging funding sources.17 MTC also launched Clipper START—an 18 month pilot project— in 2020 which provides fare discounts on single transit rides for riders whose household income is no more than double the federal poverty level.18
Environment. TCAC’s opportunity areas environmental scores are based on the CalEnviroScreen 4.0 indicators which include pollution metrics such as ozone, PM2.5, diesel PM, drinking water, pesticides, toxic release, traffic, cleanup sites, groundwater threats, hazardous waste, impaired water bodies, and solid waste sites.

Belmont scores moderately-high on environmental outcomes. The one census tract that abuts Highway 101 has the lowest environmental score in the city; this is also the tract with the most diversity of housing types. The reason for this score is primarily the result of exposure to traffic and the resulting pollution from vehicle traffic. It is important to note that no housing opportunity sites are located in the area next to Highway 101in this tract to ensure no additional concentration of housing units next to the freeway.

All of Belmont’s neighborhoods have the strongest measures in the California Healthy Places Index (HPI) (Figure III-11, Attachment C.6) developed by the Public Health Alliance of Southern California (PHASC). The HPI includes 25 community characteristics in eight categories including economic, social, education, transportation, neighborhood, housing, clean environment, and healthcare.19 This index suggests that all parts of Belmont provide residents access to healthy environments as measured by the index.

Despite having a comparatively high HPI, Belmont residents do face environmental hazards. The AARP Public Policy Institute provides livability indexes20 for all cities and counties based on categories such as housing, neighborhood characteristics (e.g., access to grocery stores), transportation, environment, health, engagement, and opportunity.

According to the AARP Public Policy Institute, Belmont has an environmental index of 46 (out of 100). This index is based on the city’s drinking water and air quality and nearroadway pollution. In 2022, 0.04% of Belmont residents are exposed to drinking water violations and there are 7.3 unhealthy air quality days per year—this represents an increase from 0% of people exposed to poor drinking water in 2015 and 1 unhealthy air 17 https://www.samtrans.com/Planning/Planning_and_Research/Mobility_Plan_for_Older_Adults_and_ People_with_Disabilities.html 18 https://mtc.ca.gov/planning/transportation/access-equity-mobility/clipperr-startsm 19 https://healthyplacesindex.org/about/ 20 Livability indexes provided by the AARP Public Policy Institute are based on data from the US Census Bureau, ACS data, and related city and county policies.
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ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 33 quality day per year in 2015. The environmental index provided by AARP also shows that 28% of residents were exposed to near-roadway pollution in 2022.

Environmental constraints. The City of Belmont released a report on the city’s Housing Constraints.21 The report includes environmental constraints in the city and how these constraints impact residential development and development costs. According to the report, Belmont experiences environmental issues ranging from suitable land for development, the provision of adequate infrastructure, and energy costs.

As stated in the Housing Constraints report, Belmont encompasses approximately 2,955 acres and the majority of the city’s parcels are developed. Undeveloped parcels are in the Western Hills area with small amounts in the San Juan area and areas east of Highway 101.

However, Belmont identified numerous environmental constraints on development in these areas including steep slopes, landslide hazards, fire hazards, and flood hazards.

Other constraints outlined in the report include seismic hazards, topography/slope, sea level rise, and water/sewer capacity.

Disparities in Access to Opportunity. Because Belmont is classified as a high resource area throughout and lacks racial and ethnic concentrations, the distribution of residents among high resource areas matches the city’s racial and ethnic distribution (Figure III-12, Attachment C.6).

TCAC’s composite opportunity score for Belmont shows all but one census tract as “highest resource.” The census tract bordering Highway 101 is classified as “high resource.” The Social Vulnerability Index (SVI) provided by the Centers for Disease Control (CDC)— ranks census tracts based on their ability to respond to a disaster—includes four themes of socioeconomic status, household composition, race or ethnicity, and housing and transportation. Belmont is rated as having low to moderately-low vulnerability to disasters (Figure III-15, Attachment C.6).

Belmont does not have any disadvantaged communities as defined under SB 535, “disadvantaged communities are defined as the top 25% scoring areas from CalEnviroScreen along with other areas with high amounts of pollution and low populations.”22
21 https://www.belmont.gov/home/showpublisheddocument/21605/637921852304683878. 22 https://oehha.ca.gov/calenviroscreen/sb535 422
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 34 Disability
“Disability types include hearing difficulty, vision difficulty, cognitive difficulty, ambulatory difficulty, self-care difficulty, and independent living difficulty.” Source: California Department of Housing and Community Development Guidance, 2021, page 36.

Disparities Specific to the Population Living with a Disability. Nine percent (9%) of the population in Belmont is living with at least one disability, compared to 8% in the county. The most common disabilities in the city are ambulatory (3.6%), independent living (3.2%), and cognitive (3.2%).

For the population 65 and over the share of the population with an ambulatory or independent living difficulty increases significantly—to 14.4% of the senior population.

Should Belmont’s seniors choose to age in place, demand for in-home care, paratransit, and accessibility improvements will increase.

Persons with disabilities have unique needs and often face greater barriers in finding housing that meets their needs, accessing employment opportunities, and accessing public transportation. This section provides an in-depth analysis of these needs and Belmont’s progress in meeting them.

Disabled persons living in Belmont are more likely to have an ambulatory difficulty (3.6%), followed by an independent living difficulty (3.2%) and cognitive difficulties (3.2%). Only

1.2% of disabled persons in the city have a vision difficulty. Although persons with disabilities often face greater barriers in accessing jobs and employment opportunities, employment rates among Belmont’s population of disabled persons is similar to that of non-disabled residents. As shown in Figure III-20, Attachment C.6, 95% of disabled residents are employed, only 5% are unemployed. For residents without a disability, 97% are employed and 3% unemployed. Employment rates for disabled persons in Belmont suggest that persons with disabilities do not—on average—experience disparities in accessing employment opportunities.

Belmont has made various efforts to improve disabled persons’ ability to access housing, employment, and supportive services. Belmont supports and provides housing for persons with disabilities (including developmental disabilities). The city currently owns two low- and very low-income group homes for adults with developmental disabilities. Belmont also works closely with the Center for Independence of Individuals with Disabilities (CID) to provide disabled residents with services including housing accessibility modifications, independent living skills training, and peer counseling. In the city’s Notice of ADA Compliance,23 Belmont committed the city to improving communication to ensure that all 23 https://www.belmont.gov/home/showdocument?id=16121.
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ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 35 disabled persons can participate in all city programs, services, and activities. More specifically, Belmont will—upon request—provide aids and services for effective communications including sign language interpreters and documents in Braille (or alternative formats) to provide accessible information and communication to people with speech, hearing, vision, or cognitive impairments. Expanding on this, Belmont modified its city codes to allow individuals with service animals in city offices and facilities—even if pets are prohibited. The city also designated an ADA Coordinator to maintain, track, and address discrimination cases and accessibility barriers.

In 2018, the city developed a Transition Plan—based on the city’s 2017 self-evaluation report—to determine which facilities and neighborhood infrastructure must be changed to remain compliant with the Americans with Disabilities Act (ADA).24 To develop the plan, Belmont evaluated existing policies and practices, identified obstacles that limit accessibility, set numerous priorities for barrier elimination, and launched community events at senior centers to gather input from the city’s population of disabled persons.

Below is a list of proposed measures, practices, and policies for Belmont to implement to address accessibility problems and incidents of discrimination on the basis of disability status.
 Implement a formal policy to address federal and state legal requirements—this policy would institutionalize organizational procedures to address accessibility features if and when they fail (e.g., accessible elevators);
 Establish an annual General Fund dedicated to mitigating accessibility barriers;  Find funding sources including funds associated with the city’s Capital Improvement project funds and existing city projects; and
 Provide accessible features including—but not limited to—accessible routes, ramps, and elevators.

According to community input, accessibility concerns are largely based on daily travel routes and sidewalks. One participant, for instance, shared that city streets only have shoulders—this has forced disabled persons to share the street with vehicles. The city also lacks curb ramps allowing for transitions between streets to areas with limited segments of sidewalks. Other accessibility concerns include tripping hazards due to sidewalk and intersection barriers.

Findings from the 21 Elements Resident Survey support feedback from residents. Belmont residents—regardless of disability status—identified neighborhood infrastructure as the greatest housing and neighborhood challenges they encounter. In fact, residents in Belmont experience problems such as bad sidewalks and no lighting more acutely than the county overall. Thirty-one percent (31%) of Belmont respondents identified these problems 24 https://www.belmont.gov/home/showpublisheddocument/19520/637240186694170000. 424
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 36 as the greatest challenge they face—this is similar to feedback from residents in East Palo Alto (40%), Daly City (25%), and Hillsborough (23%).

Actions the city has taken to improve accessibility features and further accommodate their population of disabled persons have been largely successful—especially in terms of providing housing that meets residents’ accessibility needs. Findings from the 21 Elements Resident Survey demonstrate Belmont’s progress in providing housing opportunity and supportive services. For example, the resident survey asked respondents—with a disability—to share their perspective on their housing situations (e.g., accessibility improvements). Eighty-nine percent (89%) of disabled persons in Belmont reported living in housing that met their needs. Of those who do not live in such housing, 62% of respondents reported needing grab bars in their bathroom and/or a bench in their shower and 67% need supportive services to help them take care of themselves or their home.

These results are substantially more positive than feedback collected from the county overall—74% of all respondents in San Mateo County indicated that their housing situation does meet their accessibility needs. Accessibility features and services that Belmont residents need are similar to that of the county overall.

Access to Opportunity
Regional Access
Belmont San Mateo County
Jobs to Household Ratio 0.62 1.59
Unemployment Rate 5% 6%
LEP Population 4% 7%
Share of Population by Race in Resource Areas
Employment by Disability Status
High/Highest Resource Area 0% 28% 1% 54% 4% 12%
American Indian or Alaska Native, NH Asian / API, NH
Black or African American, NH White, Non-Hispanic (NH)
Other Race or Multiple Races, NH Hispanic or Latinx
97%
95%
3%
5%
No Disability
With A Disability
Employed Unemployed
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ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 37 SECTION IV. Disproportionate Housing
Needs
This section discusses disparate housing needs for protected classes including cost burden and severe cost burden, overcrowding, substandard housing conditions, homelessness, displacement, and other considerations.

Disproportionate Housing Needs
“Disproportionate housing needs generally refers to a condition in which there are significant disparities in the proportion of members of a protected class experiencing a category of housing need when compared to the proportion of members of any other relevant groups, or the total population experiencing that category of housing need in the applicable geographic area. For purposes of this definition, categories of housing need are based on such factors as cost burden and severe cost burden, overcrowding, homelessness, and substandard housing conditions.”
Source: California Department of Housing and Community Development Guidance, 2021, page 39.

Housing Needs. According to ABAG, the population of Belmont increased by 6.7% from 2000 to 2020, which is below the growth rate of the Bay area. However, the city’s population growth has generally been in line with the county.

ABAG also reports that the number of homes in Belmont increased, 0.6% from 2010 to 2020, below the growth rate for San Mateo County and the broader region.

A total of 240 building permits were issued in Belmont between 2015 and 2020. Of those:
 138, or 57.5% were for above moderate-income units,
 36, or 15% were for moderate-income units,
 44, of 18.3% for low-income units, and
 22, or 9%, for very low-income units.
 Altogether, more than one-fourth of the permits were for low and very low-income units.

The majority of the housing inventory in Belmont was built between 1940 and 1960 (5,131 units), followed by 1960 to 1979 (3,358 units). The number of units built after 2010 (470) is three times the number built between 2000 and 2009 (just 149)—a positive trend for addressing housing gaps. The age of Belmont’s housing stock is especially important for city officials to consider when establishing programs for housing rehabilitation. The 426
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 38 needs analysis estimates that there are approximately 1,311 total units needing rehabilitation, from minor repairs to substantial rehabilitation.

Belmont has a much larger share of owner-occupied units priced between $1 million and $2 million than the county—65% of units in the city fall within this price range compared to 37% in the county. Just 18% of Belmont’s owner-occupied units are priced below $1 million, compared to 44% for the county and 65% for the Bay area overall.

According to the Zillow home value index, home prices have experienced remarkable growth in the city and county since 2011, with Belmont’s prices accelerating faster than the county or Bay area overall (Figure IV-5, Attachment C.6).

Rents in Belmont have increased at the same pace as in the county and remain about 30% higher than rents in the Bay area overall. Belmont’s rental distribution is more closely aligned with the county’s overall but much less affordable than the Bay area overall (Figure IV-6, Attachment C.6). In Belmont, 65% of rental units are priced at $2,000 or more, compared to 59% in the county, and 42% for the Bay area overall.

Condition of Housing Stock. Despite Belmont having a relatively younger housing stock, residents seem to face housing condition challenges at higher rates than the county overall. In the 21 Elements Resident Survey, 15% of respondents from Belmont indicated that their home or apartment is in bad condition while 10% reported having bed bugs, insects, or a rodent infestation—both of which are 25% above the regional average.

Additionally, 22% of respondents reported that their home or apartment is not big enough for their family. These findings supplement housing data and provide greater direction for the city when identifying rehabilitation programs and policies.

Cost Burden and Overpayment. Belmont households face lower rates of cost burden—spending more than 30% of gross income on housing costs—than in the county and Bay area overall25. Seventeen percent (17%) of Belmont households are cost burdened (versus 20% in the county) and 13% are severely cost burdened (versus 17% in the county), spending more than 50% of their gross income on housing costs. Cost burdened households have less money to spend on other essentials like groceries, transportation, education, healthcare, and childcare. Extremely cost burdened households are considered at risk for homelessness.

Cost burden is much higher for renters: in Belmont, 47% of renters are cost burdened compared with 21% of owners. Nearly all of Belmont’s households earning 30% of AMI and less are burdened, with the vast majority severely burdened (Figure IV-10, Attachment C.6). The level of burden diminishes greatly once households earn 80% of AMI and more.
25 Cost burden and severe cost burden are HUD and industry standard metrics. 427
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 39 Cost burden varies across residents of different races and ethnicities. Black or African American households, mixed race households, and Hispanic households are most likely to face severe cost burden, with rates ranging from 25% to 30%. Asian households are the least likely to be severely burdened, at 9%. Overpayment also varies by household size.

Belmont’s large family households— households with five or more persons—are less likely to be cost burdened than other households. In fact, 79% of large households are not cost burdened compared to 66% of other households. Relatedly, only 21% of large family households are cost burdened while 34% of other households overpay for their housing.

Figures IV-13 and IV-14, Attachment C.6 show the geographic distribution of overpayment rates among homeowners and renters in Belmont. Although there are no highly concentrated areas of overpayment in the city, the largest portion of renters overpaying for their housing are concentrated in census tracts 6086 and 6089. In census tracts 6088 and 6090, 20% to 40% of renters are cost burdened. No census tract in Belmont has less than 20% of renters experiencing cost burden. Excluding census tract 6089 where less than 20% of homeowners overpay for their housing, all census tracts in Belmont show 20% to 40% of cost burdened owners. It is important to note that areas where renters are more likely to be cost burdened (census tract 6089) is the one location where the least number of homeowners overpay. As shown in Figure IV-29, Attachment C.6, census tract 6088 is one of the more expensive areas in the city—this census tract has the smallest proportion of overpaying homeowners.

Overcrowding. The vast majority of households (95%) in Belmont are not overcrowded—indicated by more than one occupant per room. See Figure IV-19 in Attachment C.6. Renter households make up the vast majority of the city’s households living in overcrowded conditions. Asians and persons of Hispanic descent have much higher rates of overcrowding than others: 7.8% of Asian residents live in overcrowded conditions and 10% of Hispanic residents live in overcrowded conditions. These compare with 2.8% of non-Hispanic White residents.

By race and ethnicity, the city’s Hispanic and mixed-race households are the most likely to be living in overcrowded conditions. Belmont has no geographic concentrations of overcrowded households, as shown in the map below. Belmont is similar to Foster City, Hillsborough, and Burlingame for overcrowding. Nearby City of San Mateo and San Carlos each have one tract with moderate overcrowding (8.3% to 12%).

Substandard Housing. Renter households are also more likely to have substandard kitchen and plumbing facilities compared to owner households. Of the city’s renters, 6.6% are lacking kitchen facilities, while less than 1% are lacking plumbing. For owners, less than 1% are lacking either kitchen or plumbing facilities. Rates of substandard housing in Belmont are relatively low, however, city residents do face housing condition challenges outside of the four substandard housing conditions identified by HUD. The condition of the city’s housing stock is explained in greater detail above. 428
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 40 As noted in the Housing Needs Appendix, a summary of the most common code enforcement activity provided by the Code Enforcement Officer includes residential yard and tree maintenance, illegal dumping, construction without permits, abandoned/inoperable vehicles, smoking in multi-family residential units (prohibited in Belmont), trash and debris in public view, rodent infestation and dilapidated property fences. None of these frequent violation types provides insight into the estimated number of housing units in need of rehabilitation. Additionally, the code enforcement officer has confirmed that estimating rehabilitation needs based on age of housing stock is a reasonable measure. There do not appear to be any visual housing stock trends (i.e. boarded up windows/doors, roof or other structural damage, significant external damage) in Belmont that would guide housing rehabilitation needs/services.

Homelessness. In 2019, 1,512 people were experiencing homelessness in the county, 40% of people were in emergency or transitional shelter while the remaining 60% were unsheltered. The majority of unsheltered people experiencing homelessness were in households without children. The majority of people in transitional housing were in households with children. People who identified as American Indian or Alaskan Native (6% homeless but represent less than 1% of the general population), Black (13%, 2%), White (67%, 51%), and Hispanic (38%, 28%) are overrepresented in the homeless population compared to their share of the general population. People struggling with chronic substance abuse (112 people), severe mental illness (305), and domestic violence (127) represent a substantial share of the homeless population in 2019.

The City has no local data on homelessness to the extent needed for this analysis because it was not collected during the last homeless count. That said, the City is an active participant in the 21 Elements group as well as the Countywide CoC. In addition, the Housing Element Implementation Plan contains actions to ensure that transition housing, supportive housing, and shelters are permitted in every zoning district where housing is allowed.

Displacement and Retaining Assisted Units. Belmont has 106 low-income affordable units at risk of converting to market rate units. The risk of these units converting to market rate is low, however, according to the California Housing Partnership. Low risk is defined as units that are at risk of converting in a longer timeframe (10+ years) and which are currently owned by a large and/or stable nonprofit, mission-driven developer.

According to the Urban Displacement Project, three census tract in the city—two abutting Highway 101 and one abutting Highway 280—are at risk of “becoming exclusive.” This is based on a large rise in the home value and rent change in the census tracts between 2012 and 2018. These tracts also have high shares of renter households. As shown in Figure IV28, Attachment C.6, there are two census tracts in Belmont that are considered at risk of displacement—census tract 6089 and part of census tract 6086. 429
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 41 Findings from the 21 Elements Resident Survey support census tract data from the Urban Development Project. Survey results indicate that Belmont faces greater risks of displacement than the overall region. Overall, 21% of respondents reported that they had been displaced from their housing in the past five years. Comparatively, 29% of Belmont respondents reported being displaced. Top reasons for displacement in Belmont include apartment rules (30%), rent increased more than they could pay (25%), and landlord refused to renew their lease (25%). Residents displaced from rent increases will likely continue if home values and rent changes follow patterns between 2012 and 2018.

Of all households in Belmont that reported being displaced in the resident survey, 45% of children had to change schools. This is a lower rate than the county overall where 60% of children in displaced households had to change schools. Despite having a lower rate, displacement is a major challenge for children and heavily influences education outcomes.

According to the survey, displaced children in Belmont experienced negative outcomes from changing schools. Top school change outcomes reported by Belmont respondents include: they are in a worse school (44%), the school is more challenging (33%), and they feel less safe at their new school (33%).

Displacement can occur due to natural disasters (e.g., flooding, wildfires) as well. According to the 2012 Flood Insurance Rate Map (FIRM)—adopted by the Federal Emergency Management Agency (FEMA)—flooding hazards generally follow Belmont Creek. To reduce flooding hazards in areas surrounding Belmont Creek, the city had adopted a stormwater management program and additional regulations related to floodplain management.

These regulations were adopted and integrated in the city’s Municipal Code (Sections 7-201 through 7-222).

To assist displaced residents, the city is considering an anti-displacement policy and housing preference policy. The housing preference policy will prioritize residents applying for housing that have been displaced from a unit in the past three years. Belmont is also working towards establishing foreclosure avoidance programs, an eviction prevention ordinance, and increased funding for fair housing legal services. There is a need for additional preservation and anti-displacement efforts. These efforts should focus on units located near Highway 101 to facilitate access to services, transit, employment, and quality education in the city and surrounding areas.

Access to mortgage loans. Disparities by race and ethnicity are also prevalent for home mortgage applications, particularly in denial rates. Hispanic mortgage loan applicants (29% denial rate), American Indian or Alaska Native households (33% denial rate), and Black or African American households (27% rate) had the highest denial rates for mortgage loan applications in 2018 and 2019. These compare to 14% for Asian applicants and 20% for White applicants.
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ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 42 Disproportionate Housing Needs
Cost Burden. Belmont, 2019
Area Median Income (AMI)
Overcrowding, Belmont, 2019
Occupants per Room by Tenure
Substandard Housing, Belmont, 2019
Incomplete Kitchen and Plumbing Facilities by Tenure
Homelessness, San Mateo County, 2019
Race and Ethnicity
Share of Homeless
Population
Share of Overall
Population
American Indian or Alaska Native 6% 0%
Asian / API 6% 30%
Black or African American 13% 2%
White 67% 51%
Other Race or Multiple Races 8% 17%
Displacement, Belmont, 2019
Assisted Units at High or Very
High Risk of Displacement Belmont San Mateo County
Number of Units 0 417
% of Assisted Units 0% 8%
7%
21%
44%
73%
90%
17%
39%
39%
23%
10%
76%
39%
17%
4%
0%-30% of AMI
31%-50% of AMI
51%-80% of AMI
81%-100% of AMI
100%+ of AMI
0%-30% of Income Used for Housing 30%-50% of Income Used for Housing 50%+ of Income Used for Housing

0.6%

0.0%

6.6%

0.3%
Kitchen
Plumbing
Owner Renter

4.7%

4.8%

0.8%

0.5%

1.0 to 1.5 Occupants per Room
More than 1.5 Occupants per Room
Owner Renter Series3

1.5+ Occupants
per Room
1-1.5 Occupants
per Room

0.6%

0.0%

6.6%

0.3%
Kitchen
Plumbing
Owner Renter

1.5+ Occupants
per Room
1-1.5 Occupants
per Room
431
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 43 SECTION V. Site Inventory Analysis
AB 686 requires an analysis of sites identified to meet RHNA obligations for their ability to affirmatively further fair housing.

Census Tract Sites Analysis
The City’s proposed RHNA sites can accommodate approximately 1,176 new units and 1,023 pending and pipeline units. Table C-1 shows the distribution of those units across Census Tracts, in addition to the proportion of the population that identifies as Hispanic, the non-White share of the population, the share of low and moderate-income households, the number of R/ECAPS and RCAAs, TCAC’s opportunity score for all Census Tracts in the city. Figure 2 shows the distribution of the City’s proposed sites geographically.

Census Tract 6086
Characteristics. Census Tract 6086 is located east of CA-82 adjacent to Redwood City and Foster City to the east. The area is predominantly commercial uses along CA-82 and Highway 101. There are several lower density single-family neighborhoods and large apartment communities within the Tract. St. Mark Catholic Church, Nesbit Elementary School, various hotels, and a Caltrain Station are also located within this Census Tract.

According to TCAC’s opportunity area map, the Census Tract is a high resource area. There is a moderate share of low or moderate-income households (37% of households in the Tract). The majority of the population in this Tract are non-White (62%) and one in five (20%) identify as Hispanic. The Tract is not an R/ECAP or RCAA and is rated lower displacement risk under the Urban Displacement, Estimated Displacement Risk designations.

Assessment. The addition of 958 site inventory units including 344 for low and moderate-income (LMI) households may contribute to existing concentrations of nonWhite and LMI households in Belmont. However, Belmont as a whole is less diverse than San Mateo County overall. The demographics of this Census Tract are similar to the larger County. Neighborhoods in this area are established and provide opportunities for mixedincome households—characterized by stable moderate/mixed-income by the Urban Displacement typologies. The introduction of affordable units for low-income households could help prevent the Tract from gentrification and displacement. The addition of 44% of the City’s proposed units within this Census Tract may modestly raise the overall proportion of low and moderate-income households within this Tract. However, these sites also provide access to the high resource areas and transportation as well as help to prevent displacement of renters from the Downtown area.

Considerations. 958 site inventory units are proposed in Census Tract 6086, including 345 units for LMI households and 613 units for above moderate-income households, 633 of which are pipeline units.
432
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 44 Census Tract 6087
Characteristics. Census Tract 6087 is located between the City’s border to the north, CA82 to the east, Ralston Avenue to the south, and Alameda de las Pulgas to the west. The area is predominantly low density single-family with commercial uses along CA-82 to the east. Barrett Community Center, Notre Dame High School, Notre Dame Elementary School, Notre Dame de Namur University, and several community parks are also located within this Census Tract. Generally, the Census Tract is ranked as a highest resource area according to the TCAC’s opportunity areas and contains a moderate share of low- or moderate-income households (31% of households in the Tract). The majority of the population in this Tract are non-White (53%) and 12% identify as Hispanic. Finally, the Tract is not an R/ECAP and is rated lower displacement risk under the Urban Displacement, Estimated Displacement Risk designations.. This Census Tract is an RCAA.

Assessment. The addition of 785 site inventory units, including 518 for LMI households, will help stabilize this area and provide continued opportunities for LMI households to live in this highest resource Census Tract. Neighborhoods in this area are at risk of becoming exclusive, as characterized by the Urban Displacement definitions.

The introduction of affordable units for low-income households in this at-risk area could help prevent the Tract from gentrification and displacement. The addition of 36% of the City’s total proposed units within this Census Tract may modestly raise the overall proportion of low and moderate-income households within this Tract. However, this Census Tract is an RCAA and highest resource area that is at-risk of becoming exclusive.

Integrating additional housing units in this area is imperative to stabilize the neighborhood and prevent it from becoming exclusive.

Considerations. 785 site inventory units are proposed in Census Tract 6087, including 518 for LMI households and 267 units for above moderate-income households, 186 of which are pipeline units.

Census Tract 6088
Characteristics. Census Tract 6088 is located between the City’s border to the north, Alameda de las Pulgas to the east, Ralston Avenue to the south, and the City’s border to the west. The area is entirely very low density single-family, open space, and neighborhood uses. Cipriani Elementary School, dog park, San Juan Canyon Open Space, and Fellowship Bible Church are also located within this Census Tract. Generally, the Census Tract is ranked as a highest resource area according to the TCAC’s opportunity areas and contains the lowest share of LMI households (14% of households in the Tract) compared to other Tracts in the City. Less than half of the population in this Tract is non-White (44%) and 8% identify as Hispanic. Finally, the Tract is not an R/ECAP and is rated lower displacement risk under the Urban Displacement, Estimated Displacement Risk designations. This Census Tract is an RCAA.
433
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 45 Assessment. Only 14 site inventory units including 11 for LMI households are proposed in this Census Tract. Neighborhoods in this area are established and unaffordable to lowincome households—characterized by stable advanced exclusive by the Urban Displacement definitions. The introduction of affordable units for low-income households in this exclusive Census Tract will further integrate the City of Belmont.

However, the addition of >1% of the City’s total proposed units within this Census Tract is not likely to change existing demographics of the Tract substantially. These sites will provide access to the highest resource areas and would further integrate this RCAA.

Considerations. 14 site inventory units are proposed in Census Tract 6088, including 11 units for LMI households and 3 units for above moderate-income households, all of which are pipeline units.

Census Tract 6089
Characteristics. Census Tract 6089 is located between Ralston Avenue to the north, Alameda de las Pulgas to the east, and the City’s border to the south and west. The western portion of this Census Tract is low density residential and open space. Conversely, the eastern portion of the Tract is primarily apartment complexes. San Mateo County Human Services, Fox Elementary, Ralston Middle School, Carlmont High School, and Belmont Public Library are also located within this Census Tract. Generally, the Census Tract is a highest resource area according to the TCAC’s opportunity areas and contains the highest share of LMI households (39% of households in the Tract) compared to other Tracts in the City.

More than half of the population in this Tract is non-White (52%) and 9% identify as Hispanic. Finally, the Tract is not an R/ECAP or RCAA and is rated lower displacement risk under the Urban Displacement, Estimated Displacement Risk designations.

Assessment. There are no site inventory units proposed in this Census Tract.

Neighborhoods in this area are established and provide opportunities for mixed-income households—characterized by stable moderate/mixed-income by the Urban Displacement definitions.

Considerations. There are no site inventory units in Census Tract 6089.

Census Tract 6090
Characteristics. Census Tract 6090 is located between Ralston Avenue to the north, CA82 to the east, the City’s border to the south, and Alameda de las Pulgas to the west. The area is predominantly low-density single-family with commercial uses along CA-82 to the east and apartments along Alameda de las Pulgas to the west. Charles Armstrong School, Twin Pines Park, Silverado Belmont Hills Memory Care, and McDougal Park are also located within this Census Tract. Generally, the Census Tract is a highest resource area according to the TCAC’s opportunity areas and contains a moderate share of low- or moderateincome households (29% of households in the Tract). The majority of the population in this Tract are non-White (51%) and 15% identify as Hispanic. Finally, the Tract is not an R/ECAP 434
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 46 and is rated lower displacement risk under the Urban Displacement, Estimated Displacement Risk designations. This Census Tract is an RCAA.

Assessment. The addition of 339 site inventory units including 216 for LMI households would help maintain the Tract as mixed-income and further integrate the City of Belmont. Neighborhoods in this area are established and provide opportunities for mixed-income households—characterized by stable moderate/mixedincome by the Urban Displacement definitions. The introduction of affordable units for low-income households could help prevent the Tract from gentrification and displacement. The addition of 19% of the City’s proposed units within this Census Tract will help maintain the current income distribution of the Census Tract and continue to provide opportunities for mixed-income households to live in this RCAA and highest resource area.

Considerations. 339 site inventory units are proposed in Census Tract 6090, including 216 for LMI households and 123 units for above moderate-income households, 87 of which are pipeline units.

Census Tract 6091
Characteristics. Census Tract 6091 is only partially located in the City of Belmont, and the majority of the Tract is in San Carlos covering the downtown area. The area is almost entirely commercial uses between Highway 101 and CA-82. There are a handful of RHNA sites in this Tract near the single-family residential neighborhood between Ralston Avenue and O’Neil Avenue in Belmont. Generally, the Census Tract is a high resource area according to the TCAC’s opportunity areas and contains a moderate share of low- or moderate-income households (34% of households in the Tract). The majority of the population in this Tract are non-White (54%) and one out of three identify as Hispanic.

Finally, the Tract is not an R/ECAP and is rated lower displacement risk under the Urban Displacement, Estimated Displacement Risk designations. This Census Tract is an RCAA.

Assessment. The addition of 103 site inventory units, including 16 for LMI households, would help maintain the Tract as mixed-income and further integrate the City of Belmont.

Neighborhoods in this area are established and provide opportunities for mixed-income households—characterized by stable moderate/mixed-income by the Urban Displacement definitions. The introduction of affordable units for low-income households could help prevent the Tract from gentrification and displacement.

Considerations. 103 site inventory units are proposed in Census Tract 6091, including 16 units for LMI households and 87 units for above moderate-income households, all of which are pipeline units.
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ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 47 TABLE C-1. BELMONT PROPOSED RHNA SITES BY CENSUS TRACT SUMMARY Census Tract
AFFH Data Sites Inventory Units
Pct.

Hispanic
Pct.

NonWhite
Pct.

Low/Mod
Income R/ECAP RCAA
TCAC
Opportunity
Areas
Urban
Displacement
Very
Low Low Moderate
Above
Moderate Total
Census Tract 6086 20% 62% 37% 0 0 High
Resource
Lower
Displacement
Risk
152 128 65 613 958
Census Tract 6087 12% 53% 31% 0 1 Highest
Resource
Lower
Displacement
Risk
249 168 101 267 785
Census Tract 6088 8% 44% 14% 0 1 Highest
Resource
Lower
Displacement
Risk
0 0 11 3 14
Census Tract 6089 9% 52% 39% 0 0 Highest
Resource
Lower
Displacement
Risk
0 0 0 0 0
Census Tract 6090 15% 51% 29% 0 1 Highest
Resource
Lower
Displacement
Risk
115 60 41 123 339
Census Tract 6091 31% 54% 34% 0 1 High
Resource
Lower
Displacement
Risk
0 16 0 87 103
436
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 48 Figure C-2. Belmont Census Tract Map
437
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 49 Supportive Citywide Spatial Analysis
The following series of maps provide the location of proposed Belmont RHNA sites overlaid on demographic and fair housing data provided in HCD’s AFFH data viewer.

Hispanic Population
Figure C-3 shows proposed RHNA sites overlaid with the percentage of the population that identifies as Hispanic for Census Block Groups in the City. Two block groups have higher than 20% of the population identified as Hispanic. There are only a small handful of proposed RHNA sites within the block group just north of Ralston Avenue within Census Tract 6087. Overall, the City of Belmont (12%) has a substantially smaller Hispanic population compared to San Mateo County as a whole (24%).

Non-White Population
Figure C-4 shows proposed RHNA sites overlaid with the share of the population that identifies as non-White by Census Tract in the City of Belmont. All Census Tracts within the City have between 44% and 62% of the population non-White. Census Tract 6086 located east of CA-82 has the highest share of non-White residents (62% of the population). Fortyseven percent (47%) of site inventory units are proposed in this Census Tract. This proportion of non-White residents is similar to San Mateo County as a whole (61%). The second highest share of non-White residents by Census Tract is in Tract 6091 (54%) which is the location of 5% of proposed site inventory units. Overall, Belmont has a lower share of non-White population when compared to San Mateo County with 56% of the population being non-Hispanic White in Belmont compared to 61% in the county.

Low- and Moderate-Income
Figure C-5 shows proposed RHNA sites overlaid with the share of households that are lowand moderate-income in the City of Belmont by Census Tract. Census Tract 6089 has the highest proportion of LMI households (39%) but has no proposed LMI site inventory units.

Census Tract 6086 has the second highest proportion of LMI households compared to other Census Tracts in the City with 37% LMI households. This proportion of LMI households is similar to the income distribution of San Mateo County as a while (40% LMI households).

Census Tract 6086 is the location of 44% of the proposed site inventory units and is predominantly commercial uses along CA-82 and Highway 101. There are several lower density single-family neighborhoods and large apartment communities within the Tract. St.

Mark Catholic Church, Nesbit Elementary School, various hotels, and a Caltrain Station are also located within this Census Tract.

The lowest proportion of LMI households is within Census Tract 6088 (14%) which is the location of >1% of proposed site inventory units scattered throughout the residential neighborhoods.
438
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 50 Figure C-3. Belmont Proposed RHNA Sites, Percent Hispanic, 2019 439
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 51 Figure C-4. Belmont Proposed RHNA Sites, Percent Non-White, 2019 440
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 52 Figure C-5. Belmont Proposed RHNA Sites, Percent Low- and ModerateIncome, 2019 441
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 53 Racially or Ethnically Concentrated Areas of Poverty (R/ECAP) As shown in Figure C-6, there are no R/ECAPs in the City of Belmont.

Racially Concentrated Areas of Affluence (RCAA)
Figure C-7 shows RCAAs in Belmont. As shown in the figure, the majority of the City is an RCAA except for Census Tracts 6086 and 6089. Nearly half (44%) of proposed site inventory units are located within RCAAs and further integrate the City of Belmont racially and economically.

TCAC Areas of Opportunity
Figure C-8 shows the opportunity area designation for each Census Tract in the City based on TCAC’s resource areas. The majority of the City of Belmont is a highest resource area except for Census Tracts 6086 and 6091. All RHNA sites are located in areas that are designated as high or highest resource. Therefore, the proposed site locations will provide access to opportunity to LMI households living in the region.

Urban Displacement
Figure C-9 shows the Urban Displacement typology assigned to each Census Tract in the City of Belmont. Most Census Tracts are considered stable moderate/mixed-income. These Census Tracts (6086, 6089, 6090, and 6091) contain 64% of proposed site inventory units.

These areas are already mixed-income areas. Therefore, the introduction of additional mixed-income units will help maintain the area’s existing income diversity.

Census Tract 6087 is classified as at-risk of becoming exclusive. Thirty-six percent (36%) of proposed site inventory units are located in this Census Tract and should help stabilize the area and prevent displacement. Finally, >1% of units in Tract 6088 which is classified as stable/advanced exclusive meaning that low- and moderate-income households have minimal access to live in these neighborhoods. The introduction of 14 units in these neighborhoods will further integrate the City.
442
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 54 Figure C-6. Belmont Proposed RHNA Sites, R/ECAPs, 2023
443
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 55 Figure C-7. Belmont Proposed RHNA Sites, RCAAs, 2019
444
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 56 Figure C-8. Belmont Proposed RHNA Sites, TCAC Areas of Opportunity, 2023
445
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 57 Figure C-9. Belmont Proposed RHNA Sites, Urban Displacement, 2023 446
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 58 Segregation and Integration
Belmont has proportionately fewer residents of color than the county and the Bay Area overall, although the City’s Asian population is on par with the proportion in the County and Bay Area. Fifty-four (54%) percent of Belmont residents are White, non-Hispanic versus 39% of the County and the Bay Area overall. Twelve percent (12%) of Belmont residents are Hispanic, compared to 24% in the County and the Bay Area overall.

The City’s proposed distribution of site inventory units does not generally concentrate LMI units in areas with high non-White or Hispanic populations. However, the 345 LMI units proposed in Tract 6086 may contribute to concentrating non-White and LMI households in the downtown area east of CA-82 if non-White or Hispanic residents disproportionately occupy the new units. This area differs from more typically concentrated areas in that it does not have high rates of poverty and is not an R/ECAP. In fact, HCD indicators show this area as a high resource area and close to public transportation. Additionally, providing units in this Census Tract for low- and moderate-income households would help stabilize households in the area and prevent further displacement of renter households.

The share of non-White households in this Census Tract is on par with the Countywide distribution—62% and 61% respectively. Similarly, the proportion of LMI households in this Tract is 37% compared to 40% in San Mateo County. Furthermore, the mapping completed by the state to support this study suggests that these moderatelyconcentrated neighborhoods offer similar access to jobs, good schools, and positive environmental outcomes as other parts of Belmont.

A supplemental analysis of existing LMI households by Tract and proposed site inventory unit allocations shows that Tracts 6086 and 6091 would experience a slight decrease in LMI households as a proportion of total households by addition of the units; this is because the addition of the affordable units is balanced by the addition of market rate units.

Conversely, Tracts 6087 and 6090 would experience an increase in the proportion of LMI households of six and seven percentage points, respectively. This increase in LMI households brings Tracts 6087 and 6090 to 37% and 36% LMI households, respectively.

This proportion of LMI households is less than the countywide share of 40% in San Mateo County.

Racially and Ethnically Concentrated Areas of Poverty and Affluence
None of the proposed units are within an R/ECAP. Racially Concentrated Areas of Affluence (RCAAs) are defined by HUD as communities with a large proportion of affluent and nonHispanic White residents. The majority of Belmont is within an RCAA. Forty-four percent (44%) of site inventory units are within an RCAA, which provide access to opportunity for residents of affordable housing and reduce existing segregation patterns. These sites 447
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 59 provide increased housing opportunities for all incomes and would not exacerbate concentrations of race and affluence.

Disparities in Access to Opportunity
The majority of the City of Belmont is a highest resource area except for Census Tracts 6086 and 6091. More than half (52%) of proposed site inventory units are in highest resources areas and 48% are in high resource areas. Because Belmont is classified as a high resource area throughout and lacks major racial and ethnic concentrations, the distribution of residents among high resource areas matches the city’s racial and ethnic distribution. Additionally, all site inventory units will provide access to high resource areas for LMI households living in the region.

Disproportionate Housing Needs
Racial and ethnic minority populations in Belmont—with the exception of Asians—are more likely to be living in poverty and be housing cost burdened compared to the nonHispanic White population. They are also slightly more likely to be denied a mortgage loan.

Hispanic households have much higher rates of cost burden—48% are burdened and 25% severely burdened—and one in ten lives in an overcrowded household. The locations of the proposed RHNA sites do not directly exacerbate the segregation of any of these racial or ethnic groups because the city has a lower proportion of non-White households compared to San Mateo County as a whole.
448
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 60 SECTION VI. Contributing Factors and Fair
Housing Action Plan
Note that the Fair Housing Action Plan is also included in Chapter 3: Affirmatively Furthering Fair Housing Summary, to ensure implementation and ongoing monitoring. 449
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 61 TABLE 3-1: FAIR HOUSING ACTION PLAN
Fair Housing Issue Contributing Factors
Priority
Level
Meaningful Program Actions (from
Chapter 7, Goals, Policies, and Programs) Targets and Timeline Lack of fair housing
complaints filed.

Lack of access to
information about fair
housing rights. Limited
knowledge of fair
housing by residents.

High  H5.1: Update Website to Improve Access to Fair
Housing Information and Housing Services.
 Complete best practices review by Q1 2025.
 Complete website update by Q2 2025, update
quarterly thereafter.

Very high rates of cost
burden for <50% AMI
households and Black and
Hispanic households; high
rates of overcrowding
among Asian households.

Lack of affordable
housing citywide; low
housing production.

High  H5.2: Coordinate with other jurisdictions and
agencies in the County to advance AFFH goals
 Attend regular meetings with 21 Elements, 21
Directors and Housing Managers group.
 Collaborate with peer jurisdictions to
implement Housing Element Programs that
would benefit from efficiencies of scale.
 H5.3: Modify the Inclusionary Housing Program.  Complete feasibility analysis by Q4 2025; Implement redesigned program by Q1 2026.
 H5.4: Work with Housing Developers to
Affirmatively Market Housing to Households
with Disproportionate Housing Needs.
 Establish list of service providers by Q4 2024
and update annually thereafter.
 Ongoing as projects are processed, review
developer marketing plans to ensure
affirmative marketing is included.
 H5.6: Expand Tenant Protections  In Q4 2025, draft extended tenant protections provisions and research policy provisions for
substantial remodel exemptions and right of
return policies.
 Bring recommended language to City Council in
Q1 2026. Conduct proactive outreach to
tenants and tenant groups bi-annually.
 H5.7: Continue Financial Support of Existing
Home Sharing Program.
 City will grant funding as part of annual budget
process.
 Meet with HIP Housing within one year of
Housing Element Certification and annually
thereafter.
450
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 62 Fair Housing Issue Contributing Factors
Priority
Level
Meaningful Program Actions (from
Chapter 7, Goals, Policies, and Programs) Targets and Timeline  H5.8: Facilitate Development of Housing on
Institutional Properties.
 Reach out to each religious institution site
owner or operator within one year following
Housing Element certification and annually
thereafter.
 Provide mailed notifications to religious
institutions within six months of the adoption of
any new State legislation that reduces barriers
to development of religious institution sites.
 Reach out to each private school site owner or
operator within one year following Housing
Element certification and annually thereafter.
 H5.9: Amend Zoning Code to Facilitate
Production of ADUs and SB9 units.
 Complete zoning ordinance amendments and
establish policies and procedures to facilitate
these types of projects within one year
following Housing Element Certification.
 H5.10: Provide Financial Support for ADUs that
Serve Lower-Income Households.
 Participate in Countywide process in 2024.
 Establish a grant or loan program by Q4 2025.
 H5.11: Conduct Outreach to Encourage ADU
and SB9 Unit Production.
 Conduct analysis and outreach related to units
on sloped sites in Q2 2025.
 Join ADU Resource Center and launch online
plans gallery in Q3 2024.
 Create new outreach materials in Q1 2025.
 Conduct outreach to all ADU/JADU/SB9 owners
within 9 months of Housing Element
Certification and annually thereafter.
 H5.12: Create an AFFH Monitoring Program.  Create a list and map of existing ADUs, JADUs and SB9 units within six months of Housing
Element adoption.
 Participate in regional process to establish an
ADU monitoring program on timing they set
forward.
 If ADU production does not meet target,
consider additional efforts such as reducing
process and permitting fees to incentivize
production in 2027.
451
ROOT POLICY RESEARCH BELMONT FAIR HOUSING ASSESSMENT, PAGE 63 Fair Housing Issue Contributing Factors
Priority
Level
Meaningful Program Actions (from
Chapter 7, Goals, Policies, and Programs) Targets and Timeline Persons with disabilities and
persons of color are most
likely to file fair housing
complaints with HUD.

Lack of accessible
affordable units;
housing
discrimination.

Medium  H5.5: Provide Fair Housing Training for
Landlords and Tenants.
 Ongoing annual check in with Project Sentinel.
 Provide training in 2025 and every two years
thereafter.

Source: City of Belmont, 2024.
452
ROOT
POLICY RESEARCHBELMONT FAIR HOUSING ASSESSMENT,PAGE 64
453
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 1 AFFH Attachment C.2.

Community Engagement Resident Survey
This section reports the findings from the resident survey conducted of San Mateo County residents to support the AFFH analysis of Housing Elements. It explores residents’ housing, affordability, and neighborhood challenges and experiences with displacement and housing discrimination. The survey also asks about residents’ access to economic opportunity, captured through residents’ reported challenges with transportation, employment, and K-12 education. The survey was offered in both English and Spanish.

The resident survey was available online, in both Spanish and English, in a format accessible to screen readers, and promoted through jurisdictional communications and social media and through partner networks. A total of 2,382 residents participated.

The survey instrument included questions about residents’ current housing situation, housing, neighborhood and affordability challenges, healthy neighborhood indicators, access to opportunity, and experience with displacement and housing discrimination.

Explanation of terms. Throughout this section, several terms are used that require explanation.
 “Precariously housed” includes residents who are currently homeless or living in transitional or temporary/emergency housing, as well as residents who live with friends or family but are not themselves on the lease or property title. These residents may (or may not) make financial contributions to pay housing costs or contribute to the household in exchange for housing (e.g., childcare, healthcare services).  “Disability” indicates that the respondent or a member of the respondent’s household has a disability of some type—physical, mental, intellectual, developmental.  “Single parent” are respondents living with their children only or with their children and other adults but not a spouse/partner.
 “Tenure” in the housing industry means rentership or ownership.  “Large households” are considered those with five or more persons residing in a respective household.
 “Seriously Looked for Housing” includes touring or searching for homes or apartments, putting in applications or pursuing mortgage financing. 454
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 2 Sampling note. The survey respondents do not represent a random sample of the county or jurisdictions’ population. A true random sample is a sample in which each individual in the population has an equal chance of being selected for the survey. The selfselected nature of the survey prevents the collection of a true random sample. Important insights and themes can still be gained from the survey results, however, with an understanding of the differences among resident groups and between jurisdictions and the county overall. Overall, the data provide a rich source of information about the county’s households and their experience with housing choice and access to opportunity in the communities where they live.

Jurisdiction-level data are reported for cities with 50 responses or more. Response by jurisdiction and demographics are shown in the figure below. Overall, the survey received a very strong response from typically underrepresented residents including: people of color, renters, precariously housed residents, very low income households, households with children, large households, single parents, and residents with disabilities. 455
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 3 Figure 1.

Resident Survey Sample Sizes by Jurisdictions and Selected Characteristics Note: Numbers do not aggregate either due to multiple responses or that respondents chose not to provide a response to all demographic and socioeconomic questions.

Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey.

Belmont
Total Responses 2,382 89 82 173 130 53 148 63 59 55 84 163 99 175 832 Race/Ethnicity
African American 134 5 7 4 9 8 10 6 4 4 5 14 4 17 15
Hispanic 397 7 9 14 26 27 13 8 1 8 12 59 13 31 149
Asian 500 18 9 26 43 6 32 6 8 13 14 11 19 23 249
Other Race 149 7 10 6 8 3 14 3 3 3 3 9 7 13 47
Non-Hispanic White 757 41 35 89 27 4 44 27 27 15 35 54 36 58 195 Tenure
Homeowner 1,088 39 51 96 39 9 89 26 46 18 42 37 48 58 409 Renter 1,029 40 30 65 67 36 43 28 7 33 38 105 41 88 324 Precariously Housed 309 10 8 12 26 12 17 14 5 7 13 23 16 29 87 Income
Less than $25,000 282 14 11 12 21 15 12 11 5 6 7 40 11 29 61 $25,000-$49,999 265 13 9 10 22 9 8 6 3 6 7 28 5 20 97
$50,000-$99,999 517 10 14 38 43 10 26 11 3 10 17 37 22 40 206 Above $100,000 721 38 24 69 16 8 64 12 30 14 32 31 40 40 251 Household Characteristics
Children under 18 840 38 24 53 50 26 44 17 18 20 29 61 37 64 287 Large households 284 5 7 11 20 18 8 3 5 7 8 20 13 15 133 Single Parent 240 14 8 15 19 11 12 9 3 7 7 30 9 21 49
Disability 711 28 25 41 38 22 40 22 13 17 29 62 34 65 210 Older Adults (age 65+) 736 25 27 66 37 11 54 25 25 18 33 44 32 37 248 San
Mateo
South San
Francisco
Half
Moon
Bay Hillsborough Milbrae Pacifica
Redwood
City
San
Bruno
Foster
County Brisbane Burlingame City
Daly
City
East
Palo
Alto
456
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 4 Primary Findings
The survey data present a unique picture of the housing choices, challenges, needs, and access to economic opportunity of San Mateo County residents.

Top level findings from residents’ perspectives and experiences:
 The limited supply of housing that accommodates voucher holders presents several challenges. Specifically,
 Eight out of 10 voucher holders represented by the survey find a landlord that accepts a housing voucher to be “difficult” or “very difficult.”  According to the survey data, vouchers not being enough to cover the places residents want to live is a top impediment for residents who want to move in San Mateo County, as well as for African American, Asian, and Hispanic residents, households with children under 18, single parents, older adults, households with a member experiencing a disability, and several jurisdictions.
 Low income is a barrier to accessing housing. The impacts are highest for precariously housed respondents. large households, Hispanic households, and residents in Daly City and Redwood City.
 Nearly 4 in 10 respondents who looked for housing experienced denial of housing. African American/Black respondents, single parent households, precariously housed respondents, and households with income below $50,000 reported the highest denial rates.
 1 in 5 residents have been displaced from their home in the past five years. One of the main reasons cited for displacement was the rent increased more than I could pay. African American households, single parents, households that make less than $25,000, and precariously housed respondents reported the highest rates of displacement.
 For households with children that were displaced in the past five years, 60% of children in those households have changed schools. The most common outcomes identified by households with children who have changed schools include school is more challenging, they feel less safe at the new school, and they are in a worse school.
 Nearly 1 in 5 residents reported they have experienced discrimination in the past five years. African American, single parent, and precariously housed respondents reported the highest rates of discrimination. The most common actions 457
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 5 in response to discrimination cited by survey respondents were Nothing/I wasn’t sure what to do and Moved/found another place to live.
 Of respondents reporting a disability, about 25% report that their current housing situation does not meet their accessibility needs. The three top greatest housing needs identified by respondents included installation of grab bars in bathroom or bench in shower, supportive services to help maintain housing, and ramps.
 On average, respondents are fairly satisfied with their transportation situation. Groups with the highest proportion of respondents somewhat or not at all satisfied with their transportation options included African American, single parents, precariously housed, and Brisbane respondents.

There are some housing, affordability, and neighborhood challenges unique to specific resident groups. These include:
 Would like to move but can’t afford it—Most likely to be a challenge for Daly City, East Palo Alto, and Redwood City respondents, as well as Hispanic, renter, precariously housed, households making less than $50,000, and large household respondents.
 My house or apartment isn’t big enough for my family—Most likely to be a challenge for East Palo Alto respondents, as well as Hispanic households, large and single parent households, and households with children under 18.  I’m often late on my rent payments—Most likely to be a challenge for East Palo Alto and renter respondents, as well as households that make less than $25,000.  I can’t keep up with my utility payments—Most likely to be a challenge for East Palo Alto, Daly City, and San Mateo respondents, as well as African American and Hispanic respondents, single parent households, households with children under 18, and households that make less than $50,000.
 Bus/rail does not go where I need to go or does not operate during the times I need— Most likely to be a challenge for African American, precariously housed, single parent households, Brisbane and Pacifica respondents.  Schools in my neighborhood are poor quality—Most likely to be a challenge for East Palo Alto, Redwood City, San Bruno and South San Francisco respondents, as well as Hispanic respondents and households with children under 18. 458
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 6 Resident Survey Findings
Of survey respondents who reported their race or ethnicity, nearly 40% of survey respondents identified as non-Hispanic White, followed by Asian (26%), Hispanic (20%), African American (7%), and Other Minority (8%) residents (Figure 2). Overall, 45% of the survey respondents were homeowners, followed by 42% of renter respondents. Thirteen percent of respondents reported they are precariously housed (Figure 3). Four in ten respondents reported having household income greater than $100,000. Nearly 30% of respondents reported a household income between $50,000-99,999, followed by 15% of respondents who made between $25,000-49,999 and 16% of respondents making less than $25,000 (Figure 4).

The survey analysis also included selected demographic characteristics of respondents, including those with children under the age of 18 residing in their household, adults over the age of 65, respondents whose household includes a member experiencing a disability, those who live in large households, and single parents. Thirty five percent of respondents indicated they had children in their household, while 31% indicated they were older adults.

Thirty percent of respondents indicated they or a member of their household experienced a disability, 12% of respondents reported having large households, and 10% were single parents (Figure 5).
459
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 7 Figure 2.

Survey Respondents
by Race/Ethnicity
Note:
n=1,937; 535 respondents did not
indicate their race or ethnicity.

Source:

Root Policy Research from the 2021-
2022 21 Elements AFFH Resident
Survey.

Figure 3.

Survey Respondents
by Tenure
Note:
n=2,426.

Source:

Root Policy Research from the 2021-
2022 21 Elements AFFH Resident
Survey.

Figure 4.

Survey Respondents
by Income
Note:
n=1,785.

Source:

Root Policy Research from the 2021-
2022 21 Elements AFFH Resident
Survey.
460
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 8 Figure 5.

Survey Respondents
by Selected
Household
Characteristics
Note:

Denominator is total responses to the
survey (n=2,382)
Source:

Root Policy Research from the 2021-
2022 21 Elements AFFH Resident
Survey.

Housing, Neighborhood and Affordability Challenges
Housing challenges: overall. Survey respondents were asked to select the housing challenges they currently experience from a list of 34 different housing, neighborhood, and affordability challenges. Figures 6a through 8c present the top 10 housing and neighborhood challenges and top 5 affordability challenges experienced by jurisdiction, race/ethnicity, tenure, income, and selected household characteristics.

These responses allow a way to compare the jurisdictions to the county for housing challenges for which other types of data do not exist. In this analysis, “above the county”—shaded in light red or pink—is defined as the proportion of responses that is 25% higher than the overall county proportion. “Below the county”—shown in light blue—occurs when the proportion of responses is 25% lower than the overall county proportion.

As shown in Figure 6a, residents in Redwood City and East Palo Alto experience several housing challenges at a higher rate than the county overall. Conversely, Foster City and Hillsborough residents experience nearly all identified housing challenges at a lower rate than the county.

Notable trends in housing, neighborhood, and affordability challenges by geographic area include:
 Residents in Daly City, East Palo Alto, and Redwood City are less likely to move due to the lack of available affordable housing options.
 East Palo Alto, Redwood City, and San Mateo residents report living in housing that is too small for their families.
 Millbrae, Belmont, and Redwood City residents report being more reticent to request a repair to their unit in fear that their landlord will raise their rent or evict them.  Nearly 1 in 5 Pacifica survey respondents report that their home or apartment is in bad condition.
461
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 9  Brisbane and East Palo Alto residents are more likely to experience a landlord refusing to make repairs to their unit.
 Residents in Daly City and Millbrae are more likely to report that they don’t feel safe in their neighborhood or building.
 Half Moon Bay and East Palo Alto respondents expressed the greatest need for assistance in taking care of themselves or their home.

When compared to the county overall, the most common areas where respondents’ needs were higher than the county overall were:
 Overall, half of the jurisdictions’ respondents reported I need help taking care of myself/my home and can’t find or afford to hire someone at a higher rate than the county.  Over 40% of jurisdictions’ respondents reported a higher rate than the county for the following housing challenge: My home/apartment is in bad condition.  Nearly 40% of jurisdictions’ respondents reported a higher rate than the county for the following housing challenges: My landlord refuses to make repairs despite my requests and I don’t feel safe in my neighborhood/building.
462
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 10 Figure 6a.

Top 10 Housing Challenges Experienced by Jurisdiction
Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. 25% Above County average
25% Below County average
2,159 82 73 158 118 49 135 59 50 53 79 151 93 163 738
31% 27% 12% 20% 51% 41% 16% 25% 4% 32% 28% 43% 30% 38% 35% 20% 22% 11% 14% 24% 35% 10% 12% 4% 21% 11% 26% 20% 26% 21% 14% 21% 10% 13% 17% 14% 9% 10% 2% 23% 15% 20% 11% 15% 13% 11% 15% 14% 9% 15% 12% 3% 7% 0% 11% 18% 14% 5% 15% 10%
6% 6% 14% 3% 5% 12% 4% 5% 2% 2% 9% 9% 5% 10% 5%
6% 6% 5% 4% 8% 4% 5% 8% 6% 6% 3% 8% 4% 7% 5%
6% 7% 5% 5% 13% 8% 0% 7% 6% 11% 10% 8% 3% 6% 3%
5% 2% 7% 7% 7% 10% 2% 14% 2% 8% 9% 3% 4% 8% 4%
5% 10% 5% 4% 3% 16% 2% 3% 4% 6% 9% 11% 6% 4% 3%
4% 2% 5% 1% 3% 8% 11% 3% 2% 4% 5% 3% 3% 4% 2%
42% 37% 48% 50% 20% 33% 55% 44% 76% 36% 47% 28% 45% 35% 46% I have bed bugs/insects or rodent
infestation
The HOA in my neighborhood won't
let me make changes to my house
or property
None of the above
I need help taking care of
myself/my home and can't find or
afford to hire someone
South San
Milbrae Francisco
Housing or Neighborhood
Condition
Valid cases
Half
Moon
Bay Hillsborough Pacifica
Redwood
City
San
Bruno
San
County Brisbane Burlingame Mateo
I would like to move but I can't
afford anything that is
available/income too low
My house or apartment isn't big
enough for my family
Daly
City
East
Palo
Alto
Foster
City
I live too far from family/
friends/my community
I don't feel safe in my building/
neighborhood
I worry that if I request a repair it
will result in a rent increase or
eviction
My home/apartment is in bad
condition
My landlord refuses to make repairs
despite my requests
Belmont
463
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 11 The following two figures segment the answers by:
 Housing affordability challenges only; and
 Neighborhood challenges only.

Housing affordability challenges. As shown in Figure 6b, residents in San Mateo, Daly City, East Palo Alto, and Pacifica experience affordability challenges at a higher rate than the county overall. Conversely, Belmont, Hillsborough, Burlingame, and South San Francisco residents experience affordability challenges at a lower rate than the county.

The most significant geographic variations occur in:
 San Mateo city residents experience all five affordability challenges at a greater rate than the county overall. In addition to being less likely to pay utility bills or rent on time, San Mateo residents are more than twice as likely than the average county respondent to have bad credit or a history of eviction/foreclosure that impacts their ability to rent.  East Palo Alto, San Mateo, and Daly City residents are most likely to experience difficulty paying utility bills.
 Residents in East Palo Alto and Redwood City are most likely to be late on their rent payments.
 Millbrae residents experience the greatest difficultly paying their property taxes among jurisdictions in San Mateo County.
 Respondents from Brisbane, Half Moon Bay, and Pacifica are also more likely to have trouble keeping up with property taxes.
 Daly City, City of San Mateo, and Redwood City respondents are more likely to have bad credit or an eviction history impacting their ability to rent.

Overall, over a third of jurisdictions’ respondents experienced the following affordability challenges at a higher rate than the county: I can’t keep up with my property taxes and I have bad credit/history of evictions/foreclosure and cannot find a place to rent. .
464
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 12 Figure 6b.

Top 5 Affordability Challenges Experienced by Jurisdiction Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. 25% Above County average
25% Below County average
2,130 83 73 157 115 51 134 58 50 50 77 147 93 160 728
10% 6% 5% 6% 15% 16% 5% 12% 4% 12% 8% 12% 9% 15% 9%
8% 6% 5% 6% 10% 20% 3% 7% 2% 8% 4% 12% 4% 11% 7%
6% 2% 10% 4% 3% 2% 8% 10% 0% 16% 10% 3% 5% 9% 5%
4% 1% 4% 2% 13% 6% 0% 0% 2% 0% 5% 8% 4% 10% 2%
4% 2% 7% 3% 3% 2% 7% 3% 4% 4% 5% 3% 3% 6% 2%
73% 73% 68% 80% 65% 59% 78% 66% 88% 64% 71% 70% 77% 63% 80% I have bad credit/history of
evictions/foreclosure and cannot
find a place to rent
I have Section 8 and I am worried my
landlord will raise my rent higher
than my voucher payment
None of the above
Affordability Challenges
San
Mateo
Foster
Belmont City
South San
Francisco
Valid cases
I can't keep up with my utilities
I'm often late on my rent payments
I can't keep up with my property
taxes
Half
Moon
Bay Hillsborough Milbrae Pacifica
Redwood
City
San
County Brisbane Burlingame Bruno
Daly
City
East
Palo
Alto
465
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 13 Neighborhood challenges. As shown in Figure 6c, residents in East Palo Alto, Brisbane, Daly City, and Pacifica experience neighborhood challenges at a higher rate than the county.

Burlingame and Foster City both experience neighborhood challenges at a lower rate than the county.

Hillsborough and Belmont residents report divergent experiences related to neighborhood challenges — respondents identified more challenges around neighborhood infrastructure and access to transit but fewer challenges around school quality and job opportunities.

There are a handful of jurisdictions who experience specific neighborhood challenges at a disproportionate rate compared to the county.  For instance, East Palo Alto and Belmont residents experience neighborhood infrastructure issues (e.g., bad sidewalks, no lighting) more acutely than county residents overall.  Brisbane residents experience transportation challenges in their neighborhoods.  East Palo Alto, Redwood City, San Bruno, and South San Francisco experience challenges with school quality in their neighborhoods.
 Residents in Brisbane, Hillsborough, Pacifica, Belmont, and Half Moon Bay report the highest rates of difficulty accessing public transit.
 Daly City, Millbrae, San Mateo, and East Palo Alto residents were more likely to identify the lack of job opportunities available in their neighborhoods.

Over a third of jurisdictions’ respondents experienced the following neighborhood challenges at a higher rate than the county: I can’t get to public transit/bus/light rail easily or safely. 466
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 14 Figure 6c.

Top 5 Neighborhood Challenges Experienced by Jurisdiction Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. 25% Above County average
25% Below County average
2,079 80 72 153 116 48 130 56 53 46 75 145 91 151 712
17% 31% 18% 13% 25% 40% 4% 18% 23% 20% 15% 21% 14% 12% 16% 15% 6% 18% 3% 17% 25% 4% 14% 2% 7% 13% 20% 20% 15% 20%
15% 14% 24% 8% 14% 15% 21% 18% 9% 15% 24% 17% 14% 17% 10% 14% 19% 29% 7% 9% 10% 14% 18% 25% 17% 21% 12% 13% 15% 10% 12% 9% 8% 7% 20% 17% 8% 14% 0% 20% 13% 11% 11% 18% 12%
50% 41% 28% 69% 45% 33% 62% 46% 57% 50% 52% 41% 52% 52% 55% Bus/rail does not go where I need to
go or does not operate during the
times I need
I can't get to public transit/bus/light
rail easily or safely
There are not enough job
opportunities in the area
None of the above
San
Mateo
Foster
Belmont City
South San
Neighborhood Challenges Francisco
Valid cases
My neighborhood does not have good
sidewalks, walking areas, and/or
lighting
Schools in my neighborhood are poor
quality
Half
Moon
Bay Hillsborough Milbrae Pacifica
Redwood
City
San
County Brisbane Burlingame Bruno
Daly
City
East
Palo
Alto
467
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 15 Differences in needs by race and ethnicity and housing tenure. As shown in Figure 7a, and compared to the county overall:
 African American, Hispanic, and Other Race respondents, as well as Renters and those who are precariously housed experience several housing challenges at a higher rate than the county overall.
 Conversely, non-Hispanic White residents and homeowners are less likely to experience housing challenges.

Specifically,
 Black or African American residents are more than three times as likely to have a landlord not make a repair to their unit after a request compared to county residents overall.

Renters, Hispanic, Other Race, and Precariously housed residents are also more likely to experience this challenge.
 African American, Asian, Hispanic, Renter, and Precariously Housed households are more likely to experience bed bugs or rodent infestation in their homes.  African American, Other Race, Renter, and Precariously Housed households are also more likely to live further away from family, friends, and their community.  African Americans are three times more likely than the average county respondent to be told by their HOA they cannot make changes to their house or property. Asian households are twice as likely to experience this challenge.
 Renter, Hispanic, and Other Race respondents are more likely to worry that if they request a repair it will result in a rent increase or eviction and to report that their homes are in bad condition.
468
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 16 Figure 7a.

Top 10 Housing Challenges Experienced by Race/Ethnicity and Tenure Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. 25% Above County average
25% Below County average
2,159 132 489 392 144 734 986 974 301
31% 30% 32% 50% 31% 20% 7% 48% 56%
20% 16% 21% 35% 22% 11% 12% 29% 18%
14% 17% 13% 23% 19% 11% 2% 28% 13%
11% 12% 9% 16% 17% 10% 6% 17% 10%
6% 20% 7% 10% 10% 5% 2% 13% 10%
6% 15% 6% 6% 13% 6% 5% 8% 9%
6% 13% 6% 6% 9% 5% 4% 8% 7%
5% 14% 7% 5% 6% 5% 5% 6% 11%
5% 14% 8% 7% 5% 4% 4% 9% 9%
4% 14% 8% 4% 3% 3% 5% 3% 7%
42% 18% 37% 24% 38% 58% 68% 21% 13%
I need help taking care of myself/my home and can't find or afford to hire someone
I have bed bugs/insects or rodent infestation
The HOA in my neighborhood won't let me make changes
to my house or property
County
African
American Asian Hispanic
I would like to move but I can't afford anything that is available/income too low
Homeowner Renter
Precariously
Housing or Neighborhood Condition Housed
Valid cases
Other
Race
Non-Hispanic
White
None of the above
My house or apartment isn't big enough for my family
I worry that if I request a repair it will result in a rent increase or eviction
My home/apartment is in bad condition
My landlord refuses to make repairs despite my requests I live too far from family/ friends/my community
I don't feel safe in my building/ neighborhood
469
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 17 The above trends are similar for the most acute housing affordability challenges. As shown in Figure 7b, African American and Hispanic households, as well as renters and those precariously housed, experience affordability challenges at a higher rate than the county overall. Non-Hispanic White residents and homeowners experience these same challenges at a lower rate than the county.
 African American residents experience all five affordability challenges at a greater rate than the county overall.
 In addition to being more likely to not pay utility bills or rent on time, African American residents are more than four times as likely than the average county respondent to have a Section 8 voucher and worry that their landlord will raise their rent more than the voucher payment.
 Along with African American residents, Hispanic households, renters, and precariously housed households are most likely to experience difficulty paying utility bills, as well as have bad credit or eviction/foreclosure history impacting their ability to find a place to rent.  These groups, with the exception of those precariously housed, are also more likely to be late on their rent payments.
470
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 18 Figure 7b.

Top 5 Affordability Challenges Experienced by Race/Ethnicity and Tenure Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. 25% Above County average
25% Below County average
2,130 132 487 391 146 739 983 953 293
10% 22% 11% 17% 14% 5% 5% 15% 15%
8% 13% 6% 12% 12% 4% 1% 15% 8%
6% 16% 8% 4% 5% 7% 9% 5% 14%
4% 5% 3% 8% 4% 2% 1% 6% 11%
4% 18% 5% 6% 7% 2% 2% 7% 8%
None of the above 73% 32% 70% 63% 64% 83% 84% 61% 54%
County
African
American Asian Hispanic
Valid cases
I can't keep up with my utilities
I'm often late on my rent payments
I can't keep up with my property taxes
I have bad credit/history of evictions/foreclosure
and cannot find a place to rent
I have Section 8 and I am worried my landlord will
raise my rent higher than my voucher payment
Non-Hispanic
White Homeowner Renter
Precariously
Affordability Challenges Housed
Other
Race
471
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 19 As shown in Figure 7c, African American and precariously housed residents experience neighborhood challenges at a higher rate than the county. These two groups experience neighborhood issues related to transportation more acutely than county residents overall. In addition to Other Race respondents, they are also more likely to identify the lack of job opportunities in their respective neighborhoods.

Additionally, Hispanic residents are more likely to live in neighborhoods with poor performing schools than the average county respondent. Homeowners are also more likely to report that they cannot access public transit easily or safely.
472
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 20 Figure 7c.

Top 5 Neighborhood Challenges Experienced by Race/Ethnicity and Tenure Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. 25% Above County average
25% Below County average
2,079 133 486 389 146 737 975 918 284
17% 14% 17% 19% 16% 18% 18% 15% 18%
15% 13% 18% 20% 17% 13% 18% 13% 13%
15% 33% 16% 13% 17% 17% 17% 14% 24%
14% 24% 15% 11% 16% 16% 18% 11% 19%
12% 22% 14% 12% 19% 9% 9% 15% 20%
50% 23% 46% 48% 45% 53% 49% 51% 36%
My neighborhood does not have good sidewalks, walking
areas, and/or lighting
County
African
American Asian Hispanic Homeowner Renter
Precariously
Neighborhood Challenges Housed
Valid cases
Other
Race
NonHispanic
White
Schools in my neighborhood are poor quality
Bus/rail does not go where I need to go or does not
operate during the times I need
I can't get to public transit/bus/light rail easily or safely There are not enough job opportunities in the area
None of the above
473
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 21 Differences in needs by household status. As shown in Figure 8a, single parents, households making less than $50,000, households with children under 18 and households with a member experiencing a disability are more likely to experience housing challenges.

Conversely, households making more than $100,000 experience nearly all specified housing challenges at a lower rate than the county.

Single parents experience all ten housing challenges at a greater rate than the county overall.

Households making less than $25,000 also experience every challenge at a higher rate, with the exception of I worry that if I request a repair it will result in a rent increase or eviction.

Households making less than $50,000, single parents, and households with children under 18 are more likely to experience the following challenges:
 My house or apartment isn’t big enough for my family;  My house or apartment is in bad condition;
 My landlord refuses to make repairs despite my request;  I live too far from family/friends/my community;
 I don’t feel safe in my building/neighborhood;
 I need help taking care of myself/my home and can’t find or afford to hire someone; and  I have bed bugs/insects or rodent infestation.

Households with a member experiencing a disability are also more likely to experience landlords refusing their requests to make repairs, living further away from family/friends/community, and not being able to find or afford someone to help take care of themselves or their homes. These households are also more likely to experience bed bugs, insects, or rodent infestation, as well as HOA restrictions impacting their ability to make changes to their home or property.

Additionally, large households have the highest proportion of respondents among the selected groups that would like to move but can’t afford anything that is available. 474
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 22 Figure 8a.

Top 10 Housing Challenges Experienced by Income and Household Characteristics Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. 25% Above County average
25% Below County average
2,159 280 260 505 701 827 278 240 701 709
31% 47% 48% 37% 16% 35% 51% 40% 36% 25%
20% 25% 25% 23% 16% 34% 43% 32% 20% 13%
14% 16% 18% 19% 9% 19% 19% 28% 16% 11%
11% 15% 20% 12% 6% 15% 17% 17% 12% 9%
6% 13% 13% 8% 2% 9% 8% 14% 10% 6%
6% 9% 9% 6% 5% 10% 5% 10% 8% 6%
6% 9% 9% 6% 3% 8% 4% 10% 7% 5%
5% 9% 9% 5% 3% 7% 6% 12% 11% 6%
5% 10% 9% 5% 3% 9% 4% 15% 9% 6%
4% 7% 3% 4% 3% 7% 4% 11% 6% 5%
42% 21% 21% 37% 61% 28% 26% 12% 32% 49%
Above
Housing or Neighborhood Condition $100,000
Valid cases
I would like to move but I can't afford anything
that is available/income too low
My house or apartment isn't big enough for my
family
I worry that if I request a repair it will result in a
rent increase or eviction
My home/apartment is in bad condition
My landlord refuses to make repairs despite my
requests
None of the above
County
Less than
$25,000
$25,000-
$49,999
$50,000-
$99,999
I live too far from family/ friends/my community
I don't feel safe in my building/ neighborhood
I need help taking care of myself/my home and
can't find or afford to hire someone
I have bed bugs/insects or rodent infestation
The HOA in my neighborhood won't let me make
changes to my house or property
Children
under 18
Large
Households
Single
Parent Disability
Adults
(age 65+)
475
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 23 As shown in Figure 8b, households making less than $50,000, as well as large households, single parents, households with children under 18, and households with a member experience a disability, experience the most acute affordability challenges at a higher rate than the county overall. Households making more than $50,000 and adults over the age of 65 are less likely to experience affordability challenges.

Households making between $25,000-$50,000, single parents, and households with children under 18 experience all five affordability challenges at a greater rate than the average county respondent.

Of households experiencing major affordability issues, single parent households are most acutely impacted. These households are more than three times as likely to have a Section 8 voucher and fear their landlord will raise the rent impacting the viability of their voucher, more than twice as likely to miss utility payments and have bad credit/eviction or foreclosure history impacting their ability to rent, and twice as likely to have trouble keeping up with their property taxes.
476
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 24 Figure 8b.

Top 5 Affordability Challenges Experienced by Income and Household Characteristics Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. 25% Above County average
25% Below County average
2,130 276 260 509 703 830 279 239 699 716
10% 16% 16% 12% 3% 16% 14% 23% 15% 8%
8% 19% 16% 6% 1% 11% 12% 15% 11% 4%
6% 7% 9% 8% 5% 9% 4% 12% 8% 7%
4% 8% 7% 4% 1% 5% 6% 10% 6% 3%
4% 11% 6% 4% 1% 7% 3% 14% 8% 5%
73% 46% 56% 72% 90% 59% 70% 32% 59% 75%
Adults
(age 65+)
I have Section 8 and I am worried my landlord
will raise my rent higher than my voucher
payment
None of the above
County
Less than
$25,000
$25,000-
$49,999
$50,000-
Affordability Challenges $99,999
Valid cases
I can't keep up with my utilities
I'm often late on my rent payments
I can't keep up with my property taxes
I have bad credit/history of
evictions/foreclosure and cannot find a place
to rent
Above
$100,000
Children
under 18
Large
Households
Single
Parent Disability
477
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 25 As shown in Figure 8c, households with children under 18, as well as single parents, households with a member experiencing a disability, and households making less than $25,000 are more likely to experience neighborhood challenges. These households are most likely to report that the bus/rail does not go where I need to go or does not operate during the times I need. In addition to households that make between $25,000-$100,000, these groups are more likely to identify the lack of job opportunities in their respective neighborhoods.

Households with children under 18 are more likely to live in neighborhoods with poor quality schools. Large households are more likely to report issues with neighborhood infrastructure (e.g., bad sidewalks, poor lighting) and households with a member experiencing a disability are more likely to report they cannot access public transit easily or safely. 478
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 26 Figure 8c.

Top 5 Neighborhood Challenges Experienced by Income and Household Characteristics Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. 25% Above County average
25% Below County average
County
2,079 273 259 503 709 824 277 234 692 714
17% 17% 15% 18% 17% 19% 22% 16% 19% 14%
15% 17% 14% 11% 19% 24% 19% 17% 14% 9%
15% 19% 16% 15% 16% 19% 11% 28% 19% 16%
14% 15% 12% 14% 14% 15% 12% 15% 19% 17%
12% 21% 17% 16% 6% 17% 12% 19% 15% 11%
50% 40% 45% 51% 53% 38% 48% 31% 41% 53%
Above
Neighborhood Challenges $100,000
Valid cases
My neighborhood does not have good
sidewalks, walking areas, and/or lighting
Schools in my neighborhood are poor
quality
There are not enough job opportunities
in the area
None of the above
Less than
$25,000
$25,000-
$49,999
$50,000-
$99,999
Bus/rail does not go where I need to go or
does not operate during the times I need
I can't get to public transit/bus/light rail
easily or safely
Children
under 18
Large
Households
Single
Parent Disability
Adults
(age 65+)
479
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 27 Experience Finding Housing
This section explores residents’ experience seeking a place to rent or buy in the county and the extent to which displacement—having to move when they do not want to move—is prevalent.

For those respondents who seriously looked for housing in the past five years, this section also examines the extent to which respondents were denied housing to rent or buy and the reasons why they were denied.

Recent experience seeking housing to rent. Figure 9 presents the proportion of respondents who seriously looked to rent housing for the county, jurisdictions, and selected respondent characteristics, as well as the reasons for denial.

Over half of county respondents (56%) have seriously looked for housing in the past five years.

The most common reasons for denial included:
 Landlord not returning the respondent’s call (26%),
 Landlord told me the unit was available over the phone but when I showed up in person, it was no longer available (22%), and
 Landlord told me it would cost more because of my service or emotional support animal (14%).

Jurisdictions with the highest percentage of respondents who seriously looked for housing include Millbrae (74%), San Mateo (73%), and Redwood City (72%). While all three jurisdictions reported that landlord not returning the respondent’s call was one of their main reasons for denial, 18% of Redwood City respondents identified landlord told me they do not accept Section 8 vouchers as a main reason for denial.

Among respondents by race/ethnicity, 80% of African American respondents reported that they had seriously looked for housing in the past five years while the lowest percentage of respondents who reported seriously looking for housing were non-Hispanic White (46%). The main reasons for denial experienced by African American respondents included landlord told me the unit was available over the phone but when I showed up in person, it was no longer available (39%), landlord told me it would cost more because of my service or emotional support animal (34%), and landlord told me I couldn’t have a service or emotional support animal (28%).

Among respondents by tenure, renters (75%) and precariously housed (74%) respondents reported the highest rates of seriously looking for housing.

Among respondents by income, households making less than $25,000 (71%) had the highest rate. The main reasons for denial reported by these households were landlord told me I couldn’t have a service or emotional support animal (36%) and landlord told me it would cost more because of my service or emotional support animal (30%).
480
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 28 Single parents (79%) and households with children under 18 (66%) also reported the highest percentage of those who seriously looked for housing in the past five years among the selected household characteristics respondent groups. In addition to sharing the top two reasons for denial with the county, 25% of single parent household respondents also reported they were denied housing because the landlord told me I can’t have a service or emotional support animal. 481
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 29 Figure 9. If you looked seriously for housing to rent in San Mateo County in the past five years, were you ever denied housing?
Note: The "Percent Seriously Looked for Housing" column includes all respondents, not just those who indicated they rent.

Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey.

Jurisdiction
County 56% 26% 22% 14% 45% 928
Belmont 62% 33% 27% 31% 49
Brisbane 59% 41% 22% 26% 27
Burlingame 48% 19% 23% 54% 57
Daly City 63% 33% 16% 16% 44% 61
East Palo Alto 58% 35% 30% 26% 23
Foster City 50% 12% 16% 14% 55% 51
Half Moon Bay 68% 17% 17% 48% 29
Hillsborough 42% 14% 29% 14% 57% 14
Milbrae 74% 25% 46% 36% 28
Pacifica 51% 16% 26% 16% 55% 31
Redwood City 72% 31% 18% 40% 99
San Bruno 57% 22% 22% 39% 36
San Mateo 73% 30% 34% 39% 98
South San Francisco 47% 24% 13% 56% 248
Race/Ethnicity
African American 80% 39% 34% 28% 15% 101
Asian 56% 19% 29% 40% 199
Hispanic 63% 32% 22% 41% 230
Other Race 70% 29% 22% 45% 91
Non-Hispanic White 46% 29% 20% 48% 263
Tenure
Homeowner 36% 25% 15% 54% 183
Renter 75% 29% 22% 43% 641
Precariously Housed 74% 23% 32% 26% 188
Income
Less than $25,000 71% 30% 36% 29% 182
$25,000-$49,999 60% 39% 32% 27% 149
$50,000-$99,999 58% 24% 20% 45% 251
Above $100,000 48% 19% 14% 64% 216
Household Characteristics
Children under 18 66% 30% 29% 33% 447
Large Households 60% 33% 19% 18% 44% 139
Single Parent 79% 25% 35% 25% 19% 173
Disability 63% 24% 24% 34% 386
Older Adults (age 65+) 48% 20% 29% 39% 282
n
Overall
Percent
Seriously
Looked for
Housing
Reason for Denial
Landlord did not
return calls
and/or emails
asking about a
unit
Landlord said unit
was available over
phone, but when I
showed up in
person, it was no
longer available
Landlord told me it
would cost me
more for my
service or
emotional animal
Landlord told me
I can't have a
service or
emotional
support animal
Landlord told
me it would cost
me more to rent
because I have
children
Landlord told me
they don't rent to
families with
children
Landlord told
me they do not
accept Section 8
vouchers
Landlord told me they
couldn't make
changes to the
apartment/ home for
my disability
None
of the
Above
482
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 30 Recent experience seeking housing to buy. Figure 10 presents the proportion of respondents who seriously looked to buy housing in the county, by jurisdiction, and selected respondent characteristics, as well as the reasons for denial. As noted above, 56% of county respondents have seriously looked for housing in the past five years.

The most common reasons for denial included:
 Real estate agent told me I would need to show I was prequalified with a bank (29%) and  A bank would not give me a loan to buy a home (23%).

For the jurisdictions with the highest percentage of respondents who seriously looked for housing (Millbrae, San Mateo and Redwood City), all three cities shared the same top two reasons for denial as the county. Additionally, 21% of Millbrae respondents reported that the real estate agent would not make a disability accommodation when I asked.

For African American respondents who looked to buy housing in the last five years, the most common reason for denial was the real estate agent would not make a disability accommodation when I asked (47%).

African Americans, along with Other Races, also most commonly reported that they needed a loan prequalification before real estate agents would work with them. While between 43-54% of respondents from other racial/ethnic groups reported they did not experience any reason for denial when seriously looking to buy housing over the past five years, 12% of African American respondents reported similarly.

Among respondents by income, the main reasons for denial for households making less than $25,000 were the real estate agent told me I would need to show I was prequalified with a bank (32%) and real estate agent only showed me or only suggested homes in neighborhoods where most people were of my same race or ethnicity (26%).

Among the selected housing characteristics category, single parent households and households with children under 18 reported shared the same top two reasons for denial as the county. Additionally, 36% of single parent household respondents reported that the real estate agent would not make a disability accommodation when I asked, as well as 25% of respondents over the age of 65.

Residents in Redwood City, Millbrae, and South San Francisco, as well as large households, also reported that a bank or other lender charged me a high interest rate on my home loan as a reason for denial. 483
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 31 Figure 10. If you looked seriously for housing to buy in San Mateo County in the past five years, were you ever denied housing?
Note: The "Percent Seriously Looked for Housing" column includes all respondents, not just those who indicated they buy.

Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. n
Jurisdiction
County 56% 29% 23% 50% 870
Belmont 62% 21% 15% 35% 48
Brisbane 59% 36% 30% 42% 33
Burlingame 48% 22% 14% 61% 51
Daly City 63% 19% 27% 56% 52
East Palo Alto 58% 24% 33% 48% 21
Foster City 50% 25% 20% 49% 51
Half Moon Bay 68% 35% 23% 23% 50% 26
Hillsborough 42% 18% 23% 59% 22
Milbrae 74% 25% 29% 21% 21% 54% 28
Pacifica 51% 35% 35% 42% 31
Redwood City 72% 30% 22% 27% 50% 64
San Bruno 57% 14% 21% 62% 42
San Mateo 73% 40% 32% 38% 82
South San Francisco 47% 26% 18% 16% 57% 251
Race/Ethnicity
African American 80% 40% 38% 47% 12% 89
Asian 56% 30% 25% 43% 223
Hispanic 63% 29% 28% 49% 174
Other Race 70% 36% 21% 21% 50% 90
Non-Hispanic White 46% 29% 23% 54% 250
Tenure
Homeowner 36% 29% 17% 54% 332
Renter 75% 32% 27% 46% 467
Precariously Housed 74% 36% 36% 30% 30% 154
Income
Less than $25,000 71% 32% 25% 26% 41% 131
$25,000-$49,999 60% 42% 40% 29% 106
$50,000-$99,999 58% 35% 30% 38% 216
Above $100,000 48% 22% 13% 10% 64% 296
Household Characteristics
Children under 18 66% 33% 28% 40% 443
Large Households 60% 33% 25% 25% 49% 126
Single Parent 79% 38% 43% 36% 24% 143
Disability 63% 35% 26% 38% 330
Older Adults (age 65+) 48% 35% 29% 25% 38% 252
Percent
Seriously
Looked for
Housing
Reason for Denial
The real estate agent told
me I would need to show I
was prequalified with a
bank
A bank or other
lender would not
give me a loan to
buy a home
The real estate agent would
not make a disability
accommodation when I
asked
Only showed homes in
neighborhoods where
most people were same
race/ethnicity
A bank or other lender
charged me a high
interest rate on my
home loan
None of
the
Above
484
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 32 Denied housing to rent or buy. Figure 11 presents the proportion of those who looked and were denied housing to rent or buy for the county, jurisdictions, and selected respondent characteristics, as well as reason for denial. As shown, nearly 4 in 10 county respondents who looked for housing experienced denial of housing. African American/Black respondents, precariously housed respondents, households with income below $50,000, and single parent respondents have denial rates of 60% or higher. African American (79%) and single parent (74%) respondents report the highest rates of denial.

Among the reasons for denial:
 Income too low was a major reason for denial for all groups except homeowners and households with incomes above $100,000. Additionally, all jurisdictions report this as a common reason for being denied housing with the exception of Foster City, Hillsborough, and San Bruno.  Haven’t established a credit history or no credit history was also a common reason of denial for most groups. The impacts are higher for Asian, Hispanic and African American households, along with renter and precariously housed respondents, households with income below $50,000, and single parent households, households with children under 18, households with a member experiencing a disability, and several jurisdictions.
 Another top denial reason among certain groups is the landlord didn’t accept the type of income I earn (social security or disability benefit or child support). Source of income was the most common reason for denial among African American households (28%). Other groups with denial rates of 25% or higher for this specific issue include precariously housed respondents, single parent households, and households with a member experiencing a disability, as well as Foster City and San Bruno residents.
 Bad credit is another barrier for accessing housing, particularly for Hispanic and Other Race households, households with income between $50,000-$100,000, and large households. This also impacts East Palo Alto, San Mateo, Daly City, Redwood City, Burlingame, and South San Francisco residents at a higher rate.
485
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 33 Figure 11. If you looked seriously for housing to rent or buy in San Mateo County in the past five years, were you ever denied housing?
Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey.

Jurisdiction
County 39% 1154 18% 44% 19% 21% 449
Belmont 52% 50 38% 27% 27% 26
Brisbane 42% 38 25% 19% 31% 16
Burlingame 30% 71 24% 29% 21
Daly City 49% 73 28% 53% 28% 19% 36
East Palo Alto 55% 29 38% 44% 25% 16
Foster City 30% 63 25% 40% 30% 19
Half Moon Bay 41% 34 29% 29% 14
Hillsborough 23% 22 40% 5
Milbrae 36% 33 67% 25% 33% 25% 12
Pacifica 38% 39 47% 27% 33% 15
Redwood City 41% 105 28% 63% 26% 26% 43
San Bruno 25% 51 31% 31% 38% 13
San Mateo 48% 112 30% 38% 28% 53
South San Francisco 30% 331 19% 58% 28% 17% 98
Race/Ethnicity
African American 79% 107 25% 25% 25% 28% 27% 85
Asian 42% 281 38% 28% 21% 21% 117
Hispanic 49% 253 28% 60% 26% 26% 125
Other Race 43% 105 22% 49% 24% 45
Non-Hispanic White 31% 351 40% 19% 23% 25% 108
Tenure
Homeowner 26% 348 24% 22% 23% 91
Renter 45% 687 48% 20% 24% 310
Precariously Housed 61% 208 42% 22% 25% 126
Income
Less than $25,000 64% 199 47% 31% 29% 127
$25,000-$49,999 65% 158 48% 21% 20% 20% 103
$50,000-$99,999 38% 302 21% 51% 24% 114
Above $100,000 18% 346 27% 16% 20% 16% 64
Household Characteristics
Children under 18 51% 558 42% 26% 19% 283
Large Households 43% 171 27% 64% 41% 74
Single Parent 74% 189 41% 27% 25% 138
Disability 54% 446 39% 21% 25% 239
Older Adults (age 65+) 44% 350 35% 22% 21% 153
Percent
Denied
Housing Total n
Bad
Credit
Eviction
history
Income
too low
I had/
have
COVID Foreclosure n
Reason for Denial
Too many
people in my
household
Other
renter/
applicant
willing to pay
more for rent
Haven't
established a
credit
history/no
credit history
Don't have a
regular/
steady job/
consistent
work history
Landlord didn't
accept the type of
income I earn
(social security or
disability)
Lack of
stable
housing
record
Real or
perceived
sexual
orientation or
gender
identity
486
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 34 Experience using housing vouchers. It is “difficult” or “very difficult” for eight out of 10 voucher holders to find a landlord that accepts a housing voucher (Figure 13).

As shown in Figure 12, this is related to the amount of the voucher and current rents and the lack of supply (inability to find a unit in the allotted amount of time). Over half of voucher holders (53%) who experienced difficulty indicated the voucher is not enough to cover the rent for places I want to live and almost half of voucher holders (49%) who experienced difficulty indicated there is not enough time to find a place to live before the voucher expires.

Other significant difficulties using vouchers identified by respondents included landlords have policies of not renting to voucher holders (46%) and can’t find information about landlords that accept Section 8 (36%).

Among respondents by race/ethnicity, African American respondents had the greatest proportion of those with a housing choice voucher (60%). Of those respondents, 76% found it difficult to find a landlord that accepts a housing voucher. While 13% of Hispanic respondents have a housing voucher, 85% have found it difficult to use the voucher. Fourteen percent of Asian respondents have housing vouchers— nearly three quarters of these respondents reported that the voucher is not enough to cover the rent for the places I want to live.

Other groups of respondents with higher proportions of voucher utilization include single parent households (43%), precariously housed respondents (30%), and households with income below $25,000 (29%). For each of the aforementioned groups, more than 75% of their respective respondents reported difficulty in utilizing the housing choice voucher. The voucher is not enough to cover the rent for places I want to live was one of the main reasons cited for not using the voucher. 487
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 35 Figure 12.

Why is it difficult to
use a housing
voucher?
Source:

Root Policy Research from the 2021-
2022 21 Elements AFFH Resident
Survey.
488
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 36 Figure 13. How difficult is it to find a landlord that accepts a housing voucher? Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey.

Jurisdiction
County 12% 18% 55% 27% 250 53% 49% 46% 36% 6% 203
Belmont 16% 14% 64% 21% 81 45% 64% 36% 27% 9% 11
Brisbane 22% 20% 73% 7% 15 50% 50% 42% 33% 0% 12
Burlingame 8% 0% 75% 25% 12 50% 50% 25% 8% 0% 12
Daly City 12% 14% 50% 36% 14 83% 25% 42% 17% 25% 12
East Palo Alto 14% 29% 57% 14% 7 20% 20% 40% 60% 0% 5
Foster City 12% 18% 47% 35% 17 47% 40% 27% 33% 7% 15
Half Moon Bay 19% 22% 56% 22% 9 71% 29% 29% 43% 14% 7
Hillsborough 8% 25% 75% 0% 4 67% 67% 33% 0% 0% 3
Milbrae 22% 50% 20% 30% 10 60% 40% 20% 40% 0% 5
Pacifica 11% 13% 50% 38% 8 86% 43% 43% 43% 0% 7
Redwood City 16% 13% 61% 26% 23 40% 50% 70% 45% 5% 20
San Bruno 12% 9% 64% 27% 11 40% 60% 50% 10% 10% 10
San Mateo 24% 24% 50% 26% 38 43% 54% 43% 39% 7% 28
South San Francisco 4% 11% 33% 56% 27 63% 50% 71% 63% 8% 24 Race/Ethnicity
African American 60% 24% 60% 16% 82 55% 52% 40% 31% 6% 62 Asian 14% 23% 63% 14% 71 73% 44% 31% 31% 0% 55
Hispanic 13% 15% 40% 45% 53 58% 42% 51% 49% 11% 45
Other Race 19% 29% 50% 21% 28 55% 45% 65% 35% 5% 20
Non-Hispanic White 8% 14% 61% 25% 64 43% 61% 57% 38% 4% 56 Tenure
Homeowner 8% 23% 59% 18% 78 58% 49% 42% 31% 0% 59
Renter 18% 19% 52% 30% 165 55% 52% 48% 43% 6% 134
Precariously Housed 30% 14% 66% 20% 86 57% 54% 35% 26% 7% 74 Income
Less than $25,000 29% 17% 58% 25% 84 47% 41% 47% 37% 10% 70 $25,000-$49,999 18% 17% 52% 31% 48 63% 55% 63% 40% 5% 40 $50,000-$99,999 12% 23% 52% 26% 62 55% 55% 51% 37% 2% 49 Above $100,000 5% 20% 57% 23% 35 43% 61% 29% 32% 4% 28
Household Characteristics
Children under 18 21% 20% 60% 20% 179 59% 51% 44% 35% 1% 143 Large Households 7% 20% 45% 35% 20 63% 56% 63% 56% 6% 16 Single Parent 43% 17% 58% 24% 103 62% 52% 38% 33% 2% 85 Disability 22% 18% 58% 24% 158 57% 52% 42% 29% 5% 129
Older Adults (age 65+) 17% 18% 63% 19% 123 56% 53% 44% 34% 3% 102 Not enough time to find
a place to live before the
voucher expires
Landlords have
policies of not
renting to voucher
holders
Can't find information
about landlords that
accept Section 8 Other n
Voucher is not enough
to cover the rent for
places I want to live
Percent
with a
Housing
Voucher
Not
difficult
Somewhat
difficult
Very
difficult n
489
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 37 Displacement. Figure 14 presents the proportion of residents who experienced displacement in the past five years, as well as the reason for displacement.  Overall, 21% of survey respondents experienced displacement in the past five years. Among all survey respondents, the main reason for displacement was rent increased more than I could pay (29%).
 Respondents who are precariously housed have higher rates of recent displacement than homeowners or renters; this suggests that when displaced a unit these housing-insecure tenants are more likely to couch surf or experience homelessness for some period of time before securing a new place to live.
 Among respondents by race/ethnicity, African American respondents reported the highest rate of displacement (59%). The primary reason reported by African American respondents for their displacement was housing was unsafe (e.g., domestic assault, harassment).

Twenty eight percent also reported that they were forced out for no reason.  Asian households, as well as homeowners, households that make less than $25,000, single parent households, households that include a member experiencing a disability, and Millbrae, Brisbane and Pacifica residents are also more likely than other respondents to have been displaced due to an unsafe housing situation (e.g., domestic assault, harassment).  Additionally, Asian, precariously housed respondents, households making less than $25,000, single parent households, and Hillsborough residents are more likely than other respondents to have been displaced and not given a reason.

For respondents that had experienced displacements, they were asked to identify which city they moved from and which city they moved to. The most common moves to and from cities included:
 Moved within South San Francisco (28 respondents)
 Moved from outside San Mateo County to San Mateo (10 respondents)  Moved from San Bruno to South San Francisco (9 respondents)  Moved from Daly City to South San Francisco (9 respondents)  Moved within Burlingame (8 respondents)
490
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 38 Figure 14. Displacement Experience and Reasons for Displacement Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey.

Jurisdiction
County 21% 2066 29% 19% 18% 417
Belmont 26% 80 25% 25% 30% 20
Brisbane 24% 67 25% 31% 25% 16
Burlingame 22% 152 24% 30% 18% 33
Daly City 25% 115 35% 27% 31% 26
East Palo Alto 32% 50 20% 20% 20% 15
Foster City 11% 130 21% 21% 21% 43% 14
Half Moon Bay 31% 51 31% 25% 16
Hillsborough 12% 52 33% 33% 33% 33% 33% 6
Milbrae 27% 44 42% 33% 25% 25% 12
Pacifica 21% 75 31% 31% 31% 16
Redwood City 29% 146 31% 21% 42
San Bruno 25% 89 33% 29% 24% 21
San Mateo 37% 153 35% 31% 20% 54
South San Francisco 12% 712 42% 15% 16% 81
Race/Ethnicity
African American 59% 134 29% 30% 28% 79
Asian 22% 500 31% 22% 22% 109
Hispanic 29% 397 33% 22% 18% 115
Other Race 28% 149 54% 20% 24% 41
Non-Hispanic White 14% 757 27% 20% 31% 102
Tenure
Homeowner 8% 975 27% 25% 31% 75
Renter 34% 905 32% 18% 22% 292
Precariously Housed 48% 280 23% 24% 23% 132
Income
Less than $25,000 45% 282 28% 20% 20% 20% 127
$25,000-$49,999 30% 265 31% 19% 18% 78
$50,000-$99,999 22% 517 32% 22% 18% 115
Above $100,000 8% 721 27% 20% 23% 60
Household Characteristics
Children under 18 30% 840 27% 20% 19% 249
Large Households 20% 284 32% 19% 18% 57
Single Parent 55% 240 24% 24% 20% 131
Disability 34% 711 26% 20% 20% 20% 241
Older Adults (age 65+) 22% 736 23% 22% 22% 162
Because of
apartment
rules
Landlord
refused to
renew my
lease
Reason for Displacement
Percent
Displaced Total n
Rent
increased
more than I
could pay
Personal/
relationship
reasons
Landlord was
selling the
home/
apartment
Landlord
wanted to
move back
in/move in
family
Landlord
wanted to
rent to
someone
else
Housing was
unsafe (e.g.,
domestic
assault,
harassment)
Forced
out for
no
reason
Health/m
edical
reasons
I was
behind
on rent
Poor
condition of
property
Utilities were
too
expensive/
shut off
Natural
disaster/
flooding/
fire n
491
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 39 Children changing schools after displacement. Overall, for households with children that were displaced in the past five years, 60% of children in those households have changed schools. The most common outcomes reported among these respondents included school is more challenging (28%), they feel less safe at the new school (25%), and they are in a worse school (24%) (Figure 15).

Among respondents by race/ethnicity, non-Hispanic White households (44%) were the only subgroup to report that being displaced resulted in their children being in better schools. Of African American households that were displaced and have children, 87% reported that their children changed schools.

Of these respondents, 32% reported that their children feel safer at the new school but also have fewer activities.

Among respondents by tenure, precariously housed (78%) and homeowner (74%) households had the highest proportion of children who changed schools. The most common outcomes for precariously housed households included School is less challenging/they are bored (35%) and their children feel less safe at school (34%). For homeowner households, 39% reported that school is more challenging, followed by 31% who reported that their children feel less safe at school.

Among respondents by selected household characteristics, older adult (77%), single parent (74%), households with a member experiencing a disability (70%), and households with children under 18 (67%) all reported high proportions of children who changed schools. The most common outcomes for these respondents included School is more challenging and they feel less safe at the new school. 492
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 40 Figure 15. Children Changing Schools and Outcomes, Displaced Households Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey.

Jurisdiction
County 60% 306 28% 24% 25% 183
Belmont 45% 20 33% 44% 33% 9
Brisbane 81% 16 38% 31% 31% 13
Burlingame 55% 22 33% 33% 33% 12
Daly City 41% 17 43% 29% 29% 29% 7
East Palo Alto 54% 13 43% 57% 29% 7
Foster City 62% 13 50% 8
Half Moon Bay 58% 12 43% 29% 29% 43% 7
Hillsborough 60% 5 67% 3
Milbrae 82% 11 33% 44% 44% 33% 9
Pacifica 91% 11 50% 10
Redwood City 52% 23 25% 33% 25% 12
San Bruno 67% 18 33% 33% 33% 12
San Mateo 66% 35 32% 32% 22
South San Francisco 36% 56 26% 26% 26% 19
Race/Ethnicity
African American 87% 69 30% 30% 32% 32% 60
Asian 73% 91 27% 32% 32% 27% 66
Hispanic 49% 91 23% 30% 23% 25% 44
Other Race 65% 31 40% 30% 25% 25% 20
Non-Hispanic White 60% 60 28% 31% 44% 28% 36
Tenure
Homeowner 74% 66 39% 29% 31% 49
Renter 58% 213 25% 30% 25% 122
Precariously Housed 78% 104 35% 34% 30% 80
Income
Less than $25,000 65% 92 22% 32% 35% 60
$25,000-$49,999 66% 56 25% 28% 28% 25% 36
$50,000-$99,999 55% 85 30% 28% 23% 47
Above $100,000 59% 44 35% 31% 38% 26
Household Characteristics
Children under 18 67% 237 32% 23% 25% 158
Large Households 45% 44 32% 26% 32% 19
Single Parent 74% 124 32% 28% 29% 92
Disability 70% 188 26% 28% 30% 132
Older Adults (age 65+) 77% 117 35% 29% 29% 89
n
Percent of
Children that
Changed
Schools
School change outcomes
Total n
School is less
challenging/
they are bored
School is more
challenging
They are
in a better
school
They are
in a worse
school
They feel
less safe at
the new
school
They feel
safer at
the new
school
They have
fewer
activities
They have
more
activities
Things are
about the
same
493
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 41 Experience with housing discrimination. Overall, 19% of survey respondents felt they were discriminated against when they looked for housing in the area.1 As shown in Figure 16, African American respondents (62%), single parent households (44%) and precariously housed respondents (39%) are most likely to say they experienced housing discrimination. Residents with income above $100,000 and homeowners are least likely (11%).

Respondents who believed they experienced discrimination when looking for housing in the county reported when the discrimination occurred. Nearly half of respondents (45%) reported that the discrimination they experienced occurred between 2 and 5 years ago. Twenty eight percent of respondents reported that the discrimination occurred in the past year, 20% reported more than 5 years ago and 7% of respondents did not remember when the discrimination occurred.

How discrimination was addressed. Respondents who believed they experienced discrimination when looking for housing in the county were asked to describe the actions they took in response to the discrimination. Overall, the most common responses to discrimination experienced by survey respondents were Nothing/I wasn’t sure what to do (42%), Moved/found another place to live (30%), and Nothing/I was afraid of being evicted or harassed (20%).

Among top responses for actions taken in response to experienced discrimination, every group reported Nothing/I wasn’t sure what to do with the exception of African American and single parent households, as well as Brisbane and Hillsborough residents. Similarly, survey respondents from Foster City and Pacifica were the only groups not to include Moved/found another place to live among their top responses. African American and Asian households, as well as single parent households, were more likely than other groups to contact either a housing authority, local fair housing organization, or the California Department of Housing or Civil Rights to report their discrimination incident.

Reasons for discrimination. Respondents who believed they experienced discrimination when looking for housing in the county provided the reasons why they thought they were discriminated against. Note that the basis offered by residents is not necessarily protected by federal, state, or local fair housing law, as respondents could provide open-ended and multiple reasons why they thought they experienced discrimination.

Examples of how respondents described why they felt discriminated against, which they provided as open-ended responses to the survey, include:
1 Note that this question applies to all respondents, not just those who seriously looked for housing in the past five years. 494
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 42 Appearance/Characteristics
 “Because of my race and ethnicity”
 “[We] were given a subprime loan for home purchase for being Latinx, low-income and primarily Spanish-speaking; refinance last year was lower than expected.”  “It was clear my disability is the reason”
 “I have a child and a couple places told me they wouldn’t rent to me due to my son.”  “The agent asked if I was a tech worker. When I said no, the agent said the place was just rented, even though it was on the listing as active.”
 “I was approved for the unit and when they met my partner, who is Black, they said [the unit] was rented.”
Source of Income/Credit
 “Income was through SSDI [social security disability insurance]”  “The landlord wanted an excellent credit score…”
 “We were not able to provide all the requirement to rent, like SSN [social security number], income proof, employment, and we don’t make enough income…”
 “They wanted someone with income from employment not due to disability.”  “I was discriminated against because of my race and the fact that I had Section 8 at the time. Being African American and having Section 8 made a lot of people feel like I wouldn’t take care of their property.”
 “I am currently being discriminated against due to my need with rental help and because two of us in our household have a need for an emotional support animal.” Immigration status
 Mi hermana llamo a los departamentos donde yo vivo y la manager le dijo que no había disponible pero no era verdad también le dijo que hablara inglés y le pidió seguro social pensando que no tenia y le dijo que tenía que ganar una cierta cantidad de dinero para poder rentar. (My sister called the apartments where I live and the manager told her that there was no one available but it was not true.

She also told her to speak English and asked for social security thinking that she did not have it and told her that she had to earn a certain amount of money to be able to rent). 495
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 43 Figure 16. Percent of respondents who felt they were discriminated against and how was it addressed Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. n
Jurisdiction
County 19% 28% 45% 20% 7% 357 42% 30% 20% 359
Belmont 21% 19% 56% 19% 6% 16 38% 38% 50% 16
Brisbane 22% 29% 36% 29% 7% 14 64% 21% 21% 14
Burlingame 14% 25% 50% 20% 5% 20 35% 25% 20% 20% 20
Daly City 15% 20% 40% 33% 7% 15 56% 25% 25% 16
East Palo Alto 29% 23% 54% 15% 8% 13 38% 38% 23% 23% 13 Foster City 18% 15% 40% 45% 0% 20 38% 24% 24% 21
Half Moon Bay 26% 27% 55% 9% 9% 11 27% 36% 36% 11
Hillsborough 15% 14% 71% 0% 14% 7 29% 57% 7
Milbrae 29% 36% 50% 7% 7% 14 31% 23% 38% 23% 13
Pacifica 21% 29% 36% 36% 0% 14 50% 21% 29% 21% 21% 14
Redwood City 24% 34% 34% 19% 13% 32 47% 26% 21% 21% 34
San Bruno 12% 30% 60% 0% 10% 10 50% 30% 30% 30% 10
San Mateo 30% 35% 45% 15% 5% 40 53% 26% 26% 38
South San Francisco 13% 30% 40% 23% 6% 82 59% 27% 83
Race/Ethnicity
African American 62% 16% 59% 25% 0% 83 36% 29% 27% 26% 27% 24% 84 Asian 16% 24% 50% 20% 6% 82 28% 25% 29% 29% 24% 24% 83
Hispanic 27% 25% 42% 24% 8% 107 52% 27% 107
Other Race 30% 28% 47% 14% 12% 43 47% 30% 26% 43
Non-Hispanic White 12% 38% 41% 14% 7% 91 44% 27% 18% 91 Tenure
Homeowner 11% 26% 46% 20% 7% 95 32% 29% 22% 96
Renter 28% 26% 47% 20% 6% 232 42% 32% 23% 232
Precariously Housed 39% 21% 54% 20% 4% 98 24% 28% 35% 26% 100 Income
Less than $25,000 36% 29% 51% 11% 9% 100 39% 30% 25% 102 $25,000-$49,999 24% 31% 41% 22% 6% 64 42% 36% 25% 22% 64 $50,000-$99,999 19% 27% 45% 25% 3% 97 44% 29% 18% 97
Above $100,000 11% 28% 45% 21% 7% 76 45% 22% 16% 16% 76 Household Characteristics
Children under 18 26% 21% 57% 15% 6% 216 36% 31% 26% 218 Large Households 19% 26% 52% 9% 13% 54 65% 24% 15% 55
Single Parent 44% 13% 65% 17% 5% 106 33% 32% 27% 26% 26% 107 Disability 33% 27% 48% 21% 4% 215 33% 30% 22% 219
Older Adults (age 65+) 20% 20% 51% 20% 8% 144 24% 34% 24% 24% 146 Called/
emailed
California
Department
of Housing/
Civil Rights
Called/ emailed
City office,
County office,
or human rights
department/
agency
Filed a
complaint Other
Percent who felt
they were
discriminated
against
In the
past
year
2 to 5
years
ago
More
than 5
years
ago n
Nothing/ I
wasn't
sure what
to do
Moved/
found
another
place to
live
Nothing/ I
was afraid of
being
evicted/
harassed
Called/
emailed
housing
authority
Called/ emailed
local fair
housing
organization
Don't
remember
496
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 44 Experience of persons with disabilities. Overall, 35% of respondents’ households include a member experiencing a disability. Of these households, 26% said their housing does not meet their accessibility needs; 74% report that their current housing situation meets their needs. The three top greatest housing needs expressed by respondents included grab bars in bathroom or bench in shower (34%), supportive services to help maintain housing (33%), and ramps (26%). Other needs expressed by a substantial proportion of groups included wider doorways, reserved accessible parking spot by the entrance, and more private space in the facility in which I live.

Of respondents by jurisdiction, East Palo Alto (64%) has the lowest proportion of respondents with disabilities whose current housing situation meets their needs. Of these respondents, 63% indicated they needed supportive services to help maintain housing.

The highest proportion of respondents by group reporting that they or a member of their household experiences a disability were African American (71%), households making less than $25,000 (59%), single parent households (58%), and precariously housed respondents (56%). 497
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 45 Figure 17. Respondents experiencing a disability and their top three greatest housing needs Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. n
Jurisdiction
County 35% 74% 711 34% 33% 26% 171
Belmont 35% 89% 28 67% 67% 3
Brisbane 37% 72% 25 29% 29% 29% 29% 7
Burlingame 27% 80% 41 63% 50% 50% 8
Daly City 34% 68% 38 36% 36% 45% 36% 11
East Palo Alto 44% 64% 22 63% 8
Foster City 31% 83% 40 29% 29% 7
Half Moon Bay 45% 68% 22 29% 29% 7
Hillsborough 26% 100% 13 n/a
Milbrae 40% 82% 17 25% 25% 25% 25% 25% 25% 4
Pacifica 39% 93% 29 100% 2
Redwood City 42% 68% 62 33% 28% 28% 33% 18
San Bruno 40% 82% 34 50% 33% 33% 6
San Mateo 43% 72% 65 41% 47% 41% 17
South San Francisco 30% 68% 210 35% 28% 32% 57
Race/Ethnicity
African American 71% 87% 95 40% 40% 33% 15
Asian 31% 77% 157 29% 34% 26% 26% 35
Hispanic 41% 70% 162 37% 54% 35% 46
Other Race 38% 71% 56 63% 50% 44% 16
Non-Hispanic White 32% 77% 241 33% 27% 21% 52
Tenure
Homeowner 29% 82% 280 35% 37% 37% 43
Renter 39% 73% 347 41% 40% 27% 88
Precariously Housed 56% 71% 154 37% 26% 33% 43
Income
Less than $25,000 59% 71% 167 42% 27% 23% 48
$25,000-$49,999 40% 67% 107 45% 45% 45% 31
$50,000-$99,999 35% 77% 180 43% 26% 24% 42
Above $100,000 23% 82% 167 52% 34% 41% 29
Household Characteristics
Children under 18 35% 78% 293 40% 29% 32% 63
Large Households 35% 70% 99 41% 45% 34% 29
Single Parent 58% 81% 139 48% 28% 41% 29
Older Adults (age 65+) 46% 76% 337 44% 29% 30% 79
Ramps
Percent of
respondents
with a
disability
Current
housing
situation
meeting
needs Total n
Grab bars in
bathroom or
bench in
shower
Supportive
services to
help
maintain
housing
Alarm to
notify if a
non-verbal
child leaves
the home
Fire
alarm/doorbell
made accessible
for person with
hearing
disability/deaf
Better
navigation
for person
who is blind
Wider
doorways
Reserved
accessible
parking spot
by entrance
More
private
space in
the facility
in which I
live
Service or
emotional
support
animal
allowed
Would like to
live alone
(not with a
roommate)
Fewer
restrictions/
more freedom
498
ROOT POLICY RESEARCH APPENDIX C.2. COMMUNITY SURVEY, PAGE 46 Transportation. Over 80% of respondents indicated the type of transportation used most often is driving a personal vehicle. This share was relatively similar across the majority of jurisdictions and was the number one type of transportation used across all jurisdictions and demographic characteristics.

The groups with the lowest proportion of those who primarily drive included African American (40%), households making less than $25,000 (53%), single parents (57%), and precariously housed (57%) respondents.

As shown in Figure 18, on average respondents are fairly satisfied with their transportation situation.

Those groups somewhat or not at all satisfied with their transportation options include African American (58%), Brisbane (51%), single parents (45%) and precariously housed (44%) respondents. 499
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 47
Figure 18.

Are you satisfied
with your current
transportation
options?
Source:

Root Policy Research from the
2021-2022 21 Elements AFFH
Resident Survey.

Jurisdiction
County 29% 45% 20% 6% 1,903
Belmont 21% 42% 27% 10% 78
Brisbane 17% 33% 38% 13% 64
Burlingame 32% 45% 21% 1% 139
Daly City 19% 52% 20% 8% 109
East Palo Alto 31% 36% 24% 9% 45
Foster City 29% 43% 20% 9% 115
Half Moon Bay 30% 35% 26% 9% 46
Hillsborough 50% 34% 14% 2% 44
Milbrae 30% 45% 13% 13% 40
Pacifica 28% 42% 15% 15% 65
Redwood City 30% 36% 27% 8% 142
San Bruno 23% 54% 19% 4% 81
San Mateo 29% 52% 14% 4% 134
South San Francisco 34% 48% 15% 3% 666
Race/Ethnicity
African American 22% 21% 48% 10% 134
Asian 23% 49% 24% 4% 500
Hispanic 29% 43% 22% 7% 397
Other Race 29% 41% 21% 9% 149
Non-Hispanic White 32% 45% 17% 5% 757
Tenure
Homeowner 31% 45% 18% 6% 905
Renter 27% 44% 23% 6% 834
Precariously Housed 20% 36% 35% 9% 254
Income
Less than $25,000 22% 39% 29% 10% 282
$25,000-$49,999 25% 42% 26% 8% 265
$50,000-$99,999 28% 52% 16% 4% 517
Above $100,000 34% 44% 18% 4% 721
Household Characteristics
Children under 18 25% 43% 25% 6% 840
Large Households 29% 50% 18% 4% 284
Single Parent 20% 36% 38% 7% 240
Disability 25% 40% 27% 8% 658
Older Adults (age 65+) 30% 43% 21% 6% 736
Entirely
satisfied
Mostly
satisfied
Somewhat
unsatisfied
Not at all
satisfied n
500
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 48
Solutions offered by residents. Respondents were asked a series of questions about how to improve their situations related to housing, employment, health, education and neighborhood.

Improve housing security. When asked what could improve a respondent’s housing security, the top answers among respondents by jurisdiction, race/ethnicity, tenure, income, and other selected housing characteristics were none of the above and help me with a downpayment/purchase.

The highest proportion of respondents among groups that selected None of the above includes:
 Hillsborough residents, 71%
 Owners, 65%
 Income greater than $100,000, 54%
 Foster City residents, 53%
 White, 51%
 Burlingame residents, 50%
The highest proportion of respondents among groups that selected Help me with a downpayment or purchase includes:
 Renters, 44%
 Large households, 42%
 Daly City residents, 41%
 Hispanic, 39%
 Precariously housed, 39%
 City of San Mateo residents, 37%
Other solutions to improve housing security identified by several different groups included Help me with the housing search, help me pay rent each month, and find a landlord who accepts Section 8. The highest proportion of respondents among groups that selected these solutions includes:

Help me with the housing search
 Precariously housed, 39%
 Income less than $25,000, 34%
 Income between $25,000-$50,000, 29%
501
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 49
 Half Moon Bay residents, 27%
Help me pay rent each month
 Income less than $25,000, 35%
 Single parent, 31%
Find a landlord who accepts Section 8
 Black or African American, 37%
Improve neighborhood situation. When asked what could improve a respondent’s neighborhood situation, nearly every respondent group by jurisdiction, race/ethnicity, tenure, income, and other selected housing characteristics identified Better lighting. Other solutions flagged by multiple respondent groups to improve their neighborhood situations includes Improve street crossings and none of the above.

The highest proportion of respondents among groups that selected Better lighting includes:
 East Palo Alto residents, 45%
 Millbrae residents, 45%
 Other race, 42%
 Daly City residents, 41%
 Hispanic, 40%
 Income between $25,000-$50,000, 40%
 Income between $50,000-$100,000, 40%
The highest proportion of respondents among groups that selected Improve street crossings includes:
 City of San Mateo residents, 34%
 Single parent, 31%
The highest proportion of respondents among groups that selected None of the above includes:
 Foster City residents, 37%
 Hillsborough residents, 36%
 Burlingame residents, 28%
502
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 50
Additionally, 42% of Millbrae respondents chose Reduce crime, 40% of Brisbane respondents chose More stores to meet my needs, and Belmont (34%) and Half Moon Bay (33%) respondents chose Build more sidewalks.

Improve health situation. When asked what could improve a respondent’s health situation, the majority of respondent groups by jurisdiction, race/ethnicity, tenure, income, and other selected housing characteristics selected Make it easier to exercise, More healthy food and None of the above.

The highest proportion of respondents among groups that selected Make it easier to exercise includes:
 Redwood City residents, 48%
 Hispanic, 42%
 South San Francisco residents, 41%
 City of San Mateo residents, 41%
 Asian, 41%
 Renters, 40%
The highest proportion of respondents among groups that selected More healthy food includes:
 East Palo Alto residents, 48%
 Precariously Housed, 47%
 Single parent, 41%
 Daly City residents, 40%
 Income less than $25,000, 38%
 Black or African American, 37%
 Large Households, 37%
The highest proportion of respondents among groups that selected None of the above includes residents from:
 Hillsborough residents, 48%
 Burlingame residents, 47%
 Foster City residents, 42%
 White, 41%
 Owners, 39%
503
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 51
Additionally, African American (34%) and San Bruno (29%) respondents identified Better access to mental health care as a solution to help improve their health situations.

Improve job situation. When asked what could improve a respondent’s employment situation, the majority of respondent groups by jurisdiction, race/ethnicity, tenure, income, and other selected housing characteristics selected Increase wages and None of the above.

The highest proportion of respondents among groups that selected Increase wages includes:
 Renters, 52%
 Single parents, 50%
 Hispanic, 49%
 Households with children, 49%
 Daly City residents, 49%
 Income between $50,000-$100,000, 49%
 Large households, 48%
The highest proportion of respondents among groups that selected None of the above includes:
 Hillsborough residents, 76%
 Owners, 58%
 White, 57%
 Over 65+, 53%
 Income greater than $100,000, 53%
 Foster City residents, 53%
Additionally, 29% of households with income less than $25K identified Find a job near my apartment or house as a solution to help improve their situation.

Improve education situation. When asked what could improve a respondent’s education situation for their children, the majority of respondent groups by jurisdiction, race/ethnicity, tenure, income, and other selected housing characteristics selected None of the above, Have more activities, and Stop bullying/crime/drug use at school.

The highest proportion of respondents among groups that selected None of the above includes:
 Burlingame residents, 55%
504
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 52
 White, 52%
 Over 65+, 51%
 Hillsborough residents, 49%
 Foster City residents, 46%
 Brisbane residents, 45%
The highest proportion of respondents among groups that selected Have more activities includes:
 Single parent, 45%
 Households with children, 41%
 Large households, 41%
 Other race, 37%
 Daly City residents, 34%
 Hispanic, 34%
The highest proportion of respondents among groups that selected Stop bullying/crime/drug use at school includes:
 East Palo Alto residents, 38%
 Precariously housed, 31%
 Other race, 30%
 Redwood City residents, 29%
 Hispanic, 29%
 San Mateo residents, 28%
Additionally, 29% of Millbrae respondents identified Have better teachers at their schools as a means to improve the education situation in their respective households. 505
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 1 AFFH Attachment C.3.

Disparate Access to Educational Opportunities
This section examines the extent to which members of protected classes and those in poverty experience disparities in access to opportunity as measured by access to education. This section draws from data provided by the San Mateo Office of Education, the California Department of Education, and U.S. Census American Community Surveys (ACS). This section discusses the following topics:
 Changes in school enrollment during COVID-19 by race and ethnicity, and by groups with extenuating circumstances;
1  Achievement gaps by race and ethnicity and for groups with extenuating circumstances as measured by test scores, California State University or University of California admissions standards, and college-going rates;  Barriers to success measured by chronic absenteeism, dropout rates, and suspension rates.

After describing this section’s primary findings, we describe the county’s school districts before launching into data measuring achievement gaps and barriers to success.

Primary Findings
Student racial and ethnic diversity is modestly increasing. Student bodies in San Mateo County have become increasingly racially and ethnically diverse.  Hispanic students make up the largest ethnic group in the county’s schools, representing 38% of students in the 2020-2021 academic school year. This a slight increase from the 2010-2011 school year, where Hispanic students made up 37% of the population.
 There has been a large increase in Asian students, with 17% identifying as such in 2020-2021, an increase of 5 percentage points from 2010-2011.  Students identifying as White (26%) have decreased by 3 percentage points since 2010- 2011.
1 The term “extenuating circumstances” is used in this section to capture students whose socioeconomic situations and/or disability may make standard educational environments challenging. 506
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 2 Free and reduced lunch-qualifying students and English language learners are concentrated in a handful of schools. Overall, 29% of public school students in San Mateo County qualify for reduced or free lunch.  The rate of reduced lunch qualification was highest in Ravenswood City Elementary School District, where 83% of students qualify for reduced lunch. Also in Ravenswood City Elementary, 30% of students are experiencing homelessness. This is a large outlier in the county, where overall just 2% are experiencing homelessness.  Countywide, 20% of public school students are English learners. Again, this rate is highest at Ravenswood City Elementary, where 53% of students are English learners.

La Honda-Pescadero Unified School District, Jefferson Union High School, and Redwood City Elementary also have high rates of English learners, representing more than a third of students.

Enrollment is dropping. Public school enrollment reduced substantially in some areas during the pandemic. Total enrollment decreased by 3% between 2019-2020 and 2020-2021 in San Mateo County, which was the largest decrease of the decade.  Portola Valley and La Honda-Pescadero school districts had the largest enrollment decreases during COVID-19, with a 11% and 10% decline in enrollments, respectively.  Decreased enrollment was especially common among Pacific Islander students.

Between 2019-2021, enrollment among Pacific Islander students decreased by 6% (from 1,581 students in 2019-20 to 1,484 students in 2020-21), substantially higher than the 3% countywide average.
 Enrollment among migrant students decreased drastically by 16% over the same period (from 332 students to 279 students).

Learning proficiency is improving yet disparities exist. Across all racial and ethnic groups, the rate at which students met or exceeded English and mathematics testing standards has increased since the 2014-2015 school year. Students with extenuating circumstances (i.e., disability, facing homelessness, learning English) tend to score lower on English and mathematics tests than the overall student body.  Proficiency gaps are especially pronounced among English learning students in Portola Valley Elementary, Woodside Elementary, Menlo Park City Elementary, and Brisbane Elementary, where students with extenuating circumstances met or exceeded mathematics test standards at a rate at least 50 percentage points below the overall test rate in each district.
 Students with disabilities in San Carlos Elementary and Las Lomitas Elementary school districts scored far below the overall student body: In these districts, students with disabilities met or exceeded mathematics test standards at 54 percentage points below the overall test rate.
507
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 3 Many students meet admissions standards for CSU or UC schools.  Among the high school districts in San Mateo County, Sequoia Union had the highest rate of graduates who met such admission standards, at 69%. On the other end of the spectrum, Cabrillo Unified and South San Francisco Unified had the lowest rates at 41%.
 Jefferson Union High School District had the most drastic increase in the share of graduates meeting CSU or UC standards: just 21% of students met these standards in 2016-2017 compared to 48% of students in 2019-2020. La Honda-Pescadero Unified School District experienced a 10 percentage point increase in this success rate over the same period.

Most school districts in the county have a college-going rate at 70% or higher—yet there are wide gaps by race and ethnicity.
 In every district, White students have a higher college-going rate than Hispanic students, but the largest gaps are in South San Francisco United, where 91% of White students go to college compared to just 68% of Hispanic students—a 23 percentage point gap.

Students with extenuating circumstances are highly concentrated in a few schools and move schools often due to housing instability.  Students with extenuating circumstances may need additional resources—e.g., onsite health care, free meals, tutoring—to be successful in school. When these students are concentrated into a few schools, the schools bear an unequal responsibility for providing needed resources. K-12 school funding in California has long been inadequate, and, although policymakers have recently allocated additional resources to schools with high proportions of low income children under a “concentration grant” system, funding gaps remain.
 The highest concentration of high needs students is found in Ravenswood City Elementary, where 30% of all students are experiencing homelessness and 83% qualify for free and reduced lunch.
 Currently, students whose families have been evicted do not have protections allowing them to remain in their current school district. This can result in frequent changes in schools for low income children, raising their vulnerability to falling behind in school.

Absenteeism, dropout rates, and discipline rates are highest for students of color, students with disabilities, and students with other extenuating circumstances. While 10% of students were chronically absent during the 2018-2019 school year, chronic absenteeism rates were higher in districts with a large number of students experiencing economic and housing precarity.  For instance, Ravenswood Elementary, which has a 30% rate of homelessness among students, had one of the higher rates of chronic absenteeism at 16%. 508
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 4  Pacific Islander students (26%), Black/African American students (18%), and Hispanic students (15%) had notably higher rates of chronic absenteeism than the overall student population (10%).
 In most districts, chronic absenteeism is higher among students with disabilities. In fact, only Bayshore Elementary’s students with disabilities had a lower rate of chronic absenteeism than the overall student body.

Dropout rates vary across the county:
 Dropout rates were highest in Sequoia Union High School District (10%) and South San Francisco Unified (9%).
 In all school districts in the county, dropout rates are higher for boys than for girls.  Pacific Islander, Black/African American, and Hispanic students in the county often had higher dropout rates than those in other racial and ethnic groups  Students with disabilities, students experiencing homelessness, foster youth, and students learning English had higher dropout rates than the overall population.

Discipline rates also vary by area and race and ethnicity.  In many school districts across San Mateo County, Hispanic students are disciplined at disproportionately higher rates compared to their peers.  In most districts, Black/African American and Pacific Islander students are also overrepresented in terms of suspension rates, but these rates are slight compared to those of Hispanic students.
 Asian and Filipino students were underrepresented in terms of suspension rates.

White students were also underrepresented in discipline rates in most districts except for La Honda-Pescadero.

The demographics of faculty and staff are fairly similar to that of students.  There is a slightly larger share of White and Black/African American staff than students, meaning that Black/African American and White student groups are more likely to interact with same-race staff and faculty than other racial groups.  Asian students are less likely to interact with a same-race staff of faculty member: 17% of the student body is Asian compared to just 8% of staff and faculty.

Background
This section describes the school districts in San Mateo County, including their geographic boundaries and a brief history of the school districts’ formation. This section also includes details on how districts’ enrollments and student demographic have changed over time. 509
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 5 San Mateo County School Districts. There are three unified school districts in San Mateo County which include both elementary and high schools. These are Cabrillo Unified School District, La Honda-Pescadero Unified School District, and South San Francisco Unified School District.

In addition to the unified school districts, there are three high school districts, which include: Jefferson Union High School District, San Mateo Union High School District, and Sequoia Union High School District. The elementary schools covering these high schools’ district boundaries areas are described below:
 In the Jefferson Union High School District geographic boundary, elementary school districts are the Bayshore Elementary School District, Brisbane School District, Jefferson Elementary School District, and Pacifica School District.  Within the San Mateo Union High School District geographic boundary, elementary school districts include San Mateo-Foster City School District, Hillsborough City School District, Burlingame School District, San Bruno Park School District, and Millbrae School District.
 Within the Sequoia Union High School District geographic boundary, the elementary schools include Belmont-Redwood Shores School District, San Carlos School District, Redwood City School District, Ravenswood City School District, Menlo Park City School District, Woodside Elementary School District, Las Lomitas Elementary School District, and Portola Valley School District.

Geographic boundaries of school districts. Figure V-1 illustrates the geographic boundaries of the unified school districts as well as the three high school districts. Municipal boundaries are overlayed on the map. 510
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 6 Figure V-1.

Unified School Districts and High School Districts in San Mateo County Source: San Mateo County Office of Education.

As illustrated in the map, Cabrillo Unified School District covers Half Moon Bay and some unincorporated areas of San Mateo County. South San Francisco Unified covers South San 511
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 7 Francisco and a small portion of Daly City. La Honda-Pescadero Unified School District covers unincorporated areas of San Mateo County.

The other high school districts, Jefferson Union, San Mateo Union, and Sequoia Union, cover the remaining jurisdictions. Jefferson Union covers Brisbane, Colma, Daly City, and Pacifica. San Mateo Union covers Burlingame, Hillsborough, Millbrae, San Bruno, San Mateo City, and Foster City. Sequoia Union covers Atherton, Belmont, Redwood City, East Palo Alto, Menlo Park, San Carlos, Portola Valley, and Woodside.

The county’s elementary school districts cover the same areas as the three high school districts. Their geographic boundaries are illustrated in the map below. 512
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 8 Figure V-2.

Elementary School Districts in San Mateo County
Source: San Mateo County Office of Education.
513
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 9 Because the elementary school districts are much smaller, many jurisdictions have several elementary schools. The table blow shows each jurisdiction and their associated elementary school.

Figure V-3.

School Districts in San Mateo County’s Jurisdictions
Source: San Mateo County Office of Education.

A brief history of district formation. San Mateo County’s numerous school districts were formed over a century ago, when the county was more rural and scattered:
communities needed elementary schools close to home, and only a few students were attending high school. As young people began going to high school, individual districts often found they had too few students and resources to support their own high schools, so Jurisdiction
Atherton Sequoia Union Menlo Park City ; Las Lomitas Elementary; Redwood City
Belmont Sequoia Union Belmont-Redwood Shores
Brisbane Jefferson Union Brisbane; Bayshore Elementary
Burlingame San Mateo Union Burlingame
Colma Jefferson Union Jefferson Elementary
Daly City Jefferson Union; South San Francisco Unifie Jefferson Elementary East Palo Alto Sequoia Union Ravenswood City
Foster City San Mateo Union San Mateo-Foster City
Half Moon Bay Cabrillo Unified (none, included in Cabrillo Unified) Hillsborough San Mateo Union Hillsborough City
Menlo Park Sequoia Union Menlo Park City; Las Lomitas Elementary; Ravenswood City
Millbrae San Mateo Union Millbrae
Pacifica Jefferson Union Pacifica
Portola Valley Sequoia Union Portola Valley
Redwood City Sequoia Union Redwood City
San Bruno San Mateo Union San Bruno Park
San Carlos Sequoia Union San Carlos; Redwood City
San Mateo San Mateo Union San Mateo-Foster City
South San Francisco South San Francisco Unified (none, included in South San Francisco Unified) Woodside Sequoia Union Woodside Elementary; Portola Valley; Las Lomitas; Redwood City
Unified or High School District Elementary School District(s) 514
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 10 separate high school districts, covering the territories of two or more elementary districts, were established to meet the communities’ needs.2
Once California’s population grew and San Mateo County became more urbanized, “a jigsaw puzzle of overlapping districts evolved haphazardly.” Since 1920, the state has been pushing elementary districts to unify with the high school districts that serve their communities, citing improved educational quality and equity of opportunity. However, there has been limited success and local voters in San Mateo County have consistently resisted unification.3
Early efforts at unification were more successful in the rural communities along the coast— for example, voters approved the new Cabrillo Unified district for the area around Half Moon Bay and the La Honda-Pescadero Unified district in a 1964 election. Unification was not supported by many suburban communities edging the Bay. The county’s school district committee proposed to split each of the three high school districts and feeder schools into two or three smaller unified districts, but the State Board of Education rejected variations of those plans three times. The Board argued that the county committee’s proposals would create districts with widely varying property tax bases and could contribute to racial segregation. The State Board instead devised a plan that would create a single unified district within each of the existing high school district boundaries. Voters turned down the state plans in all three districts in June 1966, and rejected a similar proposal again in 1972.

In 1973, the Mid-Peninsula Task Force for Integrated Education petitioned the county committees to unify the elementary districts of Menlo Park, Las Lomitas, Portola Valley, Ravenswood and a portion of Sequoia Union High School District across county lines with Palo Alto Unified. Their goal was racial integration, but the county committee did not support the effort.4
Efforts against unification have persisted, leaving the county with several elementary school districts which feed into a high school, rather than a unified district. As a result, some elementary school districts have faced waning budgets and administrative hurtles.

For instance, Brisbane and Bayshore elementary school districts, at the northern end of the county, serve a little more than 1,000 students and long have struggled with tight budgets.

To rectify their budgetary concerns, the districts now share both a superintendent and a chief business officer. They also participate in a special education collaborative with the Jefferson elementary and high school districts.

According to the county’s superintendent of schools Anne Campbell, other districts may find themselves pooling their resources in the future: local identification may be strong, 2 Watson, Aleta. “How Did We End Up With 54 School Districts in San Mateo and Santa Clara Counties?” Silicon Valley Community Foundation, 2012. https://www.siliconvalleycf.org/sites/default/files/report-edu.pdf 3 Ibid.
4 Ibid.
515
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 11 she says, but financial reality is hard to ignore: “As we move forward in time, I think it’s going to be interesting to see what school districts are going to do, especially as budgets get more bleak.”5
Enrollment changes. Total public school enrollment in the county has decreased slightly, by just 1%, from the 2010-2011 academic year to 2020-2021. Figure V-4 illustrates enrollment changes by district.

Bayshore Elementary, Ravenswood City, and Portola Valley school districts experienced the largest enrollment decreases (by at least 30%) between 2010-11 and 2020-21. School districts with the largest increases in enrollments were Burlingame (22%) and BelmontRedwood Shores (30%). 5 Ibid.
516
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 12 Figure V-4.

Enrollment changes by district, 2010-11 to 2020-2021
Source: California Department of Education and Root Policy Research However, it is important to note that many of these enrollment decreases were driven by the pandemic. In fact, total enrollment in these public schools decreased by 3% between School District
Unified School Districts
Cabrillo Unified 3,352 2,934 -12%
La Honda-Pescadero 341 275 -19%
South San Francisco 9,312 8,182 -12%
High & Elementary School Districts
Jefferson Union High School 4,960 4,705 -5%
Bayshore Elementary 543 361 -34%
Brisbane Elementary 545 474 -13%
Jefferson Elementary 6,998 6,653 -5%
Pacifica 3,164 3,006 -5%
San Mateo Union High School 8,406 9,760 16%
Burlingame Elementary 2,771 3,387 22%
Hillsborough City Elementary 1,512 1,268 -16%
Millbrae Elementary 2,222 2,238 1%
San Bruno Park Elementary 2,599 2,275 -12%
San Mateo-Foster City 10,904 10,969 1%
Sequoia Union High School 8,765 10,327 18%
Belmont-Redwood Shores 3,206 4,152 30%
Las Lomitas Elementary 1,336 1,116 -16%
Menlo Park City Elementary 2,629 2,781 6%
Portola Valley Elementary 711 491 -31%
Ravenswood City Elementary 4,285 2,993 -30%
Redwood City Elementary 9,119 8,086 -11%
San Carlos Elementary 3,212 3,265 2%
Woodside Elementary 453 369 -19%
Total Enrollment 91,345 90,067 -1%
2010-2011
Enrollment
2020-2021
Enrollment Percent Change
517
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 13 2019-2020 and 2020-2021 in San Mateo County: the largest decrease of the decade. As shown in Figure V-5, enrollments actually increased steadily from 2010-2011 to 2017-2018, then began decreasing afterwards.

Figure V-5.

Public School Enrollment Changes, 2010-2011 to 2020-2021 Note: These data exclude enrollments in SBE Everest Public High School District, which in 2015 combined with the Sequoia Union High School District.

Source: California Department of Education and Root Policy Research Portola Valley and La Honda-Pescadero school districts had the largest enrollment decreases during COVID-19, with a 11% and 10% decline in enrollments, respectively. The only school district with increasing enrollments between the 2019-2020 to 2020-2021 school years was Sequoia Union High School District, with a modest 1% increase in enrollments.
518
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 14 Figure V-6.

Enrollment changes by district during COVID-19, 2019-20 to 2020-21 Source: California Department of Education and Root Policy Research.

Declining enrollments in public schools have been common across the state and country during the COVID-19 pandemic, and enrollment declines in San Mateo County are on par School District
Unified School Districts
Cabrillo Unified 3,136 2,934 -6%
La Honda-Pescadero 306 275 -10%
South San Francisco 8,438 8,182 -3%
High & Elementary School Districts
Jefferson Union High School 4,811 4,705 -2%
Bayshore Elementary 381 361 -5%
Brisbane Elementary 476 474 0%
Jefferson Elementary 6,687 6,653 -1%
Pacifica 3,110 3,006 -3%
San Mateo Union High School 9,885 9,760 -1%
Burlingame Elementary 3,534 3,387 -4%
Hillsborough City Elementary 1,290 1,268 -2%
Millbrae Elementary 2,349 2,238 -5%
San Bruno Park Elementary 2,454 2,275 -7%
San Mateo-Foster City 11,576 10,969 -5%
Sequoia Union High School 10,238 10,327 1%
Belmont-Redwood Shores 4,314 4,152 -4%
Las Lomitas Elementary 1,208 1,116 -8%
Menlo Park City Elementary 2,922 2,781 -5%
Portola Valley Elementary 551 491 -11%
Ravenswood City Elementary 3,269 2,993 -8%
Redwood City Elementary 8,530 8,086 -5%
San Carlos Elementary 3,405 3,265 -4%
Woodside Elementary 376 369 -2%
Total Enrollment 93,246 90,067 -3%
2019-2020
Enrollment
2020-2021
Enrollment Percent Change
519
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 15 with those across the state. According to a study conducted by the Public Policy Institute of California, public K–12 enrollment declined by 3% in California from the 2019-2020 school year to the 2020-2021 school year. 6
As funding is tied directly to the number of enrolled pupils, schools in San Mateo County could suffer fiscal consequences with continued declines. By law, districts are “held harmless” for declines for one year—that is, school budgets for 2020–2021 were unaffected, but continued enrollment declines could mean cuts in future years.7 Reductions in enrollments, and consequently funding, could also worsen economic inequality in the long-term by reducing students’ resources and access to opportunities.

Demographics: race & ethnicity. Over the last decade, San Mateo County’s school districts have diversified in terms of students’ race and ethnicity. Hispanic students make up the largest ethnic group in the county’s schools: 38% of students identified as Hispanic in the 2020-2021 academic school year. This is just a one percentage point increase from 2010-2011. Many other students are White (26%), though this has decreased by 3 percentage points since 2010-2011, The largest increase was in Asian students, with 17% identifying as such in 2020-2021, an increase of 5 percentage points from 2010-2011.

Other students identify as Filipino (8%), or bi- or multi-racial (8%). A small and decreasing percentage of students identify as Black/African American (1%) and Pacific Islander (2%). 6 Lafortune, Julien & Prunty, Emmanuel. “Digging into Enrollment Drops at California Public Schools.” Public Policy Institute of California. May 14, 2021. https://www.ppic.org/blog/digging-into-enrollment-drops-at-california-publicschools/ 7 Ibid.
520
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 16 Figure V-7.

Changes in Race and
Ethnicity, 2010-2011 to 2020-
2021
Note: These data exclude enrollments in SBE
Everest Public High School District, which
in 2015 combined with the Sequoia Union
High School District.

Source: California Department of Education and
Root Policy Research
:

Figure V-8 shows the racial and ethnic distribution of students enrolled in public schools by jurisdiction in 2020-2021.
 Portola Valley Elementary School District (66%) and Woodside Elementary School District (64%) had the highest share of White students, making them among the least racially and ethnically diverse districts in the county.  Ravenswood City Elementary School District and Redwood City Elementary School District had the highest share of Hispanic students, at 84% and 70%, respectively.  Ravenswood City also had the highest proportion of Pacific Islander students (7%) and Black/African American students (5%) compared to other districts.  Millbrae Elementary (46%), Hillsborough Elementary (32%), and Belmont-Redwood Shores Elementary (32%) had the highest share of Asian students.  Jefferson Elementary School District and Jefferson Union High School District had the highest portion of Filipino students, at 25% and 29% respectively. 521
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 17 Figure V-8.

Student body by Race and Ethnicity, 2020-2021
Note: In almost all school districts, less than 1% of students were Native American, so they are not included in this table.

Source: California Department of Education and Root Policy Research Enrollment changes due to COVID-19 varied by race and ethnicity. For instance, between 2019-2021, enrollment among Pacific Islander students decreased by 6% (from 1,581 students in 2019-20 to 1,484 students in 2020-21). This is substantially higher than the 3% countywide average. Enrollments among Filipino and Hispanic students decreased by 4% while enrollment among Black/African American students decreased by 2%. On the other School District
Unified School Districts
Cabrillo Unified 1% 0% 1% 52% 0% 40% 5%
La Honda-Pescadero 0% 0% 1% 63% 0% 35% 1%
South San Francisco 14% 1% 23% 48% 2% 6% 6%
High & Elementary School Districts
Jefferson Union High School 15% 1% 29% 31% 1% 14% 7%
Bayshore Elementary 19% 3% 21% 41% 4% 3% 8%
Brisbane Elementary 20% 1% 12% 28% 0% 24% 11%
Jefferson Elementary 19% 2% 25% 36% 1% 11% 5%
Pacifica 8% 1% 9% 26% 0% 39% 16%
San Mateo Union High School 23% 1% 5% 32% 2% 28% 10%
Burlingame Elementary 27% 0% 3% 16% 0% 41% 9%
Hillsborough Elementary 32% 0% 2% 5% 0% 48% 12%
Millbrae Elementary 46% 1% 6% 20% 2% 16% 8%
San Bruno Park Elementary 16% 1% 10% 41% 5% 15% 1%
San Mateo-Foster City 26% 1% 3% 37% 2% 21% 9%
Sequoia Union High School 9% 2% 1% 45% 2% 35% 5%
Belmont-Redwood Shores 32% 1% 3% 12% 1% 34% 14%
Las Lomitas Elementary 18% 1% 1% 13% 0% 53% 14%
Menlo Park City Elementary 13% 1% 1% 17% 1% 55% 11%
Portola Valley Elementary 6% 0% 0% 14% 0% 66% 13%
Ravenswood City Elementary 0% 5% 0% 84% 7% 1% 2%
Redwood City Elementary 4% 1% 1% 70% 1% 19% 4%
San Carlos Elementary 18% 1% 1% 14% 0% 49% 13%
Woodside Elementary 4% 2% 0% 16% 1% 64% 11%
Total 17% 1% 8% 38% 2% 26% 8%
Asian White
Two or
Black Filipino Hispanic more races
Pacific
Islander
522
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 18 end of the spectrum, there was a 3% increase in enrollment among White students (from 22,308 students to 23,055 students) between 2019-20 and 2020-21. Similarly, there was a 1% increase in enrollment among Asian students and a 4% increase among students of two or more races.

Figure V-9.

Enrollment Changes by Race and Ethnicity, San Mateo County, 2019-20 to 2020-21
Source: California Department of Education and Root Policy Research While many of their families may have simply moved out of San Mateo County during the pandemic, it is possible that Black/African American, Filipino, Hispanic, and Pacific Islander students are otherwise slipping through the cracks of the education system during this period.

Demographics: students with extenuating circumstances. Several students in the county’s public schools are facing additional hurtles to educational ease.

Many are English learners, qualify for reduced lunch, are foster children, are experiencing homelessness, have a disability, or are migrants. Students in these groups often have hindrances to excelling in school because of detrimental circumstances beyond their control. These include financial and social hardships as well as problems within students' families.

Qualification for free and reduced lunch is often used as a proxy for extenuating circumstances. Qualifications are determined based on household size and income. For instance, in the 2020-2021 academic year, students from a household of three making less 523
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 19 than $40,182 annually qualified for reduced price meals, and those making less than $28,236 in a household of three qualified for free meals.8 Free and reduced lunch disparities. Overall, 29% of public school students in San Mateo County qualify for reduced or free lunch. This rate was substantially lower in districts like Hillsborough Elementary, San Carlos Elementary, Portola Valley Elementary, Las Lomitas Elementary, Belmont-Redwood Shores, and Menlo Park City Elementary, where each had less than 10% of students qualify for free or reduced lunch.

The rate of reduced lunch qualification was far higher in Ravenswood City Elementary School District, where 83% of students qualify for reduced lunch.

Disparities in homelessness. In Ravenswood City Elementary, 30% of students are experiencing homelessness. This is an outlier in the county, where overall just 2% are experiencing homelessness. The school district has received media attention due to its astronomically high rate of students experiencing homelessness. Some have noted that rates of homelessness have increased due to escalating costs of living in an area surrounded by affluence.
9 Others have highlighted that ”Having a roof over your head, having a safe place to sleep and study, is fundamental to absolutely everything," and have noted that students who experience homelessness have higher dropout rates and are more likely to experience homelessness as adults.10
School moves related to evictions. Currently, students whose families have been evicted do not have protections allowing them to remain in their current school district.

This means that precarious housing also means precarious schooling for many of the county’s students. Frequent moves by students are closely related to lower educational proficiency.

In the City of San Francisco, a 2010 ordinance protects some students from being evicted during the school year; however, it only relates to owner/relative move-in evictions.11 Children in families who are evicted for other reasons may need to move schools or districts when their housing is lost.

English language learners. Countywide, 20% of public school students are English learners. Again, this rate is highest at Ravenswood City Elementary, where 53% of students are English learners. La Honda-Pescadero Unified School District, Jefferson Union High 8 “Income Eligibility Scales for School Year 2020-2021.” California Department of Education. 9 Bartley, Kaitlyn. “Homelessness: The shadow that hangs over students in this Bay Area school district.” The Mercury News. December 2018.
10 Jones, Carolyn. “California schools see big jump in homeless students.” Palo Alto Online. October 2020. 11 https://sfrb.org/new-amendment-prohibiting-owner-move-evictions-minor-children-during-school-year 524
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 20 School, and Redwood City Elementary also have high rates of English learners, representing more than a third of students.

Less than one percent of students in San Mateo County public school districts are foster youth or migrants. Cabrillo Unified School District had the highest rate of migrant students at 3%. La Honda-Pescadero had the highest rate of foster children at 2%.

School districts without large low income populations also tend to serve very few English language learners. For instance, in Hillsborough Elementary where 0% of students qualify for reduced lunch, only 1% of students are English language learners. 525
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 21 Figure V-10.

Students with Extenuating Circumstances, 2020-2021
Source: California Department of Education and Root Policy Research The overall share of students in these groups has not changed drastically over time. As shown in Figure V-11, there have been slight decreases in the share of students who are English learners and the share of students who qualify for reduced lunch from 2016-2017 School District
Unified School Districts
Cabrillo Unified 20% 37% 0% 2% 3%
La Honda-Pescadero 38% 38% 2% 1% 1%
South San Francisco 21% 34% 0% 1% 1%
High & Elementary School Districts
Jefferson Union High School 36% 44% 0% 0% 0%
Bayshore Elementary 30% 57% 0% 0% 0%
Brisbane Elementary 16% 19% 0% 0% 0%
Jefferson Elementary 14% 27% 0% 1% 0%
Pacifica 9% 18% 0% 1% 0%
San Mateo Union High School 10% 21% 0% 0% 0%
Burlingame Elementary 13% 11% 0% 0% 0%
Hillsborough Elementary 1% 0% 0% 0% 0%
Millbrae Elementary 19% 25% 0% 0% 0%
San Bruno Park Elementary 29% 18% 0% 0% 0%
San Mateo-Foster City 26% 28% 0% 2% 0%
Sequoia Union High School 15% 30% 0% 0% 0%
Belmont-Redwood Shores 10% 7% 0% 0% 0%
Las Lomitas Elementary 7% 6% 0% 0% 0%
Menlo Park City Elementary 6% 7% 0% 0% 0%
Portola Valley Elementary 4% 5% 0% 0% 0%
Ravenswood City Elementary 53% 83% 0% 30% 0%
Redwood City Elementary 38% 56% 0% 2% 1%
San Carlos Elementary 5% 6% 0% 0% 0%
Woodside Elementary 8% 10% 0% 0% 0%
Total 20% 29% <1% 2% <1%
Migrant
Reduced
Lunch
English
Learners
Foster
Children Homeless
526
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 22 to 2020-2021. Around 2% of students in the county are homeless and this has not changed between 2016-2017 and 2020-2021. Foster youth and migrant students are not shown in the figure, as both have hovered at less than 1% from year to year.

Figure V-11.

Changes in rates of English
Leaners, Reduced Lunch,
and Homelessness, 2016-
2017 to 2020-2021
Note: These data exclude enrollments in SBE
Everest Public High School District, which
in 2015 combined with the Sequoia Union
High School District.

Source: California Department of Education and
Root Policy Research
:

During COVID-19, enrollments decreased by 3% between 2019-2020 and 2020-2021 school years, as families withdrew or did not reenroll their children from public schools.

Enrollment among migrant students decreased much more drastically, by 16% (from 332 students to 279 students). Similarly, enrollment among students who qualify for reduced lunch declined at a higher rate (10%) than the overall student population. Foster children and English learners also experienced enrollment decreases at a rate higher than the total population, with 7% and 10% decreases in enrollment, respectively. 527
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 23 Figure V-12.

Enrollment Changes by Extenuating Circumstance, San Mateo County, 2019-2020 to 2020-2021
Source: California Department of Education and Root Policy Research Achievement Gaps
This section details achievement gaps within school districts. Gaps are measured by test scores, meeting California State University or University of California admissions standards, and college-going rates.

Test scores. Figure V-13 indicates the percent of students who met or exceeded English and mathematics testing standards set by the California State Assessment of Student Performance and Progress. Overall, 62% of students in the county met or exceeded English testing standards and 52% met or exceeded mathematics testing standards.

Of all the districts with high schools, San Mateo Union High School District had the highest student pass rates: 70% of their students met or exceeded standards in English testing and 50% met or exceeded standards in mathematics testing.

Among elementary school districts, Portola Valley Elementary School District and Woodside Elementary School District had the highest rates of success in English, with 87% and 88% of students meeting or exceeding English testing standards, respectively. Woodside Elementary School District and Hillsborough Elementary School District had the highest rates of success in mathematics, with 84% and 85% meeting math testing standards, respectively.

In every school district, girls scored higher on English tests than boys. Overall, girls met or exceeded English testing at a rate of 67% while boys met or exceeded English testing at a rate of 57%. The largest gender gap was in Brisbane Elementary School District, where 72% 528
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 24 of girls met or exceeded English testing standards and just 56% of boys did: a gap of 16 percentage points.

Gender gaps in mathematics were less pronounced, but largest gender gaps were in Cabrillo Unified School District and in La Honda Pescadero Unified School District. In Cabrillo Unified, girls passed mathematics at a rate 7% higher than boys, while in La Honda-Pescadero, boys passed at a rate 6% higher than girls.

Figure V-14.

Students who Met or Exceeded Testing Standards, by Gender and District, 2018-2019
Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research The gender gap in test scores has started to close in recent years, as indicated in Figure V15. In 2014-2015 there was a 11 percentage point gap in girls’ and boys’ English testing pass District
Unified School Districts
Cabrillo Unified 48% 41% 55% 34% 31% 38%
La Honda-Pescadero 43% 36% 49% 31% 34% 28%
South San Francisco 52% 45% 60% 44% 42% 45%
High & Elementary School Districts
Jefferson Union High School 57% 52% 63% 37% 38% 35%
Bayshore Elementary 27% 24% 31% 27% 27% 28%
Brisbane Elementary 64% 56% 72% 54% 56% 53%
Jefferson Elementary 48% 43% 54% 37% 39% 35%
Pacifica 60% 55% 65% 57% 57% 57%
San Mateo Union High School 70% 66% 76% 50% 50% 50%
Burlingame Elementary 80% 75% 84% 78% 78% 78%
Hillsborough Elementary 85% 81% 89% 85% 86% 84%
Millbrae Elementary 63% 57% 70% 58% 58% 58%
San Bruno Park Elementary 50% 47% 53% 41% 43% 38%
San Mateo-Foster City 62% 58% 67% 56% 56% 56%
Sequoia Union High School 68% 64% 72% 50% 50% 50%
Belmont-Redwood Shores 82% 78% 86% 79% 78% 80%
Las Lomitas Elementary 86% 84% 88% 82% 84% 80%
Menlo Park City Elementary 84% 81% 87% 83% 82% 83%
Portola Valley Elementary 87% 83% 91% 83% 84% 82%
Ravenswood City Elementary 22% 20% 23% 15% 16% 13%
Redwood City Elementary 54% 49% 59% 46% 46% 46%
San Carlos Elementary 80% 77% 83% 75% 76% 74%
Woodside Elementary 88% 85% 91% 84% 85% 83%
Total 62% 57% 67% 52% 52% 52%
English Language Arts/Literacy Mathematics
Total Boys Girls Total Boys Girls
529
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 25 rates, and by 2018-2019 this was just a 10 percentage point gap. The figure also indicates that there have been steady gains in the share of students meeting or exceeding testing standards in the county.

Figure V-15.

Students who Met or Exceeded Testing Standards, by Gender, 2014-2015 to 2018-2019
Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research Very large gaps in test scores by race and ethnicity exist among students in some areas.

Figure V-16 illustrates the rate at which students of various racial and ethnic groups met or exceeded English testing standards.

For the past five years in San Mateo County, Asian, White, and Filipino students have met or exceeded English testing standards at rates higher than the overall student population.

Hispanic, Black/African American, and Pacific Islander students, on the other hand, have been underserved in this realm and have consistently scored lower than the overall student body.

However, across all groups, the rate at which students met or exceed English testing standards has increased since the 2014-2015 school year. Hispanic students have made the largest percentage point gain: 34% met standards in 2014-2015 and 40% met standards in 2019-19, an increase of six percentage points.
530
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 26 Figure V-16.

Students who Met or Exceeded English Testing Standards, by Race and Ethnicity, 2014-2015 to 2018-2019
Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research A similar narrative holds in Math testing standards, where scores have improved among each racial and ethnic group from 2014-2015 to 2018-2019. Again, White and Asian students meet or exceed math testing standards at rates higher than the overall population while Hispanic, Pacific Islander, and Black/African American students scored lower.

White and Hispanic students have seen the biggest increases in rates of mathematics success: both have experienced a five percentage point increase in the percent of students who met or exceeded math testing standards.
531
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 27 Figure V-17.

Students who Met or Exceeded mathematics testing standards, by Race and Ethnicity, 2014-2015 to 2018-2019
Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research Figure V-18 illustrates the rates at which students of various racial and ethnic groups met or exceeded mathematics testing standards by district.

There were several districts in which the gaps between the overall test pass rates and a specific racial groups’ pass rates were especially wide. For instance, in San Carlos Elementary School District, 75% of the total student body met or exceeded math testing standards, but only 11% of Black/African American students met or exceeded math testing standards— a gap of 64 percentage points.

Other school districts with wide gaps between Black/African American and overall math testing success were Las Lomitas Elementary (46 percentage point gap), Menlo Park City Elementary (43 percentage point gap), and Belmont-Redwood Shores (42 percentage point gap).

Some school districts also had similar gaps in Pacific Islander students’ math passing rates and overall passing rates. For instance, in Menlo Park City Elementary School District, 83% of the student body met or exceeded mathematics testing standards but just 35% of Pacific Islander students passed or exceeded mathematics testing standards—a gap of 48 532
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 28 percentage points. Millbrae Elementary School District also had a 47 percentage point gap between Pacific Islander students’ and total students’ math test rates.

Figure V-18.

Students who Met or Exceeded Mathematics Testing Standards, by Race/Ethnicity and District, 2018-2019
Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research Although racial gaps in English testing were less pronounced, San Carlos Elementary School District also had a wide gap between the total student body and Black/African American School District
Unified School Districts
Cabrillo Unified 34% 65% (no data) 38% 16% (no data) 54% La Honda-Pescadero 31% (no data) (no data) (no data) 20% (no data) 46% South San Francisco 44% 75% 19% 60% 29% 33% 46%
High & Elementary School Districts
Jefferson Union High School 37% 75% (no data) 36% 17% (no data) 42% Bayshore Elementary 27% 44% (no data) 38% 17% 14% (no data) Brisbane Elementary 54% 67% (no data) 65% 38% (no data) 60% Jefferson Elementary 37% 61% 15% 42% 23% 20% 30%
Pacifica 57% 74% 38% 48% 38% (no data) 66%
San Mateo Union High School 50% 84% (no data) 46% 22% 20% 63% Burlingame Elementary 78% 92% 53% 66% 50% (no data) 81% Hillsborough Elementary 85% 92% (no data) (no data) 76% (no data) 82% Millbrae Elementary 58% 75% 31% 63% 27% 11% 51%
San Bruno Park Elementary 41% 69% 23% 64% 25% 27% 50%
San Mateo-Foster City 56% 87% 30% 61% 23% 27% 69%
Sequoia Union High School 50% 81% 18% 53% 22% 11% 76%
Belmont-Redwood Shores 79% 92% 37% 77% 52% 43% 79%
Las Lomitas Elementary 82% 93% 36% (no data) 44% (no data) 87% Menlo Park City Elementary 83% 94% 40% (no data) 55% 35% 88% Portola Valley Elementary 83% 89% (no data) (no data) 56% (no data) 89% Ravenswood City Elementary 15% (no data) 9% (no data) 15% 11% (no data) Redwood City Elementary 46% 92% 22% 76% 34% 44% 75%
San Carlos Elementary 75% 91% 11% 85% 51% (no data) 78% Woodside Elementary 84% 92% (no data) (no data) 52% (no data) 89% Total 52% 82% 18% 50% 27% 21% 71%
Overall Asian Black Filipino Hispanic White
Pacific
Islander
533
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 29 students. Namely, 80% of the student body met or exceeded English testing standards, but only 19% of Black/African American students met or exceeded testing standards—a 61 percentage point gap. Las Lomitas Elementary had a 41 percentage point gap between overall English testing success and Black/African American English testing success.

Other districts had large gaps between the total student body’s English test scores and Pacific Islander students’ test scores. Namely, in Menlo Park City Elementary School District 84% of students met or exceeded English testing standards, but only 40% of Pacific Islander students—a 44 percentage point gap.
534
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 30 Figure V-19.

Students who Met or Exceeded English Testing Standards, by Race/Ethnicity and District, 2018-2019
Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research Students with extenuating circumstances across all districts met or exceeded testing standards at lower rates. However, some districts had especially wide disparities between overall test scores and test scores of students with extenuating circumstances.

School District
Unified School Districts
Cabrillo Unified 48% 78% (no data) 54% 28% (no data) 71% La Honda-Pescadero 43% (no data) (no data) (no data) 27% (no data) 61% South San Francisco 52% 76% 36% 66% 38% 44% 56%
High & Elementary School Districts
Jefferson Union High School 57% 81% (no data) 60% 43% (no data) 59% Bayshore Elementary 27% 49% (no data) 33% 20% 14% (no data) Brisbane Elementary 64% 63% (no data) 75% 51% (no data) 79% Jefferson Elementary 48% 62% 28% 59% 34% 33% 43%
Pacifica 60% 65% 32% 52% 45% (no data) 68%
San Mateo Union High School 70% 88% 55% 79% 50% 34% 81% Burlingame Elementary 80% 88% 61% 73% 55% (no data) 83% Hillsborough Elementary 85% 89% (no data) (no data) 77% (no data) 83% Millbrae Elementary 63% 74% 46% 68% 42% 23% 61%
San Bruno Park Elementary 50% 72% 39% 76% 36% 31% 56%
San Mateo-Foster City 62% 85% 41% 68% 34% 37% 77%
Sequoia Union High School 68% 87% 44% 92% 47% 31% 88%
Belmont-Redwood Shores 82% 91% 44% 81% 64% 61% 83%
Las Lomitas Elementary 86% 91% 45% (no data) 65% (no data) 89% Menlo Park City Elementary 84% 92% 60% (no data) 62% 40% 88% Portola Valley Elementary 87% 92% (no data) (no data) 58% (no data) 93% Ravenswood City Elementary 22% (no data) 24% (no data) 21% 18% (no data) Redwood City Elementary 54% 91% 35% 73% 43% 47% 83%
San Carlos Elementary 80% 90% 19% 76% 60% (no data) 83% Woodside Elementary 88% 92% (no data) (no data) 58% (no data) 92% Total 62% 82% 34% 64% 40% 31% 79%
Overall Asian Black Filipino Hispanic White
Pacific
Islander
535
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 31 For example, English learning students in Portola Valley Elementary, Woodside Elementary, Menlo Park City Elementary, and Brisbane Elementary each met or exceeded mathematics test standards at a rate at least 50 percentage points below the overall test rate in each district. English learning students in Las Lomitas Elementary (54%) had the highest mathematics pass rates, followed by those in Belmont-Redwood Shores (42%) and Burlingame Elementary (40%).

Students with disabilities scored especially high on mathematics tests in Hillsborough Elementary, where 48% met or exceeded standards. Others in Belmont-Redwood Shores (43%) and Woodside Elementary (41%) had high pass rates as well. Students with disabilities in San Carlos Elementary and Las Lomitas Elementary school districts scored far below the overall student body: in these districts, students with disabilities met or exceeded mathematics test standards at 54 percentage points below the overall test rate.

In Jefferson Elementary and Ravenswood Elementary students experiencing homelessness passed math tests at a rate similar to their housed peers. In other districts, however, students experiencing homelessness often scored substantially lower. School districts with the widest math testing gaps between the overall student body and students experiencing homelessness were San Mateo-Foster City and Millbrae Elementary, with a 41 percentage point gap and 42 percentage point gap, respectively.
536
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 32 Figure V-20.

Students who Met or Exceeded Math Testing Standards, by Special Case and District, 2018-2019
Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research School District
Unified School Districts
Cabrillo Unified 34% 4% 5% 4% 9%
La Honda-Pescadero 31% 4% (no data) (no data) 2%
South San Francisco 44% 20% 25% 4% 18%
High & Elementary School Districts
Jefferson Union High School 37% 5% (no data) (no data) 6% Bayshore Elementary 27% 11% (no data) (no data) 9%
Brisbane Elementary 54% 4% (no data) (no data) 12%
Jefferson Elementary 37% 15% 36% (no data) 11%
Pacifica 57% 22% (no data) (no data) 17%
San Mateo Union High School 50% 10% (no data) (no data) 13% Burlingame Elementary 78% 40% (no data) (no data) 29%
Hillsborough Elementary 85% (no data) (no data) (no data) 48% Millbrae Elementary 58% 26% 16% (no data) 25%
San Bruno Park Elementary 41% 12% (no data) (no data) 9% San Mateo-Foster City 56% 11% 15% (no data) 14%
Sequoia Union High School 50% 3% 33% (no data) 9%
Belmont-Redwood Shores 79% 42% (no data) (no data) 43%
Las Lomitas Elementary 82% 54% (no data) (no data) 28%
Menlo Park City Elementary 83% 31% (no data) (no data) 38% Portola Valley Elementary 83% 14% (no data) (no data) 39% Ravenswood City Elementary 15% 5% 11% (no data) 2%
Redwood City Elementary 46% 14% (no data) 29% 14%
San Carlos Elementary 75% 24% (no data) (no data) 21%
Woodside Elementary 84% 27% (no data) (no data) 41%
English
Learners
Experiencing
homelessness Migrant
With
Overall Disabilities
537
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 33 Students with extenuating circumstances also consistently scored lower in English testing than the overall student body.

For instance, English learning students in San Mateo Union High School District, Hillsborough Elementary School District, Sequoia Union High School District, Menlo Park City Elementary School District, and Portola Valley Elementary School District met or exceeded English test standards at a rate at least 60 percentage points below the overall test rate in each district. Hillsborough Elementary had the largest gap at 85 percentage points. Las Lomitas Elementary had the highest success rate among English learners, where 50% met or exceeded English testing standards.

However, students with disabilities in Las Lomitas Elementary and San Carlos Elementary school districts met or exceeded English test standards at rate 55 and 51 percentage points below the overall test rate, respectively. These were the largest gaps in the county.

Students with disabilities at Woodside Elementary did the best on English testing, where 56% passed or exceeded standards.

Among students experiencing homelessness, those at Sequoia Union High School were most likely to meet English testing standards, with 42% meeting or exceeding standards.

The school district with the widest gap between overall English test scores and scores among students experiencing homelessness was Cabrillo Unified with a 34 percentage point gap.

Just three districts reported English testing scores among migrant students. Redwood City Elementary had the highest pass rate at 34% and Cabrillo Unified had the lowest at 16%. 538
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 34 Figure V-21.

Students who Met or Exceeded English Testing Standards, by Special Case and District, 2018-2019
Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research School District
Unified School Districts
Cabrillo Unified 48% 9% 14% 16% 12%
La Honda-Pescadero 43% 9% (no data) (no data) 9%
South San Francisco 52% 21% 35% 20% 18%
High & Elementary School Districts
Jefferson Union High School 57% 3% (no data) (no data) 19% Bayshore Elementary 27% 3% (no data) (no data) 4%
Brisbane Elementary 64% 21% (no data) (no data) 16%
Jefferson Elementary 48% 16% 30% (no data) 15%
Pacifica 60% 12% (no data) (no data) 15%
San Mateo Union High School 70% 11% (no data) (no data) 27% Burlingame Elementary 80% 33% (no data) (no data) 33%
Hillsborough Elementary 85% (no data) (no data) (no data) 47% Millbrae Elementary 63% 19% 34% (no data) 23%
San Bruno Park Elementary 50% 14% (no data) (no data) 12% San Mateo-Foster City 62% 9% 33% (no data) 15%
Sequoia Union High School 68% 8% 42% (no data) 27%
Belmont-Redwood Shores 82% 31% (no data) (no data) 45%
Las Lomitas Elementary 86% 51% (no data) (no data) 31%
Menlo Park City Elementary 84% 21% (no data) (no data) 42% Portola Valley Elementary 87% 17% (no data) (no data) 37% Ravenswood City Elementary 22% 6% 16% (no data) 5%
Redwood City Elementary 54% 13% (no data) 34% 16%
San Carlos Elementary 80% 29% (no data) (no data) 28%
Woodside Elementary 88% 18% (no data) (no data) 56%
English
Learners
Experiencing
homelessness Migrant
With
Overall Disabilities
539
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 35 Students who met university requirements. Many high schoolers in the county met admission standards for a University of California (UC) or California State University (CSU) school. Figure V-22 illustrates the percentage of cohort graduates who met admission requirements for a CSU or UC school according to California Department of Education data.

Of the high school districts in San Mateo County, Sequoia Union had the highest rate of graduates who met such admission standards, at 69%. On the other end of the spectrum, Cabrillo Unified and South San Francisco Unified had the lowest rates at 41%.

Figure V-22.

Students Meeting
California University
Admission
Standards, 2019-
2020
Source:

California Department of Education
and Root Policy Research.

Cabrillo Unified and South San Francisco Unified have experienced a decrease in the share of graduates meeting CSU or UC admission standards in recent years. For instance, in 2016-2017, 57% of South San Francisco Unified graduates met these standards, but this decreased by 16 percentage points by 2019-2020. Cabrillo Unified experienced a less drastic decrease over the same period, but the rate still shrunk by two percentage points.

Jefferson Union High School District had the most drastic increase in the share of graduates meeting CSU or UC standards: just 21% of students met these standards in 2016-2017 compared to 48% of students in 2019-2020. La Honda-Pescadero Unified School District experienced a 10 percentage point increase in this success rate over the same period.

Sequoia Union and San Mateo Union experienced more modest increases, but remain the districts with the highest rates of students meeting CSU and UC standards. 540
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 36 Figure V-23.

Students Meeting
University
Admission
Standards, 2016-
2017 and 2019-2020
Source:

California Department of Education
and Root Policy Research.

Rates at which students met CSU or UC admissions standards varied substantially by race and ethnicity in 2019-2020. In all high school districts in San Mateo County, White and Asian students meet CSU and UC admissions standards at higher rates than the overall student population.

The largest gap is in South San Francisco Unified, where just 41% of students meet CSU or UC admissions standards, but 73% of Asian students meet those standards—a 32 percentage point gap.

On the other end of the spectrum, Black/African American students typically met CSU or UC admissions standards at lower-than-average rates. The largest gap was in San Mateo Union, where just 29% of Black/African American students met CSU or UC standards compared to 68% of students in the district overall.

Filipino students typically met admissions standards at rates similar to the overall student body. For instance, in Jefferson Union, San Mateo Union, and South San Francisco Unified, Filipino students are slightly more likely to have meet CSU and UC standards than the overall student population. In Sequoia Union, they are slightly less likely to have met admission standards than the overall student population. 541
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 37 In La Honda-Pescadero, Hispanic students are slightly more likely to have met CSU or UC standards than the overall student body. However, in all other school districts, Hispanic students are less likely to have met CSU and UC standards than the overall student body.

The largest disparity is in San Mateo Union, where just 46% of Hispanic students meet the university admissions standards compared to 68% of students overall.

Finally, Pacific Islander students in Jefferson Union were slightly more likely to have met California university admissions standards compared to the overall student body, but in Sequoia Union and San Mateo Union they were substantially less likely. 542
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 38 Figure V-24.

Students Meeting University Admission Standards, by Race and Ethnicity, 2019-2020
Source: California Department of Education and Root Policy Research As expected, students with extenuating circumstances were less likely to meet CSU or UC admissions standards than students in the county overall. In all school districts where data are available, students with disabilities, students experiencing homelessness, English learners, foster youth, and migrant students met CSU or UC admission standards at lower rates than the overall student population.
543
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 39 English learners in Sequoia Union and San Mateo Regional met CSU or UC admission standards at higher rates than their peers in other school districts. However, compared to the overall student body within their own school districts, they had a larger gap than other districts. Namely, in Sequoia Union, 69% of students met admissions standards compared to just 32% of students learning English— a 37 percentage point gap.

Similarly, students with disabilities in Sequoia Union had the highest rate of meeting admissions standards (31%) compared to peers with disabilities in other districts, but also had the largest gap (38 percentage points) compared to the district’s overall student body.

Migrant students met admission standards at the lowest rate in South San Francisco Unified (27%) and at the highest rate in Sequoia Union (45%). However, in Cabrillo Unified, their rates were only eight percentage points lower than that of the overall student body, the smallest gap in the county.

Approximately 36% of students experiencing homelessness in Sequoia Union met CSU or UC admission standards, which was higher than rates in San Mateo Union (21%) and Jefferson Union (21%).

Just San Mateo Union and Sequoia Union had enough foster youth to report their rate of meeting CSU or UC admission standards. In Sequoia Union, 29% met admissions standards and 22% in San Mateo Union met admissions standards.
544
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 40 Figure V-25.

Students Meeting
University
Admission
Standards, 2019-
2020
Source:

California Department of Education
and Root Policy Research.

Notes; La-Honda Pescadero Unified
is excluded from these data as they
do not report admission standards
data for these special groups, likely
due to small sample size.

College-going rates. The college-going rate is defined as the percentage of public high school students who completed high school in a given year and subsequently enrolled in any public or private postsecondary institution (in-state or out-of-state) in the United States within 12 or 16 months of completing high school.

Most school districts in the county have a college-going rate at 70% or higher. San Mateo Union had the highest college-going rate at 77%. La Honda-Pescadero School District is the notable exception, with just 32% of graduates attending college within 12 or 16 months. 545
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 41 Figure V-26.

College-Going
Rates, 2017-2018
Source:

California Department of Education
and Root Policy Research.

As shown in Figure V-27, La Honda-Pescadero School District previously had the highest college-going rate of all the county’s high school districts, with an 80% college-going rate in 2014-2015 and a 93% college-going rate in 2015-2016. The district experienced a rapid decline in college-going rates, starting in 2016-2017. However, La Honda-Pescadero has especially small sample sizes. For instance, the district had just 26 twelfth-graders in the 2017-2018 school year, meaning that just a couple students going to college (or not) drastically alters the college-going rate in La Honda-Pescadero. All other high school districts in the county have maintained relatively consistent college-going rates. 546
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 42 Figure V-27.

College-Going
Rates, 2014-2015 to
2017-2018
Source:

California Department of Education
and Root Policy Research.

Within each of the high school districts, college-going rates vary by race and ethnicity.  In every district, White students have a higher college-going rate than Hispanic students, but the largest gaps are in South San Francisco United, where 91% of White students go to college compared to just 68% of Hispanic students, a 23 percentage point gap. Jefferson Union has the smallest gap between the two groups: 77% of White students go to college compared to 71% of Hispanic students.  Among Black/African American students, those at San Mateo Union have the highest college-going rate at 82%. Those at Jefferson Union have the lowest at just 53%, which is 24 percentage points lower than that of White students and 34 percentage points lower than that of Asian students.
 Overall, Asian students have among the highest college-going-rates in the county.

The rate is especially high in South San Francisco Unified, where 92% go to college.

The rate is lowest in Sequoia Union High School District, where 84% go to college. 547
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 43  Filipino students also have generally high rates of college-going. The highest college-going rate among Filipino students is in Sequoia Union (86%) and the lowest is in South San Francisco Unified (73%).
 College-going rates for Pacific Islander students vary substantially by district. For instance, in Sequoia Union 54% go to college, but in South San Francisco Unified 92% go to college.

Figure V-28.

College-going Rates by Race and Ethnicity, 2017-18
Note: Cabrillo Unified and La Honda- Pescadero Unified are not included here because they do not report the data, likely due to small sample sizes.

Source: California Department of Education and Root Policy Research 548
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 44 College-going rates are lower for students with disabilities and those learning English compared to the overall student population across the county.  For instance, the largest gap between overall college-going rates and English learners’ college-going rates is in South San Francisco Unified, where just 52% of English learning students go to college as opposed to 74% of the overall student population— a 22 percentage point gap. Among English learners, San Mateo Union High School District had the highest college-going rate, where 63% of English learners go to college.
 Among students with disabilities, South San Francisco Unified also had the largest gap, where 59% of students with disabilities went to college compared to 74% of the overall student population — a 15 percentage point gap. Jefferson Union, on the other hand, had a relatively high college-going rate among students with disabilities that was not very different from the district’s overall college-going rate: 71% went to college which is just five percentage points lower than the district’s overall student population.

Figure V-29.

College-going Rates
for English Learners
and Students with
Disabilities, 2017-
2018
Note:

Cabrillo Unified and La HondaPescadero Unified are not included here because they do not report the
data, likely due to small sample
sizes.

Source:

California Department of Education
and Root Policy Research.

Gaps in college enrollment by race, ethnicity, disability status, or English learning have stark financial consequences for students in the long-term. Figure V-30 illustrates median annual earnings by educational attainment. College degrees are especially important in San Mateo County: those with a bachelor’s degree in the county earn 115% more than those with a high school diploma. This gap is wider in San Mateo County than in other parts of California 549
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 45 and nationwide. The differences between high-school graduate earnings and bachelor's degree earnings are around 100% in California and 76% in the US overall.

Figure V-30.

Median Annual Earnings by Educational Attainment, 2019
Source: 5-year 2019 American Community Surveys Data.

Unfortunately, the gap between high school graduates’ and college graduates’ earnings have been increasing in San Mateo County. As illustrated in Figure V-31, median earnings for high school graduates increased by just 15% over the last decade (from $31,816 to $36,747) while earnings for college graduates increased by 29% over the same period (from $61,485 to $79,080).
550
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 46 Figure V-31.

Median Annual Earnings by Educational Attainment in San Mateo County, 2010 to 2019
Source: 5-year American Community Surveys Data.

Because income disparities between college graduates and high school graduates have been increasing, it is increasingly important that school districts in San Mateo County address differences in college-going rates stratified by race, ethnicity, and extenuating circumstances.

Barriers to Success
Many students are unable to achieve academic success because of barriers in home and school. This section explores the available indicators of barriers to success, including chronic absenteeism and dropout rates. It also describes inequities in discipline rates by 551
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 47 race and ethnicity, which has been linked both to discrimination by education professionals as well as a major barrier to students’ future success.

Chronic absenteeism. Academic studies have found that if a student is chronically absent, it reduces their math and reading achievement outcomes, educational engagement, and social engagement.12 Chronic absenteeism also has spillover effects and negatively impacts students who themselves are not chronically absent. For instance, one study found that students suffer academically from having chronically absent classmates— as exhibited across both reading and math testing outcomes.13 Students are considered chronically absent if they were absent for 10% or more of the days during a school year. Note, however, students are exempt from chronic absenteeism calculations if they receive instruction through a home or hospital instructional setting, are attending community college full-time, or were not expected to attend more than 31 days.

In the county overall, 10% of students were chronically absent during the 2018-2019 school year.
14 This is a slight increase from the 2016-2017 school year, where just 9% of students overall were chronically absent.

Chronic absenteeism rates were higher in districts with a large number of students experiencing economic and housing precarity. For instance, Ravenswood Elementary, which has a 30% rate of homelessness among students, had one of the higher rates of chronic absenteeism at 16%. La Honda-Pescadero and Sequoia Union high school districts also had high rates of chronically absent students at 16% and 17%, respectively.

When disaggregating by race and ethnicity, just 3% of Asian students were chronically absent, and 7% of White and Filipino students were chronically absent. On the other end of the spectrum, Pacific Islander students (26%), Black/African American students (18%), and Hispanic students (15%) had notably higher rates of chronic absenteeism than the overall student population (10%). Chronic absenteeism among Pacific Islander students has increased in recent years, as illustrated in Figure V-32. 12 Gottfried, Michael A. "Chronic absenteeism and its effects on students’ academic and socioemotional outcomes." Journal of Education for Students Placed at Risk (JESPAR) 19.2 (2014): 53-75. 13 Gottfried, Michael A. "Chronic absenteeism in the classroom context: Effects on achievement." Urban Education 54.1 (2019): 3-34.
14 Because of the physical school closures during the COVID-19 pandemic, the California Department of Education determined that 2019–2020 absenteeism data are not valid, therefore, we present data from the 2018-2019 school year.
552
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 48 Figure V-32.

Chronic
Absenteeism by
Race/Ethnicity,
2016-2017 to 2018-
2019
Source: California Department of
Education and Root Policy
Research
Chronic absenteeism among Pacific Islander students was especially pronounced in San Mateo-Foster City school district where there was a 26 percentage point gap between chronic absenteeism rates for Pacific Islander students (32%) and the overall student body (6%). Other districts had similarly large gaps, including San Bruno Park Elementary (20 percentage points) and South San Francisco Unified (18 percentage points).

Some districts had larger gaps in absenteeism rates between Black/African American students and the overall population. For instance, in San Carlos Elementary, 4% of the overall student body is chronically absent compared to 27% of Black/African American students— a 23 percentage point gap. Jefferson Elementary school district had a 17 percentage point gap between their overall chronic absenteeism rate (12%) and their chronic absenteeism rate among Black/African American students (28%).

Among White students, Bayshore Elementary School District was a major outlier, where 46% of White students were chronically absent compared to just 12% of the total student population. However, it is important to note that this represents a very small sample of White students: just 3% of students at Bayshore Elementary are White, one of lowest in the county.
553
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 49 Figure V-33.

Chronic Absenteeism by District and Race/Ethnicity, 2018-2019 Source: California Department of Education and Root Policy Research In most districts, chronic absenteeism is higher among students with disabilities. In fact, only Bayshore Elementary’s students with disabilities had a lower rate of chronic absenteeism than the overall student body. In all other districts, students with disabilities were more likely to be chronically absent than the overall student population. This was particularly true in Sequoia Union High School District, Jefferson Union High School District, and San Mateo Union High School District, which had gaps between the overall School District
Unified School Districts
Cabrillo Unified 10% 5% (no data) 5% 11% (no data) 10%
La Honda-Pescadero 16% (no data) (no data) (no data) 14% (no data) 18% South San Francisco 13% 4% 16% 7% 17% 31% 12%
High & Elementary School Districts
Jefferson Union High School 15% 8% 22% 11% 22% 18% 15%
Bayshore Elementary 12% 5% 12% 0% 18% 19% 46%
Brisbane Elementary 12% 3% (no data) 12% 17% (no data) 17% Jefferson Elementary 12% 5% 28% 6% 13% 25% 23%
Pacifica 7% 4% 12% 6% 9% 21% 7%
San Mateo Union High School 10% 3% 18% 4% 17% 21% 9%
Burlingame Elementary 5% 2% 15% 5% 10% 20% 5%
Hillsborough Elementary 4% 1% (no data) 4% 4% (no data) 6% Millbrae Elementary 10% 3% 6% 17% 16% 26% 14%
San Bruno Park Elementary 12% 5% 10% 4% 14% 32% 9%
San Mateo-Foster City 6% 2% 9% 2% 10% 32% 4%
Sequoia Union High School 17% 6% 23% 8% 23% 33% 10%
Belmont-Redwood Shores 5% 3% 8% 5% 12% 17% 5%
Las Lomitas Elementary 4% 2% 0% (no data) 7% (no data) 3% Menlo Park City Elementary 3% 1% 8% 7% 5% 14% 3%
Portola Valley Elementary 4% 0% (no data) (no data) 6% (no data) 3% Ravenswood City Elementary 16% 0% 20% (no data) 15% 24% 21% Redwood City Elementary 10% 2% 19% 3% 12% 18% 4%
San Carlos Elementary 4% 2% 27% 8% 7% (no data) 3%
Woodside Elementary 8% 0% 0% (no data) 12% (no data) 7% Total 10% 3% 18% 7% 15% 26% 7%
Total Asian Black Filipino Hispanic
Pacific
Islander White
554
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 50 absenteeism rate and the absenteeism rate among students with disabilities of 13, 12, and 11 percentage points, respectively.

Rates of chronic absenteeism were also higher among English learners than the general population in most districts (with the exception of Ravenswood City Elementary and Jefferson Elementary). Woodside Elementary and Sequoia Union High School districts both had 14 percentage point gaps between absenteeism rates of English learners and the overall student body.

In every school district where the data are available, foster youth had higher rates of chronic absenteeism than the overall population. This was especially true in Sequoia Union High School District, where 63% of foster youth were chronically absent compared to just 17% of the overall student body.

Similarly, in almost all districts with available data, students experiencing homelessness had higher rates of chronic absenteeism than the overall student body. The chronic absenteeism rate among students experiencing homelessness was highest in Burlingame Elementary at 64%.

Migrant students were chronically absent at rates similar to or lower than the total student body in all districts with reported data.
555
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 51 Figure V-34.

Chronic Absenteeism by District and Extenuating Circumstance, 2018-2019 Source: California Department of Education and Root Policy Research Dropout rates. As previously indicated, workers without a high school degree have the lowest annual earnings compared to others at higher levels of educational attainment. In addition to the economic and housing precarity associated with low earnings, low earnings also often lead to increased incentives to participate in criminal activity. In fact, one study School District
Unified School Districts
Cabrillo Unified 10% 12% 23% 9% (no data) 18%
La Honda-Pescadero 16% 16% (no data) (no data) (no data) 22% South San Francisco 13% 14% 47% 13% 49% 18%
High & Elementary School Districts
Jefferson Union High School 15% 27% 33% (no data) 36% 28% Bayshore Elementary 12% 19% (no data) (no data) (no data) 11% Brisbane Elementary 12% 18% (no data) (no data) (no data) 18% Jefferson Elementary 12% 10% 21% (no data) 24% 16%
Pacifica 7% 11% (no data) (no data) (no data) 14%
San Mateo Union High School 10% 21% 50% (no data) 53% 21% Burlingame Elementary 5% 8% 64% (no data) (no data) 12% Hillsborough Elementary 4% 6% (no data) (no data) (no data) 8% Millbrae Elementary 10% 12% 5% (no data) (no data) 12%
San Bruno Park Elementary 12% 12% (no data) (no data) 18% 20% San Mateo-Foster City 6% 8% 15% (no data) 17% 13%
Sequoia Union High School 17% 31% 52% 16% 63% 29%
Belmont-Redwood Shores 5% 11% (no data) (no data) (no data) 10% Las Lomitas Elementary 4% 6% (no data) (no data) (no data) 5% Menlo Park City Elementary 3% 5% (no data) (no data) (no data) 9% Portola Valley Elementary 4% 3% (no data) (no data) (no data) 9% Ravenswood City Elementary 16% 16% 19% 17% 23% 21%
Redwood City Elementary 10% 12% 30% 6% 32% 16%
San Carlos Elementary 4% 8% 23% (no data) (no data) 11% Woodside Elementary 8% 22% (no data) (no data) (no data) 10% Total
English
Learners
Experiencing
homelessness Migrant
With
Disabilities
Foster
Youth
556
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 52 suggest that high school dropouts are 3.5 times more likely than high school graduates to be imprisoned at some point during their lifetime.15 Another study found that raising the high school completion rate by one percent for all men ages 20 through 60 would save the US $1.4 billion annually in crime related costs.16 Dropping out of high school also has adverse health costs: for instance, research has shown that high school dropouts are more likely to smoke and have a marijuana disorder in adulthood.17 For these reasons, reducing high school dropout rates in San Mateo County is pivotal to the health and economic prosperity of the community.

In this report, dropout rates shown for high school districts with available data and are defined as the percentage of cohort students who did not graduate with a regular high school diploma, did not complete high school, and are not still enrolled as a "fifth year senior".

In the 2019-2020 academic year, dropout rates were highest in Sequoia Union High School District, where 10% of students dropped out. This is similar to South San Francisco Unified, where 9% of students dropped out. In both these districts, and in Cabrillo Unified, dropout rates have increased since 2016-2017.

Dropout rates have decreased by one percentage point over the same period in San Mateo Union High School District, from 5% to 4%. Jefferson Union had the lowest dropout rate in the county at just 3%, which after slightly higher rates in 2017-18 and 2018-19, is the same as its 2016-2017 rate.
15 Monrad, Maggie. "High School Dropout: A Quick Stats Fact Sheet." National High School Center (2007). 16 U.S. Department of Justice, Bureau of Justice Statistics. (2002). Correctional populations in the United States, 1998 (NCJ-192929). Washington: U.S. Government Printing Office. 17 Gonzalez, Jennifer M. Reingle, et al. "The long-term effects of school dropout and GED attainment on substance use disorders." Drug and alcohol dependence 158 (2016): 60-66. 557
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 53 Figure V-35.

Dropout Rates by
District, 2016-2017 to
2019-2020
Note: La Honda-Pescadero Unified
School District is excluded
from these data.

Source: California Department of
Education and Root Policy
Research
In all school districts in the county, dropout rates are higher for boys than for girls.

Jefferson Union had the smallest gender gap, where 3% of girls dropped out and 4% of boys dropped out. Sequoia Union had the widest gender gap, where 13% of boys dropped out compared to just 7% of girls.

Figure V-36.

Dropout Rates by
Gender, 2019-2020
Note: La Honda-Pescadero Unified
School District is excluded
from these data.

Source: California Department of
Education and Root Policy
Research
Pacific Islander, Black/African American, and Hispanic students in the county often had higher dropout rates than those in other racial and ethnic groups. 558
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 54  In Sequoia Union High School District, dropout rates were highest among Pacific Islander students, where 20% dropped out in the 2019-2020 academic year.

Dropout rates were also especially high among Hispanic and Black/African American students in Sequoia Union, at 16% and 12% respectively.  In districts with lower dropout rates, for instance, Jefferson Union, the highest dropout rates still found among Black/African American (7%) and Hispanic students (6%).
 Notably, however, in South San Francisco Unified, White students were more likely to drop out than any other racial or ethnic group. In fact, 12% of White students dropped out compared to 11% of Hispanic students, 5% of Filipino students, and 3% of Asian students. Data for Black/African American and Pacific Islander students were not available for South San Francisco Unified due to small sample sizes. 559
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 55 Figure V-37.

Dropout Rates by Race, 2019-2020
Source: California Department of Education and Root Policy Research In all school districts in the county, students with disabilities, students experiencing homelessness, foster youth, and students learning English had higher dropout rates than the overall population.
 Among students with disabilities, the highest dropout rate was in Sequoia Union, where 24% dropped out. The gap between overall dropout rates and dropout rates among students with disabilities was wide in Sequoia Union at 14 percentage points.
 Cabrillo Unified, on the other hand, had less than a one percentage point gap between the dropout rate of overall students (6%) and students with disabilities (6%).
560
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 56  Among students learning English, Sequoia Union had the highest dropout rate at 27%, while Jefferson Union had the lowest dropout rate at 8%.  Sequoia Union also had the highest rate of dropout among students experiencing homelessness at 29% while Jefferson Union, again, had the lowest at 15%.  Foster Youth in Sequoia Union had an exceptionally high dropout rate a t 40%. San Mateo Union is the only other district in the county which reported these data in 2019-2020, and found only 18% of foster youth dropped out.  Migrant students at South San Francisco Unified actually dropped out at a rate slightly lower than the general student body: just 8% of migrant students dropped out compared to 9% of the overall student body. However, those in Cabrillo Unified were 11 percentage points more likely than the total student body to dropout. 561
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 57 Figure V-38.

Dropout Rates by Extenuating Circumstance, 2019-2020
Source: California Department of Education and Root Policy Research Disproportionate discipline rates. Strict discipline policies may stigmatize suspended students and expose them to the criminal justice system at a young age, setting them up for limited economic and social success down the line. Research has found that suspensions not only negatively affect the suspended students, but also their peers. 562
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 58 Students in schools with higher suspension rates are more likely to drop out or school and less likely to attend a four-year college.18
Other academic studies have found that students from African American and Latino families are more likely than their White peers to receive expulsion or out of school suspension as consequences for the same or similar problem behavior.19 This means that Black/African American and Hispanic students suffer more of the economic and social consequences than their White peers for the same behaviors.

Luckily, in every high school district in San Mateo County, suspension rates have decreased since 2011-2012. La Honda-Pescadero School District experienced the largest decrease: it was the district with the highest suspension rate in 2011-2012 at 10%, but now has the lowest suspension rate at just 1% in 2019-2020. San Mateo Union also experienced a rapid decrease in suspension rates over the same period, with a rate of 9% in 2011-2012 to a rate of 3% in 2019-2020.
18 Bacher-Hicks, Andrew, Stephen B. Billings, and David J. Deming. The school to prison pipeline: Long-run impacts of school suspensions on adult crime. No. w26257. National Bureau of Economic Research, 2019. 19 Skiba, Russell J., et al. "Race is not neutral: A national investigation of African American and Latino disproportionality in school discipline." School Psychology Review 40.1 (2011): 85-107. 563
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 59 Figure V-39.

Suspension Rates, 2011-2012 to 2019-2020
Source: California Department of Education and Root Policy Research In many school districts across San Mateo County, Hispanic students are disciplined at disproportionately higher rates compared to their peers. Figure V-40 compares each racial/ethnic group’s share of suspensions to their share of the overall student population.  In all districts except for La Honda-Pescadero, Hispanic students make up a larger share of suspensions than their overall share of the student body. For instance, in San Mateo Union, 34% of students are Hispanic, but 66% of suspended students are Hispanic, making a 32 percentage point overrepresentation gap.  In most districts, Black and Pacific Islander students are also overrepresented in terms of suspension rates, but these rates are slight compared to those of Hispanic students. For instance, in Sequoia Union, just 2% of the student body identified as Pacific Islander but 8% of suspended students were Pacific Islander.  Asian and Filipino students were underrepresented in terms of suspension rates. For example, in Jefferson Union High School District, 31% of students identified as Filipino but just 10% of suspended students were Filipino, a 21 percentage point 564
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 60 gap. In San Mateo Union High School, 22% of students identified as Asian but just 5% of suspended students were Asian, a 17 percentage point gap.  White students were also underrepresented in discipline rates in most districts except for La Honda-Pescadero, where they were overrepresented by 30 percentage points. They were substantially underrepresented in Cabrillo Unified (with a gap of 21 percentage points) and Sequoia Union (18 percentage points). 565
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 61 Figure V-40.

Suspension Rates by Race and Ethnicity, 2019-2020
Notes: the percentage of suspensions and shares of racial groups do not sum to 100% because we exclude students with no reported race, with more than one reported race, where districts did not report racial/ethnic data due to small sample sizes. Gaps of 15 percentage points or more are highlighted.

Source: California Department of Education and Root Policy Research School District
Asian Students
Share of Student Body 1% 14% 22% 9% 13%
Share of Suspensions 1% 7% 5% 1% 3%
Gap 0% -7% -17% -8% -10%
Black Students
Share of Student Body 1% 1% 3% 1%
Share of Suspensions 5% 1% 6% 2%
Gap 4% 0% 3% 1%
Filipino Students
Share of Student Body 1% 31% 6% 2% 23%
Share of Suspensions 0% 10% 2% 0% 9%
Gap -1% -21% -4% -2% -14%
Hispanic Students
Share of Student Body 52% 32% 61% 34% 41% 48%
Share of Suspensions 79% 46% 33% 66% 62% 69%
Gap 27% 14% -28% 32% 21% 21%
Pacific Islander Students
Share of Student Body 1% 2% 2% 2%
Share of Suspensions 4% 4% 8% 3%
Gap 3% 2% 6% 1%
White Students
Share of Student Body 40% 14% 37% 26% 38% 7%
Share of Suspensions 19% 16% 67% 14% 20% 7%
Gap -21% 2% 30% -12% -18% 0%
Cabrillo
Unified
Jefferson
Union
High
La HondaPescadero
San
Mateo
Union
High
Sequoia
Union
High
South San
Francisco
Unified
566
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 62 Staff demographics. Diversity of school staff has been shown to improve outcomes for students of color. For instance, one recent study found that students are less likely to be removed from school as punishment when they and their teachers are the same race.

This effect is driven almost entirely by black students, especially black boys, who are markedly less likely to be subjected to exclusionary discipline when taught by black teachers. There is little evidence of any benefit for white students of being matched with white teachers.20 Other research in California has found that, when students have a teacher of their race, they are more likely to attend class, therefore reducing chronic absenteeism.21 Even more studies have found that having a teacher of a student’s own race substantially improves their math and reading achievement.22 In San Mateo County, the demographics of faculty and staff are fairly similar to that of its students. Figure V-41 illustrates the share of the county’s faculty and staff who are Asian, Black/African American, Hispanic, Filipino, Pacific Islander, and White, and compares those shares to the racial/ethnic breakdown of the county’s student body.

There is a slightly larger share of White and Black/African American staff than students, meaning that Black/African American and White student groups are more likely to interact with same-race staff and faculty than other racial groups. Asian students are less likely to interact with a same-race staff of faculty member: 17% of the student body is Asian compared to just 8% of staff and faculty.
20 Lindsay, Constance A., and Cassandra MD Hart. "Teacher race and school discipline: Are students suspended less often when they have a teacher of the same race?." Education Next 17.1 (2017): 72-79. 21 Gottfried, Michael, J. Jacob Kirksey, and Tina L. Fletcher. "Do High School Students With a Same-Race Teacher Attend Class More Often?." Educational Evaluation and Policy Analysis (2021): 01623737211032241. 22 Dee, T. S. (2004). Teachers, race, and student achievement in a randomized experiment. Review of economics and statistics, 86(1), 195-210.
567
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 63 Figure V-41.

Staff and Student
Demographics,
2020-2021
Notes: Percentages do not always
sum to 100% because we
do not show shares of staff
with no reported race, with
more than one reported
race, or Native American
staff.

Source: California Department of
Education and Root Policy
Research
Since 2011-2012, the county’s school districts have diversified in that there has been a 13 percentage point decrease in the share of White faculty and staff and a 10 percentage point increase in Hispanic faculty and staff. However, there has been a slight decrease (by two percentage points) in the share of faculty and staff who identify as Black/African American. There has been a two percentage point increase in the share of Asian and Filipino faculty and staff, and a one percent increase in the share of Pacific Islander faculty and staff.
568
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 64 Figure V-42.

Faculty and Staff Demographics, 2011-2012 to 2020-2021
Notes: Percentages do not always sum to 100% because we do not show shares of staff with no reported race, with more than one reported race, or Native American staff.

Source: California Department of Education and Root Policy Research Figure V-43 illustrates faculty and staff racial and ethnic diversity for the 2020-2021 school year by district.
 Portola Valley has the least diverse faculty and staff in the county, with 59% identifying as White.
 Ravenswood Elementary has the most diverse faculty and staff: the district has the highest share of Pacific Islander (5%), Black/African American (12%) and Hispanic (72%) faculty and staff.
 South San Francisco Unified School District has the highest share of Asian faculty and staff at 14%.
 Brisbane Elementary and Jefferson Elementary have the highest shares of Filipino faculty and staff at 28%.
569
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 65 Figure V-43.

Faculty and Staff Race/Ethnicity, by District, 2020-2021 Notes: Percentages do not always sum to 100% because we do not show shares of staff with no reported race, with more than one reported race, or Native American staff.

Source: California Department of Education and Root Policy Research School District
Unified School Districts
Cabrillo Unified 0% 1% 1% 46% 0% 51%
La Honda-Pescadero 0% 5% 5% 39% 0% 51%
South San Francisco 14% 3% 16% 34% 2% 28%
High & Elementary School Districts
Jefferson Union High School 3% 3% 13% 26% 1% 43%
Bayshore Elementary 13% 4% 17% 61% 0% 4%
Brisbane Elementary 7% 0% 28% 20% 4% 42%
Jefferson Elementary 13% 3% 28% 25% 0% 29%
Pacifica 7% 2% 8% 23% 2% 54%
San Mateo Union High School 11% 5% 6% 34% 3% 40%
Burlingame Elementary 8% 5% 11% 27% 3% 45%
Hillsborough Elementary 2% 1% 7% 20% 1% 55%
Millbrae Elementary 13% 3% 9% 25% 0% 48%
San Bruno Park Elementary 4% 2% 13% 26% 4% 48%
San Mateo-Foster City 13% 2% 7% 33% 3% 37%
Sequoia Union High School 2% 12% 2% 54% 4% 26%
Belmont-Redwood Shores 13% 2% 3% 39% 0% 42%
Las Lomitas Elementary 7% 7% 0% 42% 0% 42%
Menlo Park City Elementary 3% 1% 3% 28% 1% 40%
Portola Valley Elementary 4% 4% 0% 33% 0% 59%
Ravenswood City Elementary 2% 12% 1% 72% 5% 3%
Redwood City Elementary 4% 5% 2% 65% 1% 21%
San Carlos Elementary 8% 6% 3% 37% 1% 42%
Woodside Elementary 12% 8% 0% 30% 0% 49%
Total 8% 5% 8% 40% 2% 35%
Asian Black Filipino Hispanic White
Pacific
Islander
570
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 66 Figure V-44 illustrates the gap between faculty/staff representation and the student body.

For instance, at San Bruno Park Elementary, 15% of the students are White while 48% of the faculty/staff are White, leaving a 33 percentage point gap.

If schools are striving for a distribution of faculty/staff that reflects the racial and ethnic distribution of their student body, the closer to a 0 percentage point gap, the better.

Schools like San Bruno Park Elementary fall short of meeting this goal, in that there is a large overrepresentation of White faculty/staff compared to the student body. Many other districts have a large overrepresentation of White faculty/staff, including Millbrae Elementary (32 percentage point gap), Jefferson Union High School District (29 percentage point gap), and South San Francisco Unified School District (22 percentage points). There are just a few school districts where the share of White students is higher than the share of White faculty, particularly Woodside Elementary and Menlo Park City Elementary, both with a 15 percentage point gap.

Across most school districts, the share of Asian students is larger than the share of Asian faculty/staff. This suggests that Asian students are less likely than their peers to interact with a same-race teacher or staff member. The largest disparity is in Millbrae Elementary, where just 13% of the faculty identify as Asian compared to 46% of the student body, a 33 percentage point gap.

In many school districts, there is a dearth of Hispanic faculty and staff. For instance, in La Honda-Pescadero, 63% of students are Hispanic compared to 39% of faculty, a 24 percentage point gap. In other districts, however, there is a larger share of Hispanic faculty/staff than students. In Las Lomitas Elementary, for instance, 13% of students are Hispanic and 42% of faculty/staff are Hispanic. Recall that Las Lomitas Elementary commonly has high-performing English language learnings students. This may be partly due to the district’s large portion of Hispanic faculty/staff.

Though district wide there are approximately the same portions of Filipino students as there are faculty/staff, Jefferson Union High School stands out as a district where Filipino students are less likely to interact with a same-race teacher or staff member. In Jefferson Union, 29% of students are Filipino compared to just 13% of faculty/staff.

In all districts, there only very small gaps in the share of students that identify as Pacific Islander and the share of faculty/staff that identify as Pacific Islander. All in all, they are represented in approximately equal proportions.
571
ROOT POLICY RESEARCH APPENDIX C.3. ACCESS TO EDUCATION SUPPLEMENT, PAGE 67 Figure V-44.

Difference Between Staff and Student Populations, by District, 2020-2021 Notes: The figure shows percentage point gaps in student representation versus faculty/staff representation (calculated as the share of faculty/staff minus the share of students).

Source: California Department of Education and Root Policy Research School District
Unified School Districts
Cabrillo Unified -1% 1% 0% -6% 0% 11%
La Honda-Pescadero 0% 5% 4% -24% 0% 16%
South San Francisco 0% 2% -7% -14% 0% 22%
High & Elementary School Districts
Jefferson Union High School -12% 2% -16% -5% 0% 29%
Bayshore Elementary -6% 1% -4% 20% -4% 1%
Brisbane Elementary -13% -1% 16% -8% 4% 18%
Jefferson Elementary -6% 1% 3% -11% -1% 18%
Pacifica -1% 1% -1% -3% 2% 15%
San Mateo Union High School -12% 4% 1% 2% 1% 12%
Burlingame Elementary -19% 5% 8% 11% 3% 4%
Hillsborough Elementary -30% 1% 5% 15% 1% 7%
Millbrae Elementary -33% 2% 3% 5% -2% 32%
San Bruno Park Elementary -12% 1% 3% -15% -1% 33%
San Mateo-Foster City -13% 1% 4% -4% 1% 16%
Sequoia Union High School -7% 10% 1% 9% 2% -9%
Belmont-Redwood Shores -19% 1% 0% 27% -1% 8%
Las Lomitas Elementary -11% 6% -1% 29% 0% -11%
Menlo Park City Elementary -10% 0% 2% 11% 0% -15%
Portola Valley Elementary -2% 4% 0% 19% 0% -7%
Ravenswood City Elementary 2% 7% 1% -12% -2% 2%
Redwood City Elementary 0% 4% 1% -5% 0% 2%
San Carlos Elementary -10% 5% 2% 23% 1% -7%
Woodside Elementary 8% 6% 0% 14% -1% -15%
Total -9% 4% 0% 2% 0% 9%
Asian Black Filipino Hispanic
Pacific
Islander White
572
1 BELMONT SEGREGATION REPORT
UC Merced Urban Policy Lab and ABAG/MTC Staff
Version of Record: March 06, 15:54:31
C.4. Belmont Segregation Report | 2023-2031

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Belmont City CouncilSeptember 10, 2024

Belmont City Council
September 10, 2024