AGENDA
JOINT MEETING OF THE COTATI CITY COUNCIL AND THE SUCCESSOR
AGENCY TO THE FORMER COTATI COMMUNITY REDEVELOPMENT AGENCY Tuesday February 22, 2022
5:30 PM SPECIAL JOINT MEETING
Pursuant to AB 361 (2021), Teleconference Restrictions of the Brown Act Have Been Suspended, as Well as the Requirement to Provide a Physical Location for Members of the Public to Participate in the Meeting.
Cotati City Council and Planning Commission Meetings will be conducted virtually through Zoom Online video conferencing, and will still be available to watch or listen live in the following ways:
1. Using the following online livestream meeting portal link: http://cotaticityca.iqm2.com/citizens/default.aspx;
2. Cable T.V. Broadcast, local channel 28
Members of the public can participate in the meeting online by selecting “Join a Meeting” at Zoom.us. The credentials for joining the meeting are provided below:
Webinar ID: 815 5601 5740
Passcode: 227676
If you do not have the ability to join online, but would like to participate in the meeting, you can call into the meeting using your telephone, by dialing one of the following numbers and entering the meeting credentials:
1 669 900 6833 or +1 346 248 7799 or +1 253 215 8782 or +1 301 715 8592 or +1 312 626 6799 or +1 929 436 2866
Attendees may join the meeting any time after 5:15 pm. Attendees will be muted until they are called upon for Public Comment. To make a public comment, use the “raise hand” icon on your smart device or desktop computer, or dial *9 if you are using just your telephone. Please listen carefully for the Mayor or City Clerk to address you by name (or phone number) and for the audible Zoom notification that you have been unmuted.
Once you begin your public comment, your three minutes will begin.
If you would prefer to submit public comment in writing, please email your comments to [email protected]. If you are commenting on a specific agenda item or items, please state the agenda item number(s) in the subject line of the email. All comments received via email will be provided to the City Council or Planning Commission in writing and included as a part of the record of the meeting.
If you have a disability which requires an accommodation or an alternative format to assist you in observing and commenting on this meeting, please contact the City Clerk, Lauren Berges, at [email protected] or (707) 665- 3622 48 hours in advance to ensure arrangements for accommodation.
1. CALL TO ORDER
2. PUBLIC COMMENT
Pursuant to California Government Code section 54954.3(a), members of the public wishing to address the Council/Board may do so at the beginning of the special meeting, and such comments shall be limited to the special meeting topic(s).
Cotati City Council Agenda February 22, 2022
3. STUDY SESSION
A. DRAFT 6TH CYCLE HOUSING ELEMENT UPDATE PUBLIC WORKSHOP It is recommended that the City Council and Planning Commission review the provided information, provide direction on outstanding issues and receive and file the report for future consideration.
4. ADJOURNMENT
Certification of Posting of the Notice: I declare under penalty of perjury that I am employed by the City of Cotati and that I posted this notice on the City's website, bulletin boards of City Hall, Veterans' Memorial Building and the SMART Train Depot, on or before February 18, 2022, 6:00 pm.
/s/ Lauren Berges, City Clerk
Cotati City Council
Agenda Staff Report
Item type: STUDY SESSION
To: City Council
Subject: Draft 6th Cycle Housing Element Update Public Workshop Date: February 22, 2022
Written by: Noah Housh, Director of Community Development Recommendation
It is recommended that the City Council and Planning Commission review the provided information, provide direction on outstanding issues and receive and file the report for future consideration.
Background
This Workshop is a public presentation and information gathering event for the community, Planning Commission and City Council and is intended to:
1. To provide an overview of state, regional, and local housing issues and laws to provide context for the 6th Cycle Housing Element Update process;
2. To demonstrate where demographic data and community input can inform the 2023 Housing Element Update;
3. To obtain feedback from the Planning Commission and City Council on potential policy options; and
4. To seek public input on housing needs and potential solutions that will be used to inform the 6th Cycle Housing Element Update.
Analysis/Discussion
Introduction And Overview
The preparation of the Housing Element is required by California State Law, Chapter 10.6 and
10.7 of the Government Code. The City has contracted with 4LEAF, Inc. to prepare the required update to its 2014 Housing Element to cover the period between 2023 – 2031. The update of the Housing Element provides the opportunity for the City to review and supplement their existing housing policies and implementation measures to facilitate housing production
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and demonstrate how the City will accommodate its assigned housing need, spread across the different income levels for the next eight years.
The Housing Element is one of the seven mandated elements of the City’s General Plan. It is the only element of the General Plan required by the State to be updated on a set schedule. A Housing Element is required by California law to establish policies and programs that will support the provision of an adequate housing supply for citizens of all income levels. The intent of state law is to ensure that all jurisdictions in the state are zoned to provide adequate housing for all members of the community. While the State reviews the Housing Element to ensure compliance with housing law, each jurisdiction must identify its own specific housing needs to successfully address those needs.
Regional Housing Needs Allocation
The Regional Housing Needs Allocation (RHNA) is mandated by State housing laws as part of the process of updating General Plan Housing Elements. The RHNA process is meant to identify and address housing needs for the projected State population and household growth; to improve the jobs - housing balance in communities; and to ensure the availability of housing affordable to all income groups. The County of Sonoma has a combined RHNA of 14,562 units. Cotati’s assigned share of that RHNA is 234 units, including 94 units affordable to lower-income households and 39 units affordable to moderate-income households:
Draft Regional Housing Need Allocation, 2023 - 2031
Very
Low
Low Moderate Above
Moderate
Total
Cotati 60 34 39 101 234
Government Code (GC) Section 65583(a)(1) further divides the very-low-income category into extremely low and very low categories with 50% in each. Cotati’s extremely low-income unit allocation is therefore 30 units.
Zoning, Density, and Affordability Assumptions
The City is not required to construct housing units mandated by RHNA. It is instead required to demonstrate that it has adequate sites zoned at appropriate densities to accommodate the number of RHNA units in each income category. When a city lacks adequate available, vacant land for the development of its RHNA, it must either rezone adequate land at high enough densities to support affordable housing development or use other methods to identify where the units can go. These methods may include increasing allowable densities in certain land use categories; providing zoning overlays to allow housing on certain commercial parcels;
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allowing additional units within single-family neighborhoods; implementing programs to encourage more, smaller units that are typically more affordable than larger units; or developing other creative solutions that address the City’s identified housing needs. For a unit to qualify as low income in a housing site inventory, the City must demonstrate that the rent or sales price is affordable to the specified income levels. The typical method to demonstrate affordability at these income levels is to record a deed restriction on the units for all future renters or owners for 55 years.
Credit for Accessory Dwelling Units (ADUs)
The City may also take credit for non-restricted units such as Accessory Dwelling Units (ADUs) or Junior Accessory Dwelling Units (JADUs) that are rented within the affordable income categories if it can demonstrate affordable rental rates. Alternatively, the City may use HCD’s “safe harbor” affordability assumptions, which are proposed by ABAG to be distributed across income categories as follows: 15% Extremely Low; 15% Very Low; 30% low, 30% moderate; and 10% above moderate. The safe harbor for the number of ADUs assumed for the upcoming planning period is the average of ADUs permitted over the years 2018-2021; higher numbers would need to be supported by evidence of significant increases in permitted ADUs along with strong programs to promote and support their construction.
Housing Element Update Requirements:
In addition to the requirement that the Housing Element address the City’s ability to meet the RHNA through zoning, the Housing Element serves as the tool to identify and provide for the local housing needs of the community.
State law requires that the Housing Element:
• Provide achievable goals, policies, quantified objectives, and scheduled programs to preserve, improve, and develop housing opportunities; • Identify and analyze household characteristics, including housing costs compared to residents’ ability to pay; and housing characteristics, including the extent of overcrowding and an estimate of housing stock conditions; • Identify and analyze governmental constraints on the maintenance, improvement, and development of housing for all income levels. These constraints include land use and density controls, building codes and their enforcement, site improvements, fees required of developers, and local processing and permit procedures; • Identify and analyze nongovernmental constraints on the maintenance, improvement, and development of housing for all income levels, including the availability of financing, the price of land, the cost of construction, and community opposition;
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• Identify the special housing needs of the community including the homeless, seniors, female-headed households, farmworkers, and persons with disabilities; • Identify sites that are suitable for all types of residential development, including multi- family and manufactured homes, during the eight-year housing cycle to meet the City’s fair share of regional housing needs (the RHNA) at all income levels; • Identify opportunities for energy conservation with respect to residential development; and
• Be certified (approved) by the State Department of Housing & Community Development (HCD) as complying with State law.
Highlights of New Housing Laws since the last Housing Element:
The California State Legislature has identified the attainment of a decent home and suitable living environment for every Californian as the State’s major housing goal. In the last few years, the legislature has passed multiple housing bills that prescribe new requirements for Housing Elements and new by-right requirements for housing projects. The State is serious about their efforts to facilitate the construction of new housing units in California, and new housing bills will continue to reshape the housing landscape for years to come. A brief overview of the state Housing Law updates is provided below for information and context about the Housing Element update process.
AB 72 (2017) strengthened California’s 50-year-old “Housing Element law,” which requires local governments to adequately plan for future housing needs at all income levels. The bill grants the state Housing and Community Development Department (HCD) authority to review any action or failure to act by a local government that it determines is inconsistent with an adopted Housing Element or Housing Element law. This includes failure to implement program actions included in the Housing Element. HCD may revoke Housing Element compliance if the local government’s actions do not comply with state law. In addition, the HCD can refer violations to the state Attorney General’s Office for enforcement any time it determines that a local jurisdiction is in violation of state law for non-compliance with Housing Element law, the Housing Accountability Act, the “No Net Loss” law, the density bonus law or anti- discrimination laws.
Since 2018, HCD has sent more than 250 enforcement letters to jurisdictions throughout the state. The most notorious case involving the Attorney General’s office was that of Huntington Beach, which held that, for multiple reasons, the RHNA did not apply to them. The case was settled in 2020 when the City agreed to amend one of its Specific Plans to provide adequate sites to meet its RHNA obligation. In late 2021, the California HCD added a Housing Accountability Unit to further hold local jurisdictions accountable for their Housing Element commitments and other state laws.
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SB 35 (2017) requires that jurisdictions that are not meeting their RHNA obligations have a “streamlined ministerial approval process” for housing developments of two or more units when 10% or 50% of project units are provided as affordable and deed restricted. “Streamlined ministerial approval process” means that officials cannot exercise discretion over a qualifying project, but can only compare it against adopted, objective design and development standards.
Cotati has not yet received applications under SB 35, but projects developing at 50% affordable housing are eligible for streamlined review, and staff is endeavoring to have such standards adopted within the next year.
AB 1397 (2017) requires that cities zone appropriately for their share of the regional housing need, and zoning for all types of housing – including multi-family housing - is required. The new law requires strong justification when non-vacant sites are zoned to meet the housing need, especially for lower-income housing. In Cotati, this means that most of the housing sites listed in the current 5th Cycle Housing Element may not be used in the 2023 Housing Element Update without a market analysis demonstrating that the site(s) remains a suitable candidate for a housing project.
SB 166 (2017), the new “No Net Loss” law, requires that a City replace any site that was zoned and listed in inventory for low-income housing if it develops with anything else, unless the City can make findings that enough additional sites that are adequately zoned remain to allow the City to continue to accommodate its remaining housing need (RHNA), by income category (See Policy Issue #3). The intent is to ensure that jurisdictions have adequate sites with appropriate zoning to accommodate their share of the regional housing need throughout the Housing Element period. As noted above, AB 72 provides that HCD and the state Attorney General can intercede if a jurisdiction fails to uphold the “No Net Loss” provisions.
AB 686 (2018), also known as the anti-discrimination or “Affirmatively Furthering Fair Housing” (AFFH) law, requires specific analysis around patterns of socio-economic concentration within the City and the larger region. This new law requires Cotati to examine past and current zoning, land use, funding, and other practices. New programs may be needed to ensure compliance.
SB 330 (2019) amends the Housing Accountability Act to prohibit local jurisdictions from enacting new laws that would have the effect of reducing the legal limit on new housing within their borders or delay new housing via administrative or other regulatory barriers.
SB 9 and SB 10 (2021) do not directly affect Housing Element law or RHNA allocations, but they may be considered when making development capacity assumptions or when exploring policy approaches to encourage housing development to meet the City’s needs. SB 9 builds on existing accessory dwelling unit (ADU) law by allowing duplexes and lot splits on most singlefamily parcels in California, and SB 10 is an opt-in provision to allow low-density multiplexes with streamlined rezoning and flexible parameters tailored to local needs.
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In additional to the above, Government Code Section 65583(c) requires that the Housing Element include a five-year schedule of actions the local government is undertaking or intends to undertake to implement the policies and achieve the goals and objectives of the Housing Element. Significantly, if the City’s housing inventory “does not identify adequate sites to accommodate the [RHNA] need for groups of all household income levels ..., the program shall identify sites that can be developed for housing within the planning period.” Those sites must typically be identified and rezoned to allow housing by-right at default densities within 3 years from the beginning of the Housing Element period. However, AB 215 (2021) now shortens that rezoning period from three years to one year for any jurisdiction that does not have a certified Housing Element by the statutory deadline.
State’s Expectations and Requirements:
The California HCD publishes materials and provides technical assistance aimed at assisting California jurisdictions in updating their Housing Elements to comply with complex state laws and to obtain HCD certification. Thoughtful solutions will be needed to address the following HCD expectations and requirements:
• Regardless of RHNA allocations, all local governments must include zoning for a variety of housing types, including multifamily, transitional, supportive, workforce, and farmworker housing; SROs (Single Room Occupancy); homeless shelters, including Low Barrier Navigation Centers; and mobile homes. Even if the City was able to demonstrate meeting their full RHNA by depending on ADUs and housing projects already in the pipeline, the above housing types must still be allowed under state law. • The City will need to demonstrate appropriate zoning to accommodate their allocation of regional housing need for lower income households. Statute provides a default minimum density of 20 units per acre. If the City plans to accommodate their RHNA for lowincome households on sites that allow less than 20 units per acre, an analysis is required based on statutory factors that include consideration of market conditions and the City’s experience in developing affordable housing at lower densities. • Regardless of how the City accommodated its RHNA, HCD will require programs to remove zoning barriers and increase housing choices so that housing units are not out of reach to less affluent community members. Even though the City does not include areas designated as high opportunity, AB 686 requires HCD to look at how the sites zoned at high enough densities for low-income housing are integrated throughout the community. • The City may be able to demonstrate adequate sites through a combination of methods without the need to rezone specific sites within the limited period noted above (see Policy Issue #1).
Housing Constraints Analysis:
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State statute requires specific constraints to be addressed within a Housing Element.
Governmental constraints include land use and density limitations, General Plan policies and growth control programs, development fees, and local approval requirements such as for use permits and design review. Non-governmental constraints include land prices, construction costs, community opposition and the availability of vacant developable parcels. The constraints identification and analysis for Cotati is ongoing with the input of developers and community members.
Potential Governmental Constraints:
•Land use controls, including density limits and zoning •Building codes and their enforcement
•Site improvement requirements
•Fees and other exactions
•Local processing and permit procedures
•Housing for persons with disabilities
•Transitional housing & supportive housing as a residential use of property Potential Non-governmental Constraints:
•Availability of financing
•Availability and price of land
•Cost of construction
•Community opposition
Local Housing Issues and Housing Needs
One of the many requirements for the Housing Element Update is the collection of data to help determine housing needs. This includes such things as how many residents are overpaying for their housing; overcrowded units; the costs of developing housing; and demographic information and trends. The bulk of the required housing and demographic data has been provided by ABAG and is contained in Attachment 1. The Housing Element must be more than just a set of policies and a list of sites for review and approval by the HCD. The Housing Element needs to contain policies and programs that will benefit and meet the needs of current and future Cotati residents. Those needs are being identified by the 4LEAF team and the community, and programs will be tailored to address them. The most important
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method of determining housing issues and needs is to ask residents. A survey has been issued in English and Spanish asking residents about Cotati’s housing issues and housing needs; preliminary survey results are provided as Attachment 2 and are summarized below.
Public Outreach to Date:
Housing issues affect the entire community and can be confusing and contentious. California requirements about what Housing Elements must do and allow, can seem at odds with longstanding community values and identity. The public participation requirement of Housing Element law presents an opportunity to engage constituents in defining housing issues and creating solutions that both meet the needs of the community and the requirements of state law.
Restrictions on indoor gatherings due to the pandemic have necessitated virtual community outreach and engagement. While in some cases this has made it possible for more people to be engaged in the process, a digital divide may exist in cases where households lack internet connections or may be unable to attend virtual meetings due to work obligations. To ensure that community outreach during the pandemic has been as equitable as possible, the outreach program included participation opportunities via cell phone, at public events and at the convenience of the residents. Cotati’s Housing Element Update has included the following public outreach efforts to date:
Housing Element Update Webpage provides status updates, introductory information to the Housing Element Update process, access to meeting agendas and materials, a dedicated email to provide comments about the Housing Element Update, a housing interest list sign up, and community opinion surveys in Spanish and English:
Figure 1: Screenshot of Cotati’s Housing Element Update Webpage (http://www.cotaticity.org/City_Hall/Departments/Community_Development/Housing/2023_H ousing_Element_Update)
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Napa-Sonoma Collaborative Housing Element Update Webpage “Let’s Talk Housing” provides more generalized information regarding the Housing Element Update process itself, and is funded by a grant from ABAG/MTC supporting collaboration efforts between all of the communities in Napa and Sonoma Counties. Links to each individual communities housing element update pages are available frm this site.
Figure 2: Screenshot of the Napa Sonoma Collaborative Let’s Talk Housing Webpage ( https://nsc-housing.org/)
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Community Events:
• October 24, 2019, Cotati City staff held a Housing Workshop to present an overview of State legislation affecting the upcoming 6th Cycle Housing Element Cycle. Among other things, this presentation included the changes to the RHNA process affected by AB 1771 and SB 828; the likely changes to the RHNA Distribution Methodology; and the upcoming Housing Methodology Committee (HMC) process managed by ABAG/MTC.
Following up on this workshop, city staff initiated the first community engagement effort to support the 6th Cycle Housing Element Update, the Community Housing Survey and over 100 responses were received.
• In December 2020 thru February 2021, City staff gathered community input regarding the design of housing within Cotati through the Multi-Family Visual Preference Survey.
Over 75 individual responses to this survey were received with the input informing the Multi-Family Objective Design Standards, which were adopted by the City Council in September 2021.
• November 10, 2020, City staff presented the outcome of the HMC process, providing a summary of the findings and direction of the HMC including the significant increase in the projected 6th Cycle RHNA, the likely use of the Plan Bay Area (2050) as the baseline data source and the significant changes to the Housing Element Update process. • Kick-off presentation at a joint Planning Commission/City Council meeting was held via Zoom on October 12, 2021, covering the Housing Element update process, new laws, opportunities for engagement, and local housing demographics. This meeting also included an opportunity for members of the public to speak.
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• October 31, 2021, City staff tabled at the Cotati Candy Land Trick or Treat Halloween Carnival, providing residents and visitors with an overview of the Housing Element process, the community survey and had a zoning map on display for booth visitors to identify sites suitable for housing development.
• December 4, 2021, Civic Edge Consultants tabled to provide information and solicit survey responses at the Cotati Chamber of Commerce annual “Shop and Stroll” holiday event in downtown Cotati.
• Community stakeholder group interview on February 2, 2022 and continuing stakeholder interviews with community-based organizations and housing developers. • Presentation to the Planning Commission on February 22, 2022 via Zoom to discuss preliminary sites and policy strategies. This meeting also includes an opportunity for members of the public to identify priority areas for the upcoming Draft Housing Strategy. • Future Public Town Hall event in Spring 2022 to further engage residents in the Housing Element Update process, with an interest in discussing equity, residents’ individual housing needs & concerns, and diligent, targeted outreach to equitably reach renters and students.
Community Opinion Survey and Preliminary Results:
Surveys were made available in English and Spanish and could be completed on paper or on cell phones, computers, or other internet-accessing devices. Surveys were promoted on the City webpage, email distribution lists, through social media, and on flyers posted throughout the community, including in coffee shops, laundromats, and community centers. The first community opinion survey on housing issues and opportunities generated 126 responses; aggregated results can be viewed in Attachment 2 of this report. The surveys were designed to elicit residents’ opinions about housing needs and opportunities, both now and in the future, as well as their ideas about new housing types that might help to meet identified needs.
The preliminary survey results demonstrate that residents have given housing issues much thought and have innovative ideas for meeting housing needs. Generally, survey respondents identified housing costs, both for renting and purchasing, as a top concern, along with housing affordable to people that work in the City and accessible homes for the aging population. When asked what types of new housing would be most successful in Cotati, “missing middle” housing such as smaller single-family homes, townhomes, and duplexes received the most support from respondents, followed by downtown apartments and accessory dwelling units (ADUs). When asked to provide their thoughts on housing opportunities in the community, respondents had a variety of opinions on different strategies. Responses included sentiments of support for the community’s walkability, bikeability, uniqueness, and compact urban design.
Respondents expressed support for increased density, student housing, senior housing, and
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affordable housing options. Responses also included concerns about dense development and sprawl. Preliminary survey results are provided as Attachment 2.
Discussion of Policy Options:
The primary task to be addressed by this Housing Element will be the need to meet the statutory requirements of the CA Government Code. In addition to fulfilling mandates, Cotati has unique community needs and interests that can be addressed by its Housing Element.
Some preliminary options for the Council and Commission to consider are outlined below; input is sought on the most favorable options to be pursued within the 2023 6th Cycle Housing Element. Additional policy ideas, solutions, and input from members of the public and from the Council and Commission are welcomed and encouraged.
ISSUE #1: ADEQUATE SITES APPROACHES & REZONING OPTIONS
As noted above, if the City does not have sufficient sites zoned at adequate densities to accommodate its RHNA, it must include a program within its Housing Element rezone sites to meet that need within three years of the Housing Element due date (by January 31, 2026), or within one year (by January 31, 2024) if the City does not adopt and certify on time. Strong penalties would be incurred if the City failed to accomplish the required rezones in a timely manner, up to and including the loss of land use authority.
Conversely, if the City can demonstrate that it already has adequate sites that meet AB 1397 criteria and are appropriately zoned to meet the City's RHNA, it does not need to include a required rezoning program in its Housing Element. It could, if desired, include an optional program or programs to consider rezoning to provide additional opportunities for housing; this type of supplemental program would not trigger the three-year rule. Rezoning may also be pursued throughout the 6th Cycle planning period without necessitating additional review of the Housing Element.
A preliminary analysis has been conducted of the sites available for housing (Table 1, below).
Once the housing projects in the City’s approval pipeline and the “safe harbor” ADU assumptions have been factored in, the City may have adequate sites to meet its regional housing need for most income categories. This analysis is preliminary, however, and proof of adequate sites under AB 1397 will be required prior to the inventory being approved by HCD.
As well, the City must ensure that it has adequate sites available for its RHNA throughout the Housing Element period, either by having significantly more sites in inventory than are needed, or by including a program to add appropriately zoned sites to the inventory as they are needed during the Housing Element period (see Issue #3).
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Table 1: Preliminary Summary of RHNA Surplus
ELI VLI LI MI AMI Total
RHNA Allocation 30 30 34 39 101 234
RHNA
Credits
Pipeline 0 30 8 15 337 390
ADUs/JADUs 3 4 7 7 3 24
Preservation of Affordability 7 7 8 6 0 28
Remaining RHNA After Credits 20 -11 11 11 -239 -208
RHNA
Sites
Sites from 5th Cycle Housing
Element 0 10 25 67 205 307
Additional Potential Housing
Sites
0 0 21 35 110 166
Santero Way Specific Plan 0 5 5 5 83 98
TOTAL UNITS 10 56 74 135 738 1013
RHNA SURPLUS/SHORTFALL -20 26 40 96 637 779
% OF RHNA MET 149% 346% 731% 433%
ELI = Extremely Low Income; VLI = Very Low Income; LI= Low Income; MI = Moderate Income; AMI = Above Moderate Income
Policy Option A: Avoid rezoning sites. This option would make full use of other Housing Element programs to avoid any required rezoning of housing sites and the potential penalties that would apply if not accomplished on time.
Policy Option B: Rezone only after adequate inventory. This option would not completely avoid rezoning and might consider it in the future under some circumstances but only after an adequate inventory can be demonstrated without the need for a required rezoning program to meet RHNA.
Recommendation: Policy Option A. This option would allow for programs to consider targeted rezoning to be included in the Housing Element but would not count on the rezoning of any sites to demonstrate an adequate inventory and achieve a certified Housing Element.
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The risks associated with a failure to rezone sites by the statutory deadline are too great to consider rezoning sites unless necessary to achieve an adequate inventory.
ISSUE #2: ACCESSORY DWELLING UNIT APPROACHES
As noted in the Introduction section above, the City can take credit for non-restricted units such as Accessory Dwelling Units (ADUs) or Junior Accessory Dwelling Units (JADUs) consistent with HCD’s income categories under “safe harbor” affordability assumptions, which are reflected in Table 1 above. The safe harbor for the number of ADUs assumed for the upcoming planning period is the average of ADUs permitted over the years 2018-2021; in Cotati’s case that average is 3 ADUs per year. If the City uses this safe harbor assumption, this portion of their inventory will be accepted by HCD. No Net Loss reporting rules will apply (See Issue #3, below).
If the City determines that a larger number of ADUs will assist it in reaching its housing goals, including the provision of units for special needs and smaller households, it may wish to adopt additional programs to incentivize, and support ADUs. If this is the case, then higher numbers of ADUs than the "safe harbor” assumptions may be justified. This may be an appropriate approach for Cotati with programs to incentivize production. The Community survey results indicate that the community believes that ADUs are a housing type that will work well for Cotati, and census data indicate that ADUs would provide a good match for aging households, smaller households, and special needs households where family or caretakers can remain close by. As well, the provision of ADUs throughout the City can help to meet AFFH (Affirmatively Furthering Fair Housing) objectives because it integrates affordable rental housing units into higher-resource single family neighborhoods.
Another option to provide for a portion of the very-low income RHNA within single-family neighborhoods would be JADU’s. This can help meet the specific housing needs of Cotati’s smaller households, students, and low-income seniors while creating opportunities for renters or caretakers to live on-site.
A new CalHFA grant program for ADUs is available to lower-income borrowers and this information could be provided as a potential program option. Furthermore, local programs facilitated by the Napa Sonoma ADU Center and financing options for prefabricated homes with Homes for Sonoma are available for programmatic considerations.
Option A: Increase ADU Assumptions. This policy option would make maximum use of the allowances for ADUs and JADUs by adopting new programs to facilitate and encourage the construction of ADUs and JADUs, and project a larger number of units to be constructed over the planning period than the safe harbor assumptions.
Option B: Use HCD “safe harbor” ADU assumptions. This policy option would not commit to adopting additional programs to facilitate and encourage additional ADUs, but instead would use the HCD safe harbor assumptions of 3 ADUs/JADUs per year (24 total units over the planning period).
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Recommendation: Option A. Increase ADU assumptions beyond the safe harbor allowances, but only to the extent that new policies and programs are included to facilitate their construction.
ADUs meet many identified community needs and are easily integrated within Cotati’s housing stock due to enabling state legislation. Care will need to be taken to not project construction numbers and affordability levels too high such that replacement sites are needed under the No Net Loss provisions; see Issue #3 below. ADU’s under state law are currently approved ministerially, but such a program can promote permit ready ADU’s that are most compatible with Cotati’s neighborhoods.
ISSUE #3: NO NET LOSS APPROACHES
As noted in the new laws section above, the new “No Net Loss” laws will impact the sites used in Housing Element sites inventories, including assumed affordability levels and development assumptions. The intent of the legislation is to ensure all jurisdictions maintain an adequate supply of appropriately zoned land to accommodate their remaining RHNA for the entire 8-year Housing Element period. There are several components to this new law: First, a jurisdiction may not approve a project at a density or level of affordability lower than that listed in the Housing Element inventory unless it can make findings that adequate sites remain available to accommodate the remaining RHNA. Second, if a jurisdiction approves a project at a density or affordability level less than the level the site was listed for and it does not have enough other sites with appropriate zoning to accommodate the remaining RHNA, it must identify and rezone adequate sites within 6 months – a timeframe that is infeasible. Third, the inventory is expected to be dynamic and to reflect all changes and adjustments made throughout the Housing Element period. These adjustments would be made during the state mandated Annual Planning Report (APR). AB 72 allows referrals to the Attorney General for violations of the No Net Loss laws.
Jurisdictions must not run afoul of this law and plan for inventory changes throughout the Housing Element period.
Policy Option A: Zone an excess of sites to accommodate future development. This is an approach taken by many jurisdictions, with a sites “buffer” of at least 30 percent recommended.
Under this option, the City would need to ensure that there are adequate sites for at least 130% of RHNA for each income category. Preliminary projections for the 6th Cycle indicate that the City will meet and exceed this threshold.
Policy Option B: Decrease development capacity assumptions and assumed affordability levels for all sites listed in inventory. While the City is “allowed” to count any residentially zoned site that allows at least 20 units per acre as being able to accommodate 100% affordable housing, that may not be the best approach because it is difficult to predict the exact affordability levels that future projects will achieve. Likewise, the City must apply reasonable development capacity assumptions to the site, and not simply assume that 100% of the site will be developed.
Most jurisdictions use a conservative figure between 70 and 75 percent of capacity will be achieved; analysis of past development patterns in Cotati indicates that an 80% development capacity assumption is appropriate.
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Policy Option C: Administrative “B” List of sites to be added as needed. This policy option has recently been used in Southern California Housing Elements prepared by 4LEAF, Inc. and accepted by HCD. This option treats the sites inventory as truly dynamic, and revisits it each year during the APR when, if necessary, additional sites that are appropriately zoned for housing can be added to the inventory list so that adequate sites are always assured. For this option, the City would maintain an administrative “B” list of sites that are appropriately zoned for housing but that were not the City’s first choice of sites to be listed in inventory. It is like Policy Option A in that the City still needs to have enough sites zoned to accommodate more than its RHNA, but it is not required to list those sites in inventory unless and until they are needed because a listed site developed at a lower capacity or affordability level. Under this option, a program would be included in the Housing Element to maintain an administrative list of qualified sites that could be added as needed during the APR at the beginning of each year. If the program is included in a certified Housing Element, then the revised inventory would not trigger a new HCD review of the Housing Element.
Recommendation: Options B and C. Development capacity assumptions should reflect the actual densities achieved for similar projects in the City. Likewise, assumed affordability levels should reflect the actual distribution of income groups across recent development projects. If development capacity and affordability assumptions are realistic and the City has additional sites beyond those needed to show an adequate inventory, then the ability to add sites to the inventory on an as-needed basis reduces the risk of falling into a net loss.
ISSUE #4: CONSIDERATION OF POTENTIAL NEW PROGRAMS
The 2023 Housing Element is an update of the existing Housing Element, and will retain most existing goals, policies, and programs. Programs that have been completed will be removed, and those that were not successfully implemented in the existing Housing Element will also be reviewed and either eliminated or revised and continued. New policies and programs will be added where needed to address new legislative requirements, to address housing needs and trends, and to affirmatively further fair housing.
Several new program concepts are offered below for discussion. Each concept would address an identified need or community preference, and most would incentivize diverse types of housing development within the City. The Council & Commission should consider new programs to facilitate housing development and increase the potential to demonstrate adequate sites. This workshop is an opportunity for the City to identify which policies are favorable to pursue in the upcoming Draft Housing Strategy; this is not an exhaustive list, but the beginning of a dialogue where the Council & Commission can provide feedback on these potential programs, as well as any other potential programs.
Housing on Church and School Sites. Churches and schools have traditionally been located within residential zones and are a part of the neighborhood fabric. Additional opportunities for housing types that would meet Cotati’s specific housing needs may exist on underutilized church and school sites. Existing uses on these sites could remain, with residential units added within underutilized areas. Any such development would be at the discretion and desire of the property
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owner. The allowance for the addition of housing on these sites could be made through a zoning text amendment, or through placement of the Workforce Housing Overlay discussed below. A zoning text amendment could open most or all church and school sites to residential uses; use of the overlay (below) would allow specific sites to be designated by the City Council.
Workforce Housing Overlay. This is a market-driven approach that gives the City control over where workforce housing can be allowed through a legislative process (City Council review).
The Workforce Housing Overlay Zone, once applied to a commercial or light industrial parcel, would allow any of the uses allowed by the underlying zoning, or multi- family housing (rental or ownership) at a density of 20 units per acre, or both. To qualify under HCD rules, the housing can only be subject to the same review process as the commercial and light industrial uses allowed by the underlying zoning. To use this option, the City would adopt a new Workforce Housing (W-H) Overlay Zone into the Zoning Code concurrent with the Housing Element adoption. The Housing Element would then include a program to add the W-H Overlay Zone to selected sites, either by an interested property owner or through the City’s rezoning action. The benefits of this approach are that it does not take away any allowed uses in the underlying zones; it provides greater flexibility in achieving mixed-use development by potentially expanding the locations where such development may be constructed; it is market-based so that property owners can choose the development type; it allows housing to be added to underutilized commercial sites, either vertically or horizontally; it allows business owners to live on-site or to provide housing for their employees on-site; and it allows the City to determine the specific sites that are suitable. The negatives are the cost of implementation, and the higher possibility that the “No Net Loss” law would come into play because of the different options for development.
City Density Bonus Program. California requires that a density bonus be granted to projects that provide a certain amount of their units as affordable. AB 2345 (2020) allows up to a 50% density bonus for eligible projects, and the exact percentage of affordable units required varies depending on the income level and whether the affordable units are rented or sold. A City density bonus program would meet this state requirement but go beyond it for projects that meet some of the City’s specified needs and to encourage development in existing Priority Development Areas. For example, a greater density bonus might be provided in exchange for more affordable units, a deeper level of affordability, the provision of some units as fully accessible or universally designed, the provision of childcare or eldercare on-site, or other identified city-specific needs. This type of program can incentivize development by providing a greater density bonus when certain criteria beyond the state’s requirements are met.
Incentivizing Smaller Units that are Affordable “By Design.” The Cotati City Council & Planning Commission approved the Cottage Housing Ordinance in 2021 to facilitate production of smaller housing units. The final adopted ordinance requires City Council approval of the projects’ “Housing Development Plan” for such projects and is primarily focused on detached housing types. Two potential programs are detailed below to further incentivize the production of smaller units through 1) calculating impact fees with Density Unit Equivalents, and 2) allowing missing middle housing with a locally tailored SB 10 ordinance. If there is Council interest, further programs could be incorporated to incentivize the development of co-housing, dormitory
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style homes, or communal housing units utilizing this “affordable by design” approach, specifically in existing Priority Development Areas where development can meet several community goals simultaneously and is more compatible with the surrounding land uses.
Density designations are calculated by the number of dwelling units allowed per acre. The traditional acreage-based density is the same regardless of the size of the unit—i.e., a project is allowed the same number of units per acre whether made up of studio apartments or fourbedroom apartments. This traditional framework incentivizes larger units because they count toward density allowances in the same manner as smaller units but are more profitable.
The concept of “density unit equivalents” would allow small units (studios, one- and twobedroom units under a certain size) to count as a fraction of a unit, and larger units (four+ bedroom units over a certain size) to count as more than one unit. This would encourage the development of more, smaller units, and discourage large units. For example, the provision of three micro-apartments could be considered equal to the provision of one three-bedroom unit in terms of the assigned unit density (see Table 2: Proposed Density Unit Equivalent, below).
Similarly, three 400 SF cottages or micro-units would be considered “equivalent” to a traditional 3-bedroom single family home.
Table 2: Example Density Unit Equivalents
Density Units
Micro-apartment or studio (<500
sf)
0.33 density unit
One bedroom (<750 sf) 0.50 density unit
Two bedrooms (<1,000 sf) 0.75 density unit
Three bedroom 1.00 density unit
Four or more bedrooms (>2,000
sf)
1.50 density units
A density bonus, if requested, would be applied to the mapped General Plan density.
Using the density unit equivalent concept, property owners or developers would be able to provide the number of density units in any combination. For example, consider a one-acre parcel with a mapped density of 10 units per acre. To meet the 10-unit count, a multifamily project could consist of 10 three-bedroom units, 15 one-bedroom units, or 30 micro-apartments. For a one-acre parcel with a mapped density of 5 units per acre, a single family development project could provide 5 three-bedroom units, or 10 one-bedroom cottages, or 15 efficiency units or tiny homes of less than 500 square feet. A combination of unit sizes can also be accommodated under this concept. The Council & Commission should note that unless development impact fees are also reduced to reflect the smaller unit sizes, the per-unit costs may remain too large to incentivize the construction of smaller, more affordable units.
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State legislation facilitating greater production of smaller units in smaller developments is now available. SB 10 (2021) was passed to facilitate residential-scale density of missing middle housing such as townhomes and low-rise multiplexes in existing residential zones. The bill allows a jurisdiction to streamline for developments of up to 10 units. Where such a decision could have previously jeopardized Housing Element certification timelines with costly and lengthy rezoning, the enabling legislation exempts such local ordinances from the California Environmental Quality Act (CEQA). Though the legislation allows rezoning of up to 10 units, lower unit counts can be adopted. The ordinance can be tailored to a variety of local needs, including eligible parcels or zones and development/design standards such as height, setbacks, and parking requirements. This program is an opportunity for the City to expand upon the Cottage Housing Ordinance by opting into an existing state program while retaining local control with a tailored ordinance that addresses Cotati’s unique housing needs and opportunities.
Summary:
The preliminary sites analysis indicates that Cotati’s can likely demonstrate adequate sites under existing zoning (density allowances) to meet the RHNA allocation. However, in order to meet statutory requirements of the State and HCD and the results of the housing needs assessment currently being conducted, it is anticipated that the City will likely need to adopt several programs to target these individual requirements. A program to rezone sites for inclusion in the sites inventory is not recommended because of the state requirements and potential penalties if the rezoning is not accomplished by the deadline. Rather, the Council & Commission should consider and provide direction on pursuing the following programs that would assist the City in meeting its identified housing needs without triggering the more restrictive rezoning obligations:
• Make full use of the allowance for ADUs at the affordability levels predetermined by the Association of Bay Area Governments and pre-certified by HCD, and facilitate more ADU/JADUs than the 3 per year safe harbor along with the adoption of programs to encourage and facilitate them; • Consider amending the Zoning Code to allow residential uses in conjunction with church (and possibly school) uses;
• Consider adopting a Workforce Housing Overlay Zone that allows attached housing developments with the same review process as development in the base zone;
• Consider creating a City density bonus program that goes beyond the state program where it can also further other specified City goals, particularly in Priority Development Areas;
• Consider a program for workforce housing to purchase existing multi-family, or new development in Priority Development Areas using joint powers authority
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financing tools (or other financing tools to facilitate such development available in state law);
• Consider creating a program to waive, set to zero, or pay down certain impact fees for very low-income affordable housing units;
• Consider incentivizing smaller units of all types that are “affordable by design” using dwelling unit equivalents, particularly in Priority Development Areas where this can simultaneously meet several City goals;
• Consider incentivizing affordable and/or missing middle housing with enhanced streamlining provisions and prioritizing the review of such projects over typical market rate development;
City Council & Planning Commission discussion and public input on the City’s different options is requested. This input will then be used to formalize the City’s draft Housing Element strategy, programs and policies.
Next Steps:
Following this public workshop with consideration of comments received thus far, 4LEAF will work with City staff to prepare a Draft Housing Strategy to be presented at the City Council public workshop in Spring 2022. The Draft Housing Strategy will consist of the housing goals, policies, and programs to be included in the 6th Cycle Housing Element. It will be informed by state law, the public input received to date, and direction provided by the City Council & Planning Commission. Public input on the preferred options will be important in understanding the community’s desires and goals.
• Draft Housing Strategy will be prepared for input at City Council workshop. (Target: April 2022)
• An HCD Draft Housing Element, including a Draft Housing Sites Inventory, will be prepared for a 30-day public review and then for a 90-day review by HCD, during which time public comment will also be considered. CEQA review will be completed at this time. (Target: Spring - Fall 2022)
• Following HCD review, a Draft Housing Element incorporating HCD’s requested changes and the CEQA document will be prepared for Planning Commission recommendation and City Council action. (Target: Late 2022) Public input will continue to be accepted at each of these review points. Although certification after only one final review is not guaranteed, Cotati’s HCD-reviewed 6th Cycle Housing Element must be adopted by the City Council no later than January 31, 2023 and certified within 120 days in order to achieve timely certification and for the City to remain in compliance with state housing law.
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Public Comment:
Separate from the surveys and input received through the engagement efforts detailed above, no specific public comments have been received pertaining to the information presented, as of the writing of this staff report.
Financial Considerations
The total anticipated cost of the Housing Element Update is $149,289, which is the anticipated total cost for the public engagement, CEQA analysis and the updated housing element itself. As the Council is aware, City staff have been successful in securing multiple grants specifically to cover the cost of State mandated housing efforts. These grants are anticipated to cover approximately $85,000 of the housing element update costs leaving a potential General Fund cost obligation of approximately $64,289. This falls within the $65,000 of General Fund monies allocated in FY21/22 for the Housing Element Update, therefore no additional budget requests are anticipated.
Environmental Issues
This action is an informational presentation only and as such, is not a project under the California Environmental Quality Act. The completed draft housing element will be analyzed under the requirements of the CEQA and a formal determination will be made prior to any decision actions on the proposed project.
Attachments:
ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (PDF) ATTACHMENT 2 - Preliminary Results from Cotati Community Survey (PDF)
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1 HOUSING NEEDS DATA REPORT: COTATI
ABAG/MTC Staff and Baird + Driskell Community Planning
2021-04-02
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 2 0.1 Table of content
0.1 Table of content.................................................................................................... 2
0.2 List of figures ....................................................................................................... 3
0.3 List of tables ........................................................................................................ 3 1 Introduction .............................................................................................................. 5 2 Summary of Key Facts .................................................................................................. 6 3 Looking to the Future: Regional Housing Needs .................................................................. 9
3.1 Regional Housing Needs Determination......................................................................... 9
3.2 Regional Housing Needs Allocation .............................................................................. 9 4 Population, Employment and Household Characteristics ..................................................... 11
4.1 Population ..........................................................................................................11
4.2 Age...................................................................................................................12
4.3 Race and Ethnicity ................................................................................................14
4.4 Employment Trends ...............................................................................................15
4.4.1 Balance of Jobs and Workers...............................................................................15
4.4.2 Sector Composition ..........................................................................................19
4.4.3 Unemployment ...............................................................................................20
4.5 Extremely Low-Income Households.............................................................................21
4.6 Tenure...............................................................................................................25
4.7 Displacement .......................................................................................................29 5 Housing Stock Characteristics ...................................................................................... 31
5.1 Housing Types, Year Built, Vacancy, and Permits............................................................31
5.2 Assisted Housing Developments At-Risk of Conversion......................................................34
5.3 Substandard Housing..............................................................................................35
5.4 Home and Rent Values............................................................................................36
5.5 Overpayment and Overcrowding ................................................................................39 6 Special Housing Needs................................................................................................ 48
6.1 Large Households ..................................................................................................48
6.2 Female-Headed Households......................................................................................49
6.3 Seniors...............................................................................................................51
6.4 People with Disabilities ..........................................................................................52
6.5 Homelessness.......................................................................................................54
6.6 Farmworkers .......................................................................................................59
6.7 Non-English Speakers .............................................................................................60
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 3 0.2 List of figures
Figure 1: Population Growth Trends .......................................................................................12 Figure 2: Population by Age, 2000-2019...................................................................................13 Figure 3: Senior and Youth Population by Race ..........................................................................14 Figure 4: Population by Race, 2000-2019 .................................................................................15 Figure 5: Jobs in a Jurisdiction .............................................................................................16 Figure 6: Workers by Earnings, by Jurisdiction as Place of Work and Place of Residence.........................17 Figure 7: Jobs-Worker Ratios, By Wage Group ...........................................................................18 Figure 8: Jobs-Household Ratio .............................................................................................19 Figure 9: Resident Employment by Industry ..............................................................................20 Figure 10: Unemployment Rate.............................................................................................21 Figure 11: Households by Household Income Level......................................................................23 Figure 12: Household Income Level by Tenure ...........................................................................24 Figure 13: Poverty Status by Race..........................................................................................25 Figure 14: Housing Tenure...................................................................................................26 Figure 15: Housing Tenure by Race of Householder .....................................................................27 Figure 16: Housing Tenure by Age..........................................................................................28 Figure 17: Housing Tenure by Housing Type ..............................................................................29 Figure 18: Households by Displacement Risk and Tenure...............................................................30 Figure 19: Housing Type Trends ............................................................................................31 Figure 20: Housing Units by Year Structure Built ........................................................................32 Figure 21: Vacant Units by Type............................................................................................33 Figure 22: Substandard Housing Issues.....................................................................................36 Figure 23: Home Values of Owner-Occupied Units.......................................................................37 Figure 24: Zillow Home Value Index (ZHVI)...............................................................................37 Figure 25: Contract Rents for Renter-Occupied Units...................................................................38 Figure 26: Median Contract Rent ...........................................................................................39 Figure 27: Cost Burden by Tenure ..........................................................................................40 Figure 28: Cost Burden by Income Level ..................................................................................41 Figure 29: Cost Burden by Race.............................................................................................42 Figure 30: Cost Burden by Household Size ................................................................................43 Figure 31: Cost-Burdened Senior Households by Income Level ........................................................44 Figure 32: Overcrowding by Tenure and Severity ........................................................................45 Figure 33: Overcrowding by Income Level and Severity ................................................................46 Figure 34: Overcrowding by Race...........................................................................................47 Figure 35: Household Size by Tenure ......................................................................................48 Figure 36: Housing Units by Number of Bedrooms .......................................................................49 Figure 37: Household Type ..................................................................................................50 Figure 38: Female-Headed Households by Poverty Status ..............................................................51 Figure 39: Senior Households by Income and Tenure....................................................................52 Figure 40: Disability by Type ................................................................................................53 Figure 41: Homelessness by Household Type and Shelter Status, Sonoma County .................................55 Figure 42: Racial Group Share of General and Homeless Populations, Sonoma County............................56 Figure 43: Latinx Share of General and Homeless Populations, Sonoma County....................................57 Figure 44: Characteristics for the Population Experiencing Homelessness, Sonoma County......................58 Figure 45: Farm Operations and Farm Labor by County, Sonoma County ............................................60 Figure 46: Population with Limited English Proficiency.................................................................61
0.3 List of tables
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 4 Table 1: Illustrative Regional Housing Needs Allocation from Draft Methodology ..................................10 Table 2: Population Growth Trends ........................................................................................11 Table 3: Housing Permitting.................................................................................................33 Table 4: Assisted Units at Risk of Conversion.............................................................................34 Table 5: Population with Developmental Disabilities by Age ..........................................................54 Table 6: Population with Developmental Disabilities by Residence...................................................54 Table 7: Students in Local Public Schools Experiencing Homelessness ...............................................59 Table 8: Migrant Worker Student Population .............................................................................59
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 5 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 our growth and housing challenges. Required by the state, the Housing Element identifies what the existing housing conditions and community needs are, reiterates goals, and creates a plan for more housing. The Housing Element is an integral part of the General Plan, which guides the policies of Cotati.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 6 2 SUMMARY OF KEY FACTS
• Population – Generally, the population of the Bay Area continues to grow because of natural growth and because the strong economy draws new residents to the region. The population of Cotati increased by 16.4% from 2000 to 2020, which is above the growth rate of the Bay Area. • Age – In 2019, Cotati’s youth population under the age of 18 was 1,691 and senior population 65 and older was 977. These age groups represent 22.7% and 13.1%, respectively, of Cotati’s population.
• Race/Ethnicity – In 2020, 74.5% of Cotati’s population was White while 0.6% was African American, 2.0% was Asian, and 18.4% was Latinx. People of color in Cotati comprise a proportion below the overall proportion in the Bay Area as a whole.1 • Employment – Cotati residents most commonly work in the Health & Educational Services industry. From January 2010 to January 2021, the unemployment rate in Cotati decreased by
8.8 percentage points. Since 2010, the number of jobs located in the jurisdiction increased by 1,020 (43.4%). Additionally, the jobs-household ratio in Cotati has increased from 0.84 in 2002 to 1.14 jobs per household 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. The number of homes in Cotati increased, 2.2% from 2010 to 2020, which is above the growth rate for Sonoma County and below the growth rate of the region’s housing stock during this time period.
• Home Prices – A diversity of homes at all income levels creates opportunities for all Cotati residents to live and thrive in the community.
– Ownership The largest proportion of homes had a value in the range of $500k-$750k in 2019. Home prices increased by 84.7% from 2010 to 2020. – Rental Prices – The typical contract rent for an apartment in Cotati was $1,470 in 2019. Rental prices increased by 41.3% from 2009 to 2019. To rent a typical apartment without cost burden, a household would need to make $59,120 per year.2 • Housing Type – It is important to have a variety of housing types to meet the needs of a community today and in the future. In 2020, 45.6% of homes in Cotati were single family detached, 19.1% were single family attached, 14.1% were small multifamily (2-4 units), and
17.3% were medium or large multifamily (5+ units). Between 2010 and 2020, the number of single-family units increased more than multi-family units. Generally, in Cotati, the share of
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.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 7 the housing stock that is detached single family homes is below 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 Cotati, 24.6% of households spend 30%-50% of their income on housing, while 14.5% of households are severely cost burden and use the majority of their income for housing.
• Displacement/Gentrification – According to research from The University of California, Berkeley, 54.2% of households in Cotati live in neighborhoods that are susceptible to or experiencing displacement, and 0.0% live in areas at risk of or undergoing gentrification. 2.9% of households in Cotati 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 at all income levels is built.
• Neighborhood – 0.0% of residents in Cotati live in neighborhoods identified as “Highest Resource” or “High Resource” areas by State-commissioned research, while 55.9% of residents live in areas identified by this research as “Low Resource” or “High Segregation and Poverty” areas. These neighborhood designations are based on a range of indicators covering areas 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 Cotati, 10.3% of residents have a disability of any kind and may require accessible housing. Additionally, 12.2% of Cotati households are larger households with five or more people, who likely need larger housing units with three bedrooms or more. 14.3% of households are female-headed families, which are often at greater risk of housing insecurity.
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
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.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 8 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.
Additionally, there may be instances where there is no data available for a jurisdiction for particular data point, or where a value is 0 and the automatically generated text cannot perform a calculation. In these cases, the automatically generated text is “NODATA.” Staff should reword these sentences before using them in the context of the Housing Element or other documents.
Note on Figures
Any figure that does not specify geography in the figure name represents data for Cotati.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 9 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 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.5 This calculation, known as 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 need. The adjustments result from recent legislation requiring HCD to apply additional adjustment factors to the baseline growth projection from California Department of Finance, in order 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 the share of cost burdened households, and seek to bring the region more in line with comparable ones.6 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.
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 or RHNA – the share of the RHND assigned to each jurisdiction by the Association of Bay Area Governments (ABAG). State Housing Element Law requires ABAG to develop a methodology that calculates the number of housing units assigned to each city and county and distributes 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-needsallocation Almost all jurisdictions in the Bay Area are likely to receive a larger RHNA this cycle compared to the last cycle, primarily due to changes in state law that led to a considerably higher RHND compared to previous cycles.
In January 2021, ABAG adopted a Draft RHNA Methodology, which is currently being reviewed by HCD.
For Cotati, the proposed RHNA to be planned for this cycle is 234 units, a slated increase from the last cycle. Please note that the previously stated figures are merely illustrative, as ABAG has yet to issue Final RHNA allocations. The Final RHNA allocations that local jurisdictions will use for their
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 HCD divides the RHND into the following four income categories:
Very Low-income: 0-50% of Area Median Income
Low-income: 50-80% of Area Median Income
Moderate-income: 80-120% of Area Median Income
Above Moderate-income: 120% or more of Area Median Income 6 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
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 10 Housing Elements will be released at the end of 2021. The potential allocation that Cotati would receive from the Draft RHNA Methodology is broken down by income category as follows:
Table 1: Illustrative Regional Housing Needs Allocation from Draft Methodology Income Group Cotati
Units
Sonoma
County Units
Bay Area
Units
Cotati
Percent
Sonoma
County
Percent
Bay Area
Percent
Very Low Income
(<50% of AMI) 60 3999 114442 25.6% 27.5% 25.9%
Low Income (50%-80%
of AMI) 34 2302 65892 14.5% 15.8% 14.9%
Moderate Income
(80%-120% of AMI) 39 2302 72712 16.7% 15.8% 16.5%
Above Moderate
Income (>120% of
AMI)
101 5959 188130 43.2% 40.9% 42.6%
Total 234 14562 441176 100.0% 100.0% 100.0%
Source: Association of Bay Area Governments Methodology and tentative numbers were approved by ABAG’s Executive board on January 21, 2021 (Resolution No. 02-2021). The numbers were submitted for review to California Housing and Community Development in February 2021, after which an appeals process will take place during the Summer and Fall of 2021.
THESE NUMBERS SHOULD BE CONSIDERED PRELIMINARY AND SUBJECT TO CHANGE PER HCD REVIEW
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 11 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, except for 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, Cotati’s population has increased by 16.4%; this rate is above that of the region as a whole, at 14.8%. In Cotati, roughly 11.8% of its population moved during the past year, a number 1.6 percentage points smaller than the regional rate of 13.4%.
Table 2: Population Growth Trends
Geography 1990 1995 2000 2005 2010 2015 2020
Cotati 5714 6471 6471 7185 7265 7367 7533
Sonoma County 388222 416776 458614 475703 483878 500640 492980 Bay Area 6020147 6381961 6784348 7073912 7150739 7595694 7790537 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.
In 2020, the population of Cotati was estimated to be 7,533 (see Table 2). From 1990 to 2000, the population increased by 13.2%, while it increased by 12.3% during the first decade of the 2000s. In the most recent decade, the population increased by 3.7%. The population of Cotati makes up 1.5% of Sonoma County.7
7 To compare the rate of growth across various geographic scales, Figure 1 shows population for the jurisdiction, county, and region indexed to the population in the year 1990. This means that the data points represent the population growth (i.e. percent change) in each of these geographies relative to their populations in 1990.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 12 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.
For some jurisdictions, a break may appear at the end of each decade (1999, 2009) as estimates are compared to census counts.
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.
4.2 Age
The distribution of age groups in a city shapes what types of housing the community may need in the near future. An increase in the older population may mean there is a developing need for more senior housing options, while higher numbers of children and young families can point to the need for more family housing options and related services. There has also been a move by many to age-in-place or downsize to stay within their communities, which can mean more multifamily and accessible units are also needed.
In Cotati, the median age in 2000 was 33; by 2019, this figure had increased, landing at around 36 years. More specifically, the population of those under 14 has increased since 2010, while the 65-andover population has increased (see Figure 2).
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 13 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 senior and youth population by race can add an additional layer of understanding, as families and seniors of color are even more likely to experience challenges finding affordable housing.
People of color8 make up 11.5% of seniors and 21.8% of youth under 18 (see Figure 3).
8 Here, we count all non-white racial groups
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 14 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 has occurred over time and continues to impact communities of color today9. Since 2000, the percentage of residents in Cotati identifying as White has decreased – and by the same token the percentage of residents of all other races and ethnicities has increased – by 5.2 percentage points, with the 2019 population standing at 5,555 (see Figure 4). In absolute terms, the White, Non-Hispanic population increased the most while the Black or African American, Non-Hispanic population decreased the most.
9 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.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 15 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
4.4.1 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 will have more employed residents than jobs there 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 this 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. A city with a surplus of workers “exports” workers to other parts of the region, while a city with a surplus of jobs must conversely “import” them. Between 2002 and 2018, the number of jobs in Cotati increased by 53.5% (see Figure 5).
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 16 Figure 5: Jobs in a Jurisdiction
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.
There are 3,977 employed residents, and 3,126 jobs10 in Cotati - the ratio of jobs to resident workers is
0.79; Cotati is a net exporter of workers.
Figure 6 shows the balance when comparing jobs to workers, broken down by different wage groups, offering additional insight into local dynamics. A community may offer employment for relatively lowincome 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 a given wage category suggests the need to import those workers, while conversely, surpluses of workers in a wage group relative to jobs means the community will export those workers to other jurisdictions. Such flows are not inherently bad, though over time, sub-regional imbalances may appear. Cotati has more low-wage jobs than low-wage residents (where low-wage refers to jobs paying less than $25,000). At the other end of the wage
10 Employed residents in a jurisdiction is counted by place of residence (they may work elsewhere) while jobs in 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.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 17 spectrum, the city has more high-wage residents than high-wage jobs (where high-wage refers to jobs paying more than $75,000) (see Figure 6).
11 Figure 6: Workers by Earnings, by 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 in a wage group as it has resident workers - in principle, a balance. Values above 1 indicate a jurisdiction will need to import workers for jobs in a given wage group. At the regional scale, this ratio is 1.04 jobs for each worker, implying a modest import of workers from outside the region (see Figure 7).
11 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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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 18 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 Data Packet Workbook, Table POPEMP-14.
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 not only means many workers will need to prepare for long commutes and time spent on the road, but in the aggregate it contributes to traffic congestion and time lost for all road users.
If 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 jobs-household ratio in Cotati has increased from 0.84 in 2002, to 1.14 jobs per household in 2018 (see Figure 8).
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 19 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 jobs-housing 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.
4.4.2 Sector Composition
In terms of sectoral composition, the largest industry in which Cotati residents work is Health & Educational Services, and the largest sector in which Sonoma residents work is Health & Educational Services (see Figure 9). For the Bay Area as a whole, the Health & Educational Services industry employs the most workers.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 20 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.
4.4.3 Unemployment
In Cotati, there was a 8.8 percentage point decrease in the unemployment rate between January 2010 and January 2021. Jurisdictions through the region experienced a sharp rise in unemployment in 2020 due to impacts related to the COVID-19 pandemic, though with a general improvement and recovery in the later months of 2020.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 21 Figure 10: 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 seasonallyadjusted 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 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 low-income households in the state12.
In Cotati, 55.9% of households make more than 100% of the Area Median Income (AMI)13, compared to
10.1% making less than 30% of AMI, which is considered extremely low-income (see Figure 11).
12 Bohn, S.et al. 2020. Income Inequality and Economic Opportunity in California. Public Policy Institute of California.
13 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
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 22 Regionally, more than half of all households make more than 100% AMI, while 15% make less than 30% AMI. In Sonoma County, 30% AMI is the equivalent to the annual income of $29,450 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.
Note on Estimating the Projected Number of Extremely Low-Income Households Local jurisdictions are required to provide an estimate for their projected extremely low-income households 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. For more information, visit HCD’s Building Blocks page on Extremely Low-Income Housing Needs.
This document does not contain the required data point of projected extremely low-income households, as Bay Area jurisdictions have not yet received their final RHNA numbers. Once Cotati receives its 6th Cycle RHNA, staff can estimate the projected extremely low-income households using one of the following three methodologies:
Option A: Assume that 59.8% of Cotati’s very low-income RHNA is for extremely low-income households.
According to HCD’s Regional Housing Need Determination for the Bay Area, 15.5% of the region’s housing need is for 0-30% AMI households while 25.9% is for 0-50% AMI households. Therefore, extremely low-income housing need represents 59.8% of the region’s very low-income housing need, as 15.5 divided by 25.9 is 59.8%. This option aligns with HCD’s guidance to use U.S. Census data to calculate the percentage of very low-income RHNA that qualifies for extremely low-income households, as HCD uses U.S. Census data to calculate the Regional Housing Need Determination.
Option B: Assume that 45.7% of Cotati’s very low-income RHNA is for extremely low-income households.
According to the data shown below (Figure 11), 624 of Cotati’s households are 0-50% AMI while 285 are extremely low-income. Therefore, extremely low-income households represent 45.7% of households who are 0-50% AMI, as 285 divided by 624 is 45.7%. This option aligns with HCD’s guidance to use U.S. Census data to calculate the percentage of very low-income RHNA that qualifies for extremely low-income households, as the information in Figure 11 represents a tabulation of Census Bureau Data.
Option C: Assume that 50% of Cotati’s very low-income RHNA is for extremely low-income households.
HCD’s guidance notes that instead of using use U.S. Census data to calculate the percentage of very low-income RHNA that qualifies for extremely low-income households, local jurisdictions can presume that 50% of their RHNA for very low-income households qualifies for extremely low-income households.
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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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 23 Figure 11: 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.
Throughout the region, there are 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.
In Cotati, the largest proportion of renters falls in the Greater than 100% of AMI income group, while the largest proportion of homeowners are found in the Greater than 100% of AMI group (see Figure 12).
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 24 Figure 12: Household Income Level by Tenure
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.
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.
Currently, people of color are more likely to experience poverty and financial instability as a result of federal and local housing policies that have historically excluded them from the same opportunities extended to white residents.14 These economic disparities also leave communities of color at higher risk for housing insecurity, displacement or homelessness. In Cotati, Black or African American (Hispanic and Non-Hispanic) residents experience the highest rates of poverty, followed by Other Race or Multiple Races (Hispanic and Non-Hispanic) residents (see Figure 13).
14 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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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 25 Figure 13: 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.
4.6 Tenure
The number of residents who own their homes compared to those who rent their homes can help identify the level of housing insecurity – ability for individuals to stay in their homes – in a city and region. Generally, renters may be displaced more quickly if prices increase. In Cotati there are a total of 2,758 housing units, and fewer residents rent than own their homes: 43.3% versus 56.7% (see Figure 14). By comparison, 38.5% of households in Sonoma County are renters, while 44% of Bay Area households rent their homes.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 26 Figure 14: 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 policy are still evident across Bay Area communities.15 In Cotati, 100.0% of Black households owned their homes, while homeownership rates were 85.1% for Asian households, 33.1% for Latinx households, and 56.4% for White households. Notably, recent changes to state law require local jurisdictions to examine these dynamics and other fair housing issues when updating their Housing Elements.
15 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.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 27 Figure 15: 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.
The age of residents who rent or own their home can also signal the housing challenges a community is experiencing. Younger households tend to rent and may struggle to buy a first home in the Bay Area due to high housing costs. At the same time, senior homeowners seeking to downsize may have limited options in an expensive housing market.
In Cotati, 58.3% of householders between the ages of 25 and 44 are renters, while 20.9% of householders over 65 are (see Figure 16).
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 28 Figure 16: 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.
In many cities, homeownership rates for households in single-family homes are substantially higher than the rates for households in multi-family housing. In Cotati, 74.6% of households in detached single-family homes are homeowners, while 11.6% of households in multi-family housing are homeowners (see Figure 17).
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 29 Figure 17: 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.
4.7 Displacement
Because of 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, Berkeley has mapped all neighborhoods in the Bay area, identifying their risk for gentrification. They find that in Cotati, 54.2% of households live in neighborhoods that are susceptible to or experiencing displacement and 0.0% live in neighborhoods at risk of or undergoing gentrification.
Equally important, some neighborhoods in the Bay Area do not have housing appropriate for a broad section of the workforce. UC Berkeley estimates that 2.9% of households in Cotati live in neighborhoods where low-income households are likely to be excluded due to prohibitive housing costs.16
16 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 18 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-area-gentrification-and-displacement
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 30 Figure 18: 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: LowIncome/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.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 31 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 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 up more options across incomes and tenure, from young households seeking homeownership options to seniors looking to downsize and age-in-place.
The housing stock of Cotati in 2020 was made up of 45.6% single family detached homes, 19.1% single family attached homes, 14.1% multifamily homes with 2 to 4 units, 17.3% multifamily homes with 5 or more units, and 3.9% mobile homes (see Figure 19). In Cotati, the housing type that experienced the most growth between 2010 and 2020 was Single-Family Home: Attached.
Figure 19: 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.
Production has not kept up with housing demand for several decades in the Bay Area, as the total number of units built and available has not yet come close to meeting the population and job growth experienced throughout the region. In Cotati, the largest proportion of the housing stock was built 1980 to 1999, with 1,199 units constructed during this period (see Figure 20). Since 2010, 3.2% of the current housing stock was built, which is 93 units.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 32 Figure 20: 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 make up 5.3% of the overall housing stock in Cotati. The rental vacancy stands at 3.9%, while the ownership vacancy rate is 2.1%. Of the vacant units, the most common type of vacancy is Other Vacant (see Figure 21).17
Throughout the Bay Area, vacancies make up 2.6% of the total housing units, with homes listed for rent; units used for 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. Vacant units classified as “for recreational or occasional use” are those that are held for shortterm periods of use throughout the year. Accordingly, vacation rentals and short-term rentals like AirBnB are likely to fall in this category. The Census Bureau classifies units as “other vacant” if they are vacant due to foreclosure, personal/family reasons, legal proceedings, repairs/renovations, abandonment, preparation for being rented or sold, or vacant for an extended absence for reasons such as a work assignment, military duty, or incarceration.18 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 likely to represent a large portion of the “other vacant” category. Additionally, the need for seismic retrofitting
17 The vacancy rates by tenure is for a smaller universe than the total vacancy rate first reported, which in principle includes the full stock (5.3%). The vacancy by tenure counts are rates relative to the rental stock (occupied and vacant) and ownership stock (occupied and vacant) - but exclude a a significant number of vacancy categories, including the numerically significant other vacant. 18 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.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 33 in older housing stock could also influence the proportion of “other vacant” units in some jurisdictions.19
Figure 21: 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.
Between 2015 and 2019, 80 housing units were issued permits in Cotati. 55.0% of permits issued in Cotati were for above moderate-income housing, 18.8% were for moderate-income housing, and 26.2% were for low- or very low-income housing (see Table 3).
Table 3: Housing Permitting
Income Group value
Above Moderate Income Permits 44
Low Income Permits 16
Moderate Income Permits 15
Very Low Income Permits 5
Universe: Housing permits issued between 2015 and 2019
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. Low Income: 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
19 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.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 34 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)
This table is included in the Data Packet Workbook as Table HSG-11.
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. Additionally, it is typically faster and less expensive to preserve currently affordable units that are at risk of converting to market-rate than it is to build new affordable housing.
The data in the table below comes from the California Housing Partnership’s Preservation Database, 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. However, this database does not include all deed-restricted affordable units in the state, so there may be at-risk assisted units in a jurisdiction that are not captured in this data table. There are 147 assisted units in Cotati in the Preservation Database. Of these units, 0.0% are at High Risk or Very High Risk of conversion.20 Note on At-Risk Assisted Housing Developments
HCD requires that Housing Elements list the assisted housing developments at risk of converting to market-rate uses. For more information on the specific properties that are at Moderate Risk, High Risk, or Very High Risk of conversion, local jurisdiction staff should contact Danielle Mazzella, Preservation & Data Manager at the California Housing Partnership, at [email protected].
Table 4: Assisted Units at Risk of Conversion
Income Cotati Sonoma County Bay Area
Low 147 7195 110177
Moderate 0 68 3375
High 0 267 1854
Very High 0 149 1053
Total Assisted Units in Database 147 7679 116459
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.
20 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, mission-driven developer.
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.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 35 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 at-risk 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. California Housing Partnership uses the following categories for assisted housing developments in its database: Very-High Risk: affordable homes that are atrisk 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, mission-driven developer. 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 atrisk of converting to market rate in 10+ years and/or are owned by a large/stable non-profit, mission-driven developer.
Source: California Housing Partnership, Preservation Database (2020) This table is included in the Data Packet Workbook as Table RISK-01.
5.3 Substandard Housing
Housing costs in the region are among the highest in the country, which could result in households, particularly renters, needing to live in substandard conditions in order to afford housing. Generally, there is limited data on the extent of substandard housing issues in a community. However, the Census Bureau data included in the graph below gives a sense of some of the substandard conditions that may be present in Cotati. For example, 0.8% of renters in Cotati reported lacking a kitchen and 0.0% of renters lack plumbing, compared to 1.2% of owners who lack a kitchen and 1.2% of owners who lack plumbing.
Note on Substandard Housing
HCD requires Housing Elements to estimate the number of units in need of rehabilitation and replacement. As a data source for housing units in need of rehabilitation and replacement is not available for all jurisdictions in the region, ABAG was not able to provide this required data point in this document. To produce an estimate of housing needs in need of rehabilitation and replacement, staff can supplement the data below on substandard housing issues with additional local information from code enforcement, recent windshield surveys of properties, building department data, knowledgeable builders/developers in the community, or nonprofit housing developers or organizations. For more information, visit HCD’s Building Blocks page on Housing Stock Characteristics.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 36 Figure 22: 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.
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 Bay Area, the costs of housing have long been among the highest in the nation. The typical home value in Cotati was estimated at $629,580 by December of 2020, per data from Zillow. The largest proportion of homes were valued between $500k-$750k (see Figure 23). By comparison, the typical home value is $691,580 in Sonoma County and $1,077,230 the Bay Area, with the largest share of units valued $500k-$750k.
The region’s home values have increased steadily since 2000, besides a decrease during the Great Recession. The rise in home prices has been especially steep since 2012, with the median home value in the Bay Area nearly doubling during this time. Since 2001, the typical home value has increased
70.9% in Cotati from $368,280 to $629,580. This change is above the change in Sonoma County, and below the change for the region (see Figure 24).
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 37 Figure 23: 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.
Figure 24: 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
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 38 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)
For the data table behind this figure, please refer to the Data Packet Workbook, Table HSG-08.
Similar to home values, rents have also 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, and sometimes, out of the state.
In Cotati, the largest proportion of rental units rented in the Rent $1000-$1500 category, totaling
30.7%, followed by 24.8% of units renting in the Rent $1500-$2000 category (see Figure 25). Looking beyond the city, the largest share of units is in the $1000-$1500 category (county) compared to the $1500-$2000 category for the region as a whole.
Figure 25: 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.
Since 2009, the median rent has increased by 41.3% in Cotati, from $1,140 to $1,470 per month (see Figure 26). In Sonoma County, the median rent has increased 22.7%, from $1,200 to $1,470. The median rent in the region has increased significantly during this time from $1,200 to $1,850, a 54% increase.21
21 While the data on home values shown in Figure 24 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
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 39 Figure 26: 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.
5.5 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 income on housing puts low-income households at higher risk of displacement, eviction, or homelessness.
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.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 40 Figure 27: 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). 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.
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.
Renters are often more cost-burdened than owners. While the housing market has resulted in home prices increasing dramatically, homeowners often have mortgages with fixed rates, whereas renters are more likely to be impacted by market increases. When looking at the cost burden across tenure in Cotati, 29.3% of renters spend 30% to 50% of their income on housing compared to 17.2% of those that own (see Figure 27). Additionally, 18.2% of renters spend 50% or more of their income on housing, while 10.3% of owners are severely cost-burdened.
In Cotati, 14.5% of households spend 50% or more of their income on housing, while 24.6% spend 30% to 50%. However, these rates vary greatly across income categories (see Figure 28). For example, 58.4% of Cotati households making less than 30% of AMI spend the majority of their income on housing. For Cotati residents making more than 100% of AMI, just 2.5% are severely cost-burdened, and 85.0% of those making more than 100% of AMI spend less than 30% of their income on housing.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 41 Figure 28: 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.
Currently, people of color are more likely to experience poverty and financial instability as a result of federal and local housing policies that have historically excluded them from the same opportunities extended to white residents. As a result, they often pay a greater percentage of their income on housing, and in turn, are at a greater risk of housing insecurity.
Hispanic or Latinx residents are the most cost burdened with 35.4% spending 30% to 50% of their income on housing, and Asian / API, Non-Hispanic residents are the most severely cost burdened with
50.0% spending more than 50% of their income on housing (see Figure 29).
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 42 Figure 29: 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.
Large family households often have special housing needs due to a lack of adequately sized affordable housing available. The higher costs required for homes with multiple bedrooms can result in larger families experiencing a disproportionate cost burden than the rest of the population and can increase the risk of housing insecurity.
In Cotati, 14.3% of large family households experience a cost burden of 30%-50%, while 5.9% of households spend more than half of their income on housing. Some 25.5% of all other households have a cost burden of 30%-50%, with 15.2% of households spending more than 50% of their income on housing (see Figure 30).
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 43 Figure 30: 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). 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.
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, putting 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. 33.7% of seniors making less than 30% of AMI are spending the majority of their income on housing. For seniors making more than 100% of AMI, 75.0% are not cost-burdened and spend less than 30% of their income on housing (see Figure 31).
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 44 Figure 31: 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 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 JoseSunnyvale-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.
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 that are renting, with multiple households sharing a unit to make it possible to stay in their communities. In Cotati, 3.1% of households that rent are severely overcrowded (more than 1.5 occupants per room), compared to 0.0% of households that own (see Figure 32). In Cotati, 14.6% of renters experience moderate overcrowding (1 to 1.5 occupants per room), compared to 1.3% for those own.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 45 Figure 32: Overcrowding by Tenure 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.
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.
Overcrowding often disproportionately impacts low-income households. 0.0% of very low-income households (below 50% AMI) experience severe overcrowding, while 0.0% of households above 100% experience this level of overcrowding (see Figure 33).
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 46 Figure 33: 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 similar to how they are more likely to experience poverty, financial instability, and housing insecurity. People of color tend to experience overcrowding at higher rates than White residents. In Cotati, the racial group with the largest overcrowding rate is Hispanic or Latinx (see Figure 34)
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 47 Figure 34: 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 nonHispanic/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.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 48 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 who rent could end up living in overcrowded conditions. In Cotati, for large households with 5 or more persons, most units (51.5%) are renter occupied (see Figure 35). In 2017, 8.4% of large households were very low-income, earning less than 50% of the area median income (AMI).
Figure 35: 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.
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 3 or more bedrooms, of which there are 1,565 units in Cotati. Among these large units with 3 or more bedrooms, 25.6% are owner-occupied and 74.4% are renter occupied (see Figure 36).
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 49 Figure 36: 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.
6.2 Female-Headed Households
Households headed by one person are often at greater risk of housing insecurity, particularly femaleheaded households, who may be supporting children or a family with only one income. In Cotati, the largest proportion of households is Married-couple Family Households at 45.6% of total, while FemaleHeaded Households make up 14.3% of all households.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 50 Figure 37: 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 particular 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 Cotati, 20.1% of female-headed households with children fall below the Federal Poverty Line, while
14.8% of female-headed households without children live in poverty (see Figure 38).
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 51 Figure 38: 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.
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/or reduced mobility.
Seniors who rent may be at 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 39).
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 52 Figure 39: 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 JoseSunnyvale-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.
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 are in need of 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, the need typically outweighs what is available, 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 40 shows the rates at which different disabilities are present among residents of Cotati. Overall, 10.3% of people in Cotati have a disability of any kind.22
22 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.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 53 Figure 40: 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.
State law also requires Housing Elements to examine the housing needs of people with developmental disabilities. Developmental disabilities are defined as severe, chronic, and attributed to a mental or physical impairment that begins before a person turns 18 years old. This can include Down’s Syndrome, autism, epilepsy, cerebral palsy, and mild to severe mental retardation. Some people with developmental disabilities are unable to work, rely on Supplemental Security Income, and live with family members. In addition to their specific housing needs, they are at increased risk of housing insecurity after an aging parent or family member is no longer able to care for them.23 In Cotati, of the population with a developmental disability, children under the age of 18 make up
39.3%, while adults account for 60.7%.
23 For more information or data on developmental disabilities in your jurisdiction, contact the Golden Gate Regional Center for Marin, San Francisco and San Mateo Counties; the North Bay Regional Center for Napa, Solano and Sonoma Counties; the Regional Center for the East Bay for Alameda and Contra Costa Counties; or the San Andreas Regional Center for Santa Clara County.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 54 Table 5: Population with Developmental Disabilities by Age Age Group value
Age 18+ 34
Age Under 18 22
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 Age Group (2020) This table is included in the Data Packet Workbook as Table DISAB-04.
The most common living arrangement for individuals with disabilities in Cotati is the home of parent /family /guardian.
Table 6: Population with Developmental Disabilities by Residence Residence Type value
Home of Parent /Family /Guardian 40
Independent /Supported Living 15
Foster /Family Home 4
Other 0
Intermediate Care Facility 0
Community Care Facility 0
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.
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 experienced by people of color, people with disabilities, those struggling with addiction and those dealing with traumatic life circumstances. In Sonoma 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, 71.2% are unsheltered. Of homeless households with children, most are sheltered in emergency shelter (see Figure 41).
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 55 Figure 41: Homelessness by Household Type and Shelter Status, Sonoma 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.
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.
People of color are more likely to experience poverty and financial instability as a result 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 Sonoma County, White (Hispanic and Non-Hispanic) residents represent the largest proportion of residents experiencing homelessness and account for
64.7% of the homeless population, while making up 74.8% of the overall population (see Figure 42).
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 56 Figure 42: Racial Group Share of General and Homeless Populations, Sonoma 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.
In Sonoma, Latinx residents represent 28.2% of the population experiencing homelessness, while Latinx residents comprise 26.5% of the general population (see Figure 43).
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 57 Figure 43: Latinx Share of General and Homeless Populations, Sonoma 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.
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-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 Sonoma County, homeless individuals are commonly challenged by chronic substance abuse, with 1,015 reporting this condition (see Figure 12). Of those, some 80.5% are unsheltered, further adding to the challenge of handling the issue.
Note on Homelessness Data
Notably all the data on homelessness provided above is for the entire county. This data comes from the Department of Housing and Urban Development’s (HUD) Point in Time count, which is the most comprehensive publicly available data source on people experiencing homelessness. HUD only provides this data at the countylevel and not for specific jurisdictions. However, Housing Element law requires local jurisdictions to estimate or count of the daily average number of people lacking shelter. Therefore, staff will need to supplement the data in this document with additional local data on the number of people experiencing homelessness. If staff do not have estimates of people experiencing homelessness in their jurisdiction readily available, HCD recommends contacting local service providers such as continuum-of-care providers, local homeless shelter and service providers, food
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 58 programs, operators of transitional housing programs, local drug and alcohol program service providers, and county mental health and social service departments.24
Figure 44: Characteristics for the Population Experiencing Homelessness, Sonoma 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.
In Cotati, there were no reported students experiencing homeless in the 2019-20 school year. By comparison, Sonoma County has seen a 12.9% 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 2019-2020 school year, there were still some 13,718 students experiencing homelessness throughout the region, adding undue burdens on learning and thriving, with the potential for longer term negative effects.
24 For more information, see HCD’s Building Blocks webpage for People Experiencing Homelessness:
https://www.hcd.ca.gov/community-development/building-blocks/housing-needs/people-experiencinghomelessness.shtml
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 59 Table 7: Students in Local Public Schools Experiencing Homelessness AcademicYear Cotati Sonoma County Bay Area
2016-17 0 690 14990
2017-18 0 1445 15142
2018-19 0 345 15427
2019-20 0 601 13718
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.
6.6 Farmworkers
Across the state, housing for farmworkers has been recognized as an important and unique concern.
Farmworkers generally receive wages that are considerably lower than other jobs and may have temporary housing needs. Finding decent and affordable housing can be challenging, particularly in the current housing market.
In Cotati, 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 3.5% increase in the number of migrant worker students since the 2016-17 school year.
Table 8: Migrant Worker Student Population
AcademicYear Cotati Sonoma County Bay Area
2016-17 0 825 4630
2017-18 0 789 4607
2018-19 0 738 4075
2019-20 0 854 3976
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) This table is included in the Data Packet Workbook as Table FARM-01.
According to the U.S. Department of Agriculture Census of Farmworkers, the number of permanent farm workers in Sonoma County has increased since 2002, totaling 6,715 in 2017, while the number of seasonal farm workers has decreased, totaling 7,664 in 2017 (see Figure 45).
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 60 Figure 45: Farm Operations and Farm Labor by County, Sonoma 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 United States, which means that many languages are spoken throughout the Bay Area. Since learning a new language is universally challenging, it is not uncommon for residents who have immigrated to the United States 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 Cotati, 4.6% of residents 5 years and older identify as speaking English not well or not at all, which is below the proportion for Sonoma County.
Throughout the region the proportion of residents 5 years and older with limited English proficiency is 8%.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) 61 Figure 46: 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.
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Attachment: ATTACHMENT 1 - ABAG_MTC_Housing_Needs_Data_Report_Cotati_w_toc (6th Housing Element Update Draft Roll Out) ATTACHMENT 2. PRELIMINARY RESULTS FROM COMMUNITY SURVEY
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