City Council/Public Finance and Economic Development Authority/Parking Authority
May 20, 2024

Final Regional Housing Needs
Allocation (RHNA) Plan:

CYCLE 6 (JUNE 30 TH, 2023 - JANUARY 31 ST, 2032)
Merced County Region
Adopted Per Resolution 2022/11-17-02
November 17, 2022

1 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

TABLE OF CONTENTS

0. Executive Summary .......................................................................................................................2

1. Introduction to the Cycle 6 RHNA ...............................................................................................8

2. RHNA Objectives and Factors ...................................................................................................12

3. Determination of Need ................................................................................................................23

4. Adopted RHNA Methodology ....................................................................................................26

5. Appendices ....................................................................................................................................37 List of Tables
Table 1: Cycle 6 (2023 - 2031) Adopted RHNA Methodology Summary Table ......................6 Table 2: Considered RHNA Adjustment Factors.........................................................................28 Table 3: Selected RHNA Adjustment Factors............................................................................. 29 Table 4: Baseline Total RHNA Calculations (Step 1) ..................................................................30 Table 5: Total Housing Need Adjustment Options (Step 2).......................................................31 Table 6 Below-Moderate-Income Adjustment Factors and Their Impacts (Step 3).............32 Table 7: Cycle 6 (2023 – 2032) Final Adopted RHNA Methodology Summary Table..........35 Table 8: Weighting of Total Housing Need Adjustment Factors for the Adopted Methodology (Step 2).......................................................................................................................36 Table 9: Weighting of Below-Moderate-Income Need Adjustment Factors for the Adopted Methodology (Step 3).......................................................................................................................36 2 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan This document summarizes the Merced
County Association of Governments’ (MCAG)
adopted Regional Housing Needs Allocation
(RHNA) Methodology and the process used
to arrive at that methodology. It includes
summaries of public input solicited to date,
adjustment factors considered by the MCAG
RHNA Steering Committee, and an analysis of
the methodology adopted to allocate housing
needs among MCAG’s member jurisdictions. It
contains a review of public comments received
regarding the adopted methodology and
responses to those comments. It concludes by
documenting the allocation of housing need,
including how it complies with State statute
and its review and approval by the California
Department of Housing and Community
Development (HCD).

0.1 Process
The Regional Housing Needs Allocation
(RHNA) is a state-mandated process that
ensures local governments have enough zoned
capacity to accommodate future housing need
for households at all income levels. MCAG’s
RHNA process can be broadly thought of in
four steps:

1. Regional Determination: The
California Department of Housing
and Community Development (HCD)
worked with California’s Department
of Finance (DoF) to calculate the
region’s housing need for the next
eight years. This is called the region’s
Determination of Need. MCAG received
its final Determination of Need for
Cycle 6 (June 30th, 2023 - January
31st 2032) in December 2021. MCAG’s
final Determination of Need is 22,620
housing units.

2. RHNA Framework and Proposed
Methodology Recommendation: After
receiving a Determination of Need
from HCD, MCAG initiated discussions
with the public and representatives
from local jurisdictions (i.e., city
and county governments). These
discussions sought to collaboratively
develop a proposed methodology for
allocating the region’s housing need
among all jurisdictions. The RHNA
Steering Committee, an advisory
group of public and jurisdictional
representatives assembled to provide
input on MCAG’s RHNA process, voted
to recommend a proposed methodology
option to MCAG’s Governing Board on
May 18th, 2022.

3. Public Comment and Release of a Draft
RHNA Methodology: Once a proposed
methodology was authorized by MCAG’s
Governing Board for circulation, the
public reviewed and commented on the
methodology. MCAG then reviewed and
responded to comments received and
released the methodology to HCD for
formal review. HCD issued its findings
Executive Summary
3 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan of this review on September 14th,
2022 and found that the draft RHNA
Methodology furthered all statutory
RHNA objectives.

4. Finalizing the Regional Housing
Needs Allocation and Plan: Once the
methodology was certified by HCD,
MCAG’s Governing Board adopted
the methodology on September 15th,
2022. Finally, the adopted methodology
and resulting allocation of regional
housing needs were documented in
the Regional Housing Needs Allocation
(RHNA) Plan which was released for
a 45-day jurisdictional appeals period
on September 16th, 2022. Following the
conclusion of the appeals period, during
which no appeals were received, the
MCAG Governing Board adopted the
Final RHNA Plan on November 17, 2022.

0.2 Implications for Local
Governments
The RHNA Methodology described in this
document assigns housing need for four
income categories relative to Merced County’s
area median income (AMI): very low (<50
percent of AMI), low (50-80 percent of AMI),
moderate (80-120 percent of AMI), and above
moderate (120+ percent of AMI), for which
MCAG’s jurisdictional partners must plan for.

Once the methodology is adopted, jurisdictions
have until February 2024 to adopt housing
elements that demonstrate how they will
accommodate their respective allocations
through zoned land within their city limits.

Figure 1. RHNA Process Diagram (May 18th, 2022 RHNA Steering Committee Meeting) 4 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Step 1 – Baseline Total Housing Need:

In step 1, total RHNA for all income levels was
allocated among MCAG’s 7 jurisdictions using
each jurisdiction’s share of forecasted 2015 -
2035 household growth from the 2018 RTP/
SCS preferred land use scenario1. Then, the
regional average split for moderate and above-
moderate income housing need (58.6 percent)
and low and very low-income housing need
(41.4 percent) was applied to each jurisdiction’s
total allocation.

1. Allocations from the 2022 RTP/SCS were not
yet available during the methodology development
process, thus 2018 allocations were used
instead.

In addition to demonstrating enough zoned
capacity to accommodate the total number
of allocated units, each jurisdiction must also
demonstrate adequate capacity zoned at 20
units per acre or more for units affordable to
households earning at or below 80 percent
AMI.

This requirement is based on the assumption
that affordable housing becomes easier
to build if it can be built at higher densities
(at least 20 units per acre). Jurisdictions
that do not have enough zoned capacity
to accommodate their total RHNA, and the
proportion that must be affordable to low and
very low-income households, must identify and
rezone sites by January 31st, 2024.

0.3 Adopted RHNA
Methodology
The Adopted RHNA Methodology
(“the Methodology”) was unanimously
recommended by the RHNA Steering
Committee on May 18th, 2022 and adopted
by MCAG’s Governing Board on September
15th, 2022. It is the product of six months
of collaboration by the RHNA Steering
Committee, a diverse group comprised
of housing advocates and jurisdictional
representatives. It was developed to further
five critical RHNA objectives, discussed in
section 2 of this document. The Methodology
is made up of three steps:

Figure 2: Step 1 of the RHNA Methodology:

Baseline Total Housing Need

5 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Figure 3: Step 2 of the RHNA Methodology:

Adjust Total Housing Need
Step 2 – Adjust Total Housing Need: In step
2, total housing need is adjusted based on
adjustment factors. Additional data was used
to adjust jurisdictions’ baseline shares of
the regional housing need up or down. Data
used to make adjustments are referred to
as adjustment factors. As described in the
following section, several adjustment factors
for total housing need were initially explored,
then narrowed down.

Step 3 – Allocate Housing Need by Income
Group: In step 3, the proportion of below-
moderate income housing need is adjusted.

Once total need is adjusted, it is broken into
four income categories so that all jurisdictions
receive the same percentage (i.e. the
countywide percentage) of housing need for
each income category. Additional adjustment
factors are then used as the basis for adjusting
each jurisdiction’s proportion of below-
moderate income housing need up or down.

Figure 4: Step 3 of the RHNA Methodology:

Allocate Housing Need by Income Group
6 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Table 1: Cycle 6 (2023 – 2032) Final Adopted RHNA Summary Table Jurisdiction
Lower Income Units Higher Income Units
Total
RHNA Very
Low Low
Very
Low +
Low
% of
Total
RHNA
(VL + L)
Moderate Above
Atwater 768 526 1,294 42.9% 508 1,215 3,017
Dos Palos 56 39 95 36.4% 49 117 261
Gustine 77 53 130 37.5% 64 152 346
Livingston 311 213 524 47.8% 169 404 1,097
Los Banos 719 493 1,212 38.7% 566 1,354 3,132
Merced 2,543 1,742 4,285 40.7% 1,838 4,394 10,517 Unincorporated
County 1,042 714 1,756 41.3% 736 1,758 4,250
Total 5,516 3,780 9,296 41.1% 3,930 9,394 22,620

0.4 Project Schedule
Figure 5: Simplified RHNA Project Schedule

7 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

0.5 Key Terms
RHNA Determination of Housing Need: HCD
issued an overall region-wide housing need
called the RHNA Determination. The RHNA
Determination is the total housing units the
region’s jurisdictions must plan for between
June 30th, 2023 and January 31st, 2032.

RHNA Methodology: MCAG prepared a
RHNA Methodology to allocate the region’s
RHNA to each of its seven jurisdictions. This
methodology must reflect certain objectives of
State law and be consistent with the RTP/SCS.

This methodology was adopted by the MCAG
Governing Board on September 15th, 2022.

RHNA Jurisdictional Allocations: Each
jurisdiction’s share of the RHNA and the
proportion that must be targeted at above and
below-moderate income households.

Regional Housing Needs Allocation (RHNA)
Plan: The RHNA Plan (this document)
describes the RHNA process and officially
assigns allocations to each jurisdiction.

Housing Elements: Each jurisdiction in the
Merced region must adopt a housing element
that accommodates their assigned RHNA
jurisdictional allocation. Housing elements
must be adopted by January 31st 2024.

RHNA Objective: Five state-mandated guiding
principles which the adopted methodology
must “further”.

RHNA Factor: 12 factors that must be
considered during the development of the
adopted methodology.

Methodology Adjustment Factor: data-driven
rationale for adjusting each jurisdiction’s share
of below-moderate RHNA above or below
the regional average. Must further a RHNA
objective.

0.6 Outline of this
Document
Section 1: Introduction to the Cycle 6 RHNA
The introduction provides an overview of the
Housing Element Law as it relates to RHNA
and summarizes the RHNA process.

Section 2: RHNA Objectives and Factors
Section 2 describes each RHNA Objective
and Factor and how each was “furthered” or
“considered” as part of the adopted RHNA
Methodology.

Section 3: Regional RHNA Determination
This section summarizes the Regional
Determination of Housing Need provided to
MCAG by HCD in December 2021.

Section 4: Adopted RHNA Methodology
This section provides a detailed description
of the adopted RHNA Methodology and
allocations of housing need for each
jurisdiction.

Section 5: Appendices
Included in the appendices are a variety of
supporting documents including a summary
of the RHNA Methodology options considered
during the methodology development process,
HCD’s findings with respect to the draft RHNA
Methodology, and comments received on the
draft RHNA Methodology.
8 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

1.1 What is RHNA?
California’s Regional Housing Needs Allocation
(RHNA) process assesses each region’s
total housing need for the next eight years
and directs local jurisdictions (i.e. cities and
counties) to collaborate on a plan to distribute
that need amongst themselves. Housing need
is allocated to jurisdictions at four income
levels: above moderate income (120 percent
Area Median Income [AMI] or higher), moderate
income (80-120 percent AMI), low income
(50-80 percent AMI), and very low income (less
than 50 percent AMI).

The purpose of the RHNA process is twofold:

1. To allocate a share of the region’s
housing need such that each jurisdiction
plays a role in meeting the overall need
and knows the clear, quantified amount
it must accommodate.

2. To guide where housing is built
throughout the region, moving away
from a development pattern reflective
of local zoning constraints and toward
a growth pattern reflective of regional
and state equity, environmental, and
socioeconomic objectives.

1.2 Implications for Local
Governments
The RHNA process has several implications
for local jurisdictions. As a result of the RHNA
process, each jurisdiction in the Merced Region
must update its Housing Element by February
2024 and demonstrate sufficient buildable
capacity within its zoning to accommodate its
assigned share of regional housing need for
the 8.6-year period spanning June 30th, 2023
through January 31st, 2032.

While the RHNA process affects zoning,
it does not directly mandate or fund the
construction of the assigned housing need. It
is the intent of Housing Element law that the
RHNA process prompt jurisdictions to prepare
for their full housing need via zoning, as well
as through adjacent actions such as SB35
permit streamlining for affordable housing or
analyzing construction feasibility during the
Housing Element stage.

Because the RHNA process assigns housing
need by income category, jurisdictions
must also design their Housing Elements
to accommodate various income groups.

RHNA requirements assume that housing
affordable to low-income and very-low-income
households is most financially feasible to build
at medium and high densities.

Thus, housing element law, specifically AB
1398, dictates that jurisdictions’ Housing
Elements must accommodate housing
need for low-income and very-low-income
households at zoned densities of 20 units
per acre or greater. Jurisdictions that lack
sufficient housing capacity to meet their share
of regional need must identify sites and rezone
them within the first three years of the RHNA
planning horizon.
1 Introduction to the Cycle 6 RHNA
9 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

1.3 The RHNA Process
The RHNA process began in January
2022 when MCAG staff briefed the RHNA
Steering Committee on the Cycle 6 RHNA
process. HCD provided a final RHNA
Determination on December 1st, 2021 of 22,620
housing units for the 8.6-year RHNA period
(see Appendix B for HCD letter to MCAG dated
December 1, 2021).

State law requires MCAG to develop and adopt
a methodology for allocating a portion of the
RHNA Determination to each jurisdiction within
the Merced Region. On May 18th, 2022, the
RHNA Steering Committee voted unanimously
to recommend a proposed RHNA methodology
(discussed in Section 4) to the MCAG
Governing Board.

MCAG staff and consultants documented
the preferred methodology and all other
methodology options and released a Proposed
RHNA Methodology Framework Memorandum
for a 35 day public comment period starting
June 21st, 2022, which concluded on July 26th,
2022 and included a public hearing during the
July 21st, 2022 meeting of MCAG’s Governing
Board.

Public comment was addressed and integrated
into the draft RHNA Methodology Framework
Memorandum which was formally reviewed
by HCD. On September 14th, 2022, HCD issued
its Review of the draft Regional Housing Need
Allocation (RHNA) Methodology (see Appendix
C) with a determination that the adopted RHNA
Methodology furthered all statutory objectives.

Following HCD review of the draft RHNA
Methodology, the MCAG Governing Board
adopted the RHNA Methodology on
September 15th, 2022. Based on the Adopted
RHNA Methodology, MCAG released the
draft allocations of housing need for each
jurisdiction as a part of the draft RHNA Plan
for a 45-day jurisdictional appeals period.

The appeals period gives each jurisdiction
an opportunity to provide comments on the
allocations described in the draft RHNA Plan.

The public review and comment period for the
MCAG draft RHNA Plan ran for 45 days from
September 16th, 2022 to October 31st, 2022.

State law asserts that if any jurisdiction
proposes a revision to the draft RHNA
Allocations, MCAG, “shall accept the proposed
revision, modify its earlier determination,
or indicate, based upon available data and
accepted planning methodology, why the
proposed revision is inconsistent with the
regional housing need.” Jurisdictions may
only propose revisions if certain conditions
are met. These conditions include failure
of MCAG to consider local RHNA planning
factors through a jurisdictional survey, failure
to distribute housing need in accordance with
the Draft RHNA Methodology, or significant
and unforseen changes to any jursdictions’
circumstances.

After the 45-day appeals period, no appeals
were filed, nor were any revisions requested by
any jurisdiction within the Merced region.

The MCAG Governing Board conducted a
public hearing and adopted the Final RHNA
Plan (this document) on November 17th, 2022.

Following the adoption of the Final RHNA Plan,
each jurisdiction must then update its Housing
Element to demonstrate that it is meeting State
law requirements.
10 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Jurisdictions within Merced County are
required to adopt and submit Housing
Elements to HCD for final review and
certification on or before January 31st, 2023.

1.4 SB 375: Legal
Requirements
The Sustainable Communities and Climate
Protection Act of 2008 (SB 375) was passed
to support the State’s climate action goals, as
identified in Assembly Bill 32 (AB 32), to reduce
greenhouse gas (GHG) emissions through
coordinated transportation and land use
planning. The bill mandates each of California’s
Metropolitan Planning Organizations (MPOs) to
prepare a Sustainable Communities Strategy
as a part of its Regional Transportation Plan.

The SCS contains land use, housing, and
transportation strategies that, if implemented,
would allow the region to meet its GHG
reduction targets.

In the past, the RHNA was undertaken
independently from the RTP . SB 375 requires
that the RHNA and RTP/SCS processes be
aligned to better integrate housing, land
use, and transportation planning. The law
recognizes the importance of planning for
housing and land use in creating sustainable
communities where residents of all income
levels have access to jobs, services, and
housing using transit, walking and bicycling.

In addition to the RHNA requirements of
housing element law (Government Code
Section 65584), SB 375 requires MCAG to
address the region’s housing needs in the SCS
of the RTP and will:
• Consider the State housing goals
(Government Code Section 65080 (b)(2)
(B)(vi));
• Identify areas within the region sufficient
to house all the population of the region,
including all economic segments of
the population, over the course of the
planning period for the RTP (out to
2046 for the 2022 RTP/SCS) taking
into account net migration into the
region, population growth, household
formation, and employment growth
(Government Code Section 65080 (b)
(2)(B)(ii); and
• Identify areas within the region sufficient
to house the regional housing needs for
the region (Government Code Section
65080 (b)(2)(B)(iii)).

1.4.1 RHNA – RTP/SCS Consistency
As part of the RHNA Methodology
development process, MCAG staff and
consultants closely coordinated work on
the 2022 RTP/SCS and the Cycle 6 RHNA.

Throughout the scenario development
process for the RTP/SCS, every opportunity
was taken to ensure consistency of the RTP/
SCS preferred land use allocation with the
RHNA process. This was accomplished by
working with the RTP team to share relevant
data, engaging in joint RTP/SCS and RHNA
meetings with jurisdiction representatives, and
developing RHNA-specific survey questions as
part of public outreach conducted for the RTP/
SCS process.
11 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

1.5 Regional Housing Need
The RHNA has two statutorily-required
components that must be addressed by MCAG
and its member jurisdictions:

1. In December 2021, MCAG received a
Determination of Housing Need from
HCD of 22,620 housing units for the 8.6-
year period beginning June 30th, 2023
through January 31st, 2032.

2. This determination is further segmented
into four income categories as follows:
• Very Low Income (less than 50 percent
of AMI)
• Low Income (50-80 percent of AMI)
• Moderate Income (80-120 percent of
AMI)
• Above-Moderate Income (above 120
percent of AMI)
RHNA Survey Question: MCAG staff and
consultants developed a RHNA-focused
survey question as part of an RTP/SCS survey
instrument, and the use of RTP/SCS data to
inform the baseline allocation of total housing
need to jurisdictions. Figure 6 shows how
responses to this question shed light on
participants’ desire for more diverse housing
types in areas with existing infrastructure.

Joint RTP/SCS and RHNA Meetings: Another
example of RHNA/RTP consistency included
in the scenario development process was
frequent communication between MCAG’s
RTP/SCS and RHNA consultant teams.

Members of the RHNA team participated in
two RTP/SCS workshops to gather input and
facilitate housing-focused discussions.

Figure 6: RHNA - RTP/SCS Survey Question
12 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

2.1 RHNA Objectives and
Factors
In developing its RHNA Methodology,
statute requires MCAG to “further” certain
objectives and “consider” certain factors.

There are 5 RHNA Objectives that the
RHNA Methodology must “further”. These
objectives are intended to provide a guiding
framework for the methodology development
process and the adopted methodology must
clearly demonstrate how each objective is
incorporated. There are 12 RHNA Factors
which must be considered and evaluated to
the extent that relevant data is available. The
extent to which these factors are directly
incorporated into the methodology is at
the discretion of MCAG staff. The RHNA
Objectives and Factors are discussed in
sections 2.2 and 2.3, respectively.

2.2 RHNA Objectives
(§65584.D)
State Statute requires that MCAG’s RHNA
Methodology “further” the following five
objectives. In practice, that means the RHNA
Methodology must advance these objectives
directly and ensure that each is clearly
reflected in how the methodology allocates
housing need. The following section provides
additional details about each RHNA Objective
and how each was “furthered” by the RHNA
Methodology.
2 RHNA Objectives and Factors

RHNA OBJECTIVES
(§65584.D)

RHNA FACTORS
§65584.04(e)
• Guiding framework for RHNA
methodology
• MCAG must demonstrate how
methodology “furthers” each of the
five objectives
• “Furthering” means proactive
inclusion of each objective
• 12 RHNA factors provide context for
the RHNA methodology
• Data gathered through surveys and
consultations with jurisdictions
• RHNA methodology must “consider”
each factor
Figure 7: Relationship Between RHNA Factors
and RHNA Objectives
13 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Objective 1: Increasing Housing Supply and
Mix of Types

State Definition: “Increasing the housing
supply and the mix of housing types, tenure,
and affordability in all cities and counties
within the region in an equitable manner, which
shall result in each jurisdiction receiving an
allocation of units for low- and very low-income
households.”
How the Adopted Methodology Furthers the
Objective: Per statutory direction, the RHNA
methodology ensures that each jurisdiction is
assigned housing need at a variety of income
levels so that no jurisdiction is exempt from
zoning for lower income housing need.

Before making any adjustments based on
available data, the methodology assigns each
jurisdiction higher density, below-moderate-
income housing need at an equivalent rate.

This alone, without adjustment factors, likely
pushes jurisdictions with predominantly single-
family housing to move toward housing mix
and income integration.

The outcomes of the methodology also further
this objective:
• Livingston and Los Banos—the
jurisdictions with the highest median
gross rent in the region—receive greater
shares of total housing need than
their current shares of the region’s
households. This responds to supply
constraints that help create high rents.

Conversely, Dos Palos—which has the
lowest median gross rent in the region—
receives less total RHNA than its share
of the region’s households.
• Livingston—the region’s only jurisdiction
with both a high prevalence of high
opportunity areas (per California Tax
Credit Allocation Committee (TCAC)
data) and less multifamily housing
than average—is allocated more
below-moderate-income housing
need, promoting both multifamily and
affordable housing in that jurisdiction.

Objective 2: Promoting Infill, Equity, and
Environment

State Definition: “Promoting infill development
and socioeconomic equity, the protection of
environmental and agricultural resources,
the encouragement of efficient development
patterns, and the achievement of the region’s
greenhouse gas reductions targets provided
by the State Air Resources Board pursuant to
Section 65080.”
How the Adopted Methodology Furthers
the Objective: The methodology directly
incorporates three adjustment factors that
directly address this objective: percent of land
within a jurisdiction’s Sphere of Influence (SOI)
that is high-quality agricultural land, percent of
a jurisdiction’s population within a quarter mile
of a transit stop, and a factor measuring the
balance of housing to jobs accessible within a
15-minute drive.

The agricultural land adjustment factor
increases the total RHNA assigned to
jurisdictions with limited high-quality farmland,
helping preserve farmland where it exists.

The transit access factor increases the
below-moderate-income RHNA assigned
to jurisdictions with good transit access,
promoting equitable access to a key
14 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan mobility service and low-emissions mode of
transportation. And the jobs-housing-balance
adjustment factor increases the total housing
need assigned to jurisdictions with limited
housing but lots of jobs within a 15-minute
drive, promoting housing where short
commutes are most possible, thereby reducing
vehicle miles traveled and related emissions.

The inclusion of these adjustment factors
contributes to the following outcomes that
further this objective:
• Jurisdictions with less transit
access—Dos Palos, Gustine, and the
Unincorporated area—receive downward
adjustments in their housing need,
resulting in lower allocations than those
jurisdictions’ shares of the region’s
households. Conversely, jurisdictions
with greater transit access—like Merced
and Atwater—receive increased housing
need allocations.
• Jurisdictions with lower average daily
VMT per household—Merced, Atwater,
and Livingston—all receive upward
adjustments to their total housing
need allocations, resulting in greater
percentage allocations than their current
share of the region’s households.

Objective 3: Ensuring Jobs-Housing Balance
and Fit
State Definition: “Promoting an improved
intraregional relationship between jobs and
housing, including an improved balance
between the number of low-wage jobs and the
number of housing units affordable to low-
wage workers in each jurisdiction.”
How the Adopted Methodology Furthers
the Objective: The methodology directly
incorporates an adjustment factor related to
jobs-housing balance. This factor identifies
jurisdictions with limited housing but many
jobs within a 15-minute drive, increasing the
total housing need allocated to jurisdictions
with such imbalances (and vice versa).

The inclusion of this adjustment factor
contributes to the following outcomes that
further this objective:
• Jurisdictions with limited affordable
rental housing but access to many low-
wage jobs within a 15-minute drive—
primarily Atwater and Livingston—are
allocated greater percentages of below-
moderate-income housing need than
those jurisdictions’ current shares of the
region’s households.
• Jurisdictions with limited housing
generally but access to many jobs
within a 15-minute drive—Atwater,
Livingston, and Merced—are allocated a
higher percentage of total housing need
than those jurisdiction’s current shares
of the region’s households. The opposite
holds true such that jurisdictions that
currently display a better balance of
housing and nearby jobs—such as
Gustine and Dos Palos—receive lower
allocations.

Objective 4: Promoting Regional Income
Parity

State Definition: “Allocating a lower proportion
of housing need to an income category when
a jurisdiction already has a disproportionately
15 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan high share of households in that income
category, as compared to the countywide
distribution of households in that category
from the most recent American Community
Survey.”
How the Adopted Methodology Furthers the
Objective: The methodology incorporates
an adjustment factor to address regional
income parity: percent of population below
the poverty level. This factor raises the below-
moderate-income housing need allocations of
jurisdictions with lower than average poverty
rates and vice versa.

By promoting housing for lower income
residents in areas with less poverty, this
factor aims to diversify the income mix
of jurisdictions, promote income parity
throughout the region, and counteract
tendencies for neighborhoods and jurisdictions
to form enclaves of wealth and poverty.

The inclusion of this adjustment factor
contributes to the following outcomes that
further this objective:
• Merced—the only area within the region
with higher-than-average poverty—
receives a downward adjustment to
its below-moderate income housing
need allocation relative to the baseline
allocation.
• Los Banos and Atwater, two higher
income jurisdictions, receive greater
total and below-moderate-income
housing need allocations, relative to
their current shares of such households.
• Atwater, Livingston, and the
Unincorporated area—which all exhibit
poverty rates below the regional average
and contain TCAC high opportunity
tracts—receive upward adjustments to
their below-moderate-income housing
need allocations relative to their
baseline allocations.

Objective 5: Affirmatively Furthering Fair
Housing
State Definition: “‘Affirmatively furthering fair
housing’ means taking meaningful actions,
in addition to combating discrimination, that
overcome patterns of segregation and foster
inclusive communities free from barriers
that restrict access to opportunity based on
protected characteristics.

Specifically, affirmatively furthering fair housing
means taking meaningful actions that, taken
together, address significant disparities in
housing needs and in access to opportunity,
replacing segregated living patterns
with truly integrated and balanced living
patterns, transforming racially and ethnically
concentrated areas of poverty into areas of
opportunity, and fostering and maintaining
compliance with civil rights and fair housing
laws.”
How the Adopted Methodology Furthers
the Objective: The methodology directly
incorporates an adjustment factor in pursuit of
affirmatively furthering fair housing: percent of
a jurisdiction’s housing units that are in TCAC
designated high opportunity areas. This factor
raises the below-moderate-income housing
need allocations of jurisdictions with higher
than average percentages of their housing
stock in high opportunity areas, signifying
the strong presence of high opportunity
neighborhoods.
16 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

2.3 RHNA Factors
(§65584.04(e))
In addition to “furthering” the above objectives,
the methodology must also “incorporate” the
RHNA Factors below. This means the RHNA
Factors must be explored and considered but
that they are not required to be represented
within the methodology or furthered
quantitatively via its outcomes.

To successfully incorporate the RHNA factors,
relevant secondary data was reviewed, and
each jurisdiction was directly surveyed about
the factors, per §65584.04.(b)(1). Consultation
meetings were also held with representatives
of each jurisdiction in which information was
solicited regarding the RHNA Factors.

The following section covers each of the RHNA
Factors and how they were considered during
the RHNA Methodology development process.

Factor 1: Existing and Projected Jobs and
Housing Relationship
State Definition: “Each member jurisdiction’s
existing and projected jobs and housing
relationship. This shall include an estimate
based on readily available data on the number
of low-wage jobs within the jurisdiction and
how many housing units within the jurisdiction
are affordable to low-wage workers as well as
an estimate based on readily available data, of
projected job growth and projected household
growth by income level within each member
jurisdiction during the planning period.” -
§65584.04(e)
MCAG Consideration: Existing jobs-housing
balance and fit (ratio of low wage jobs to low
By promoting housing for lower-income
residents in jurisdictions with more high
opportunity neighborhoods, this factor aims to
increase access among low-income residents
in areas where they and their families are most
likely to succeed.

By using TCAC data, this factor also helps
ensure that areas preferred for affordable
housing funding have sufficient land zoned for
higher densities to support new construction of
affordable housing.

The inclusion of this adjustment factor
contributes to the following outcomes that
further this objective:
• Livingston and Atwater—jurisdictions
with an above average prevalence of
high opportunity neighborhoods—
receive upward adjustments to their
total and below-moderate-income
housing need, resulting in allocations
greater than those jurisdictions’ current
share of the region’s households. Other
jurisdictions with high opportunity
neighborhoods, such as Merced, also
receive upward adjustments to their
total housing need.
• Gustine and Dos Palos—the two
jurisdictions without high opportunity
neighborhoods—receive downward
adjustments to their total and below-
moderate-income housing need,
resulting in lower percentage allocations
than those jurisdictions’ current shares
of the region’s households.
17 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan income households) was reviewed for all
jurisdictions. In addition, MCAG learned the
following through local agency consultations:

Jobs-housing balance in Merced County is
related to proximity to regional job centers.

In Cities along the SR-99 corridor such as
Atwater, Livingston, and Merced, jurisdictional
staff said there are generally more jobs than
affordable homes. Regardless of the balance of
employment and housing in their jurisdictions,
almost all cities in the county said that high
rates of housing cost burden for residents
impacts the imbalance of low-wage workers to
homes affordable to low-wage workers.

Factor 2: Opportunities and Constraints to
Development of Additional Housing
2a: Capacity for Water and Sewer Service
State Definition: “Lack of capacity for sewer
or water service due to federal or state laws,
regulations or regulatory actions, or supply
and distribution decisions made by a sewer
or water service provider other than the local
jurisdiction that preclude the jurisdiction
from providing necessary infrastructure for
additional development during the planning
period.” - §65584.04(e)
MCAG Consideration: Many jurisdictions cited
infrastructure capacity, particularly sewer
and water, as one of their chief concerns
heading into this RHNA Cycle. This issue is
complicated by two facts: first, that sewer
and water districts do not align perfectly with
jurisdictional boundaries; second, that water
use is significantly regulated by the state via
the Sustainable Groundwater Management
Act (SGMA) and subject to regional decision
making by coalitions of jurisdictions tasked
with water basin stewardship, called
Groundwater Sustainability Agencies (GSAs).

To inform MCAG’s understanding of these
issues, data from the California SGMA
dashboard was consulted.

2b: Availability of Land Suitable for Urban
Development
State Definition: “The availability of land
suitable for urban development or for
conversion to residential use, the availability
of underutilized land, and opportunities for
infill development and increased residential
densities. The council of governments may
not limit its consideration of suitable housing
sites or land suitable for urban development
to existing zoning ordinances and land use
restrictions of a locality, but shall consider the
potential for increased residential development
under alternative zoning ordinances and land
use restrictions.

The determination of available land suitable
for urban development may exclude lands
where the Federal Emergency Management
Agency (FEMA) or the Department of Water
Resources (DWR) has determined that the
flood management infrastructure designed to
protect that land is not adequate to avoid the
risk of flooding.” - §65584.04(e)
MCAG Consideration: MCAG considered a
range of data that could indicate environmental
constraints or hazards that could preclude
urban development. These included FEMA
flood maps as well as wetland, water, steep
slope and environmental hazard data from the
DWR.
18 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan 2c: Lands Preserved or Protected from Urban
Development
State Definition: “Lands preserved or protected
from urban development under existing
federal or state programs, or both, designed to
protect open space, farmland, environmental
habitats, and natural resources on a long-term
basis, including land zoned or designated for
agricultural protection or preservation that
is subject to a local ballot measure that was
approved by the voters of that jurisdiction
that prohibits or restricts conversion to non-
agricultural uses.” - §65584.04(e)
MCAG Consideration: MCAG considered a
range of data to establish areas that may be
precluded from development due to existing
preservation agreements. These included the
Farmland Monitoring and Mapping Program
(FMMP) and California Conservation Easement
Database (CCED).
2d: County Policies to Preserve Prime
Agricultural Land
State Definition: “County policies to preserve
prime agricultural land, as defined pursuant
to Section 56064, within an unincorporated
and land within an unincorporated area zoned
or designated for agricultural protection or
preservation that is subject to a local ballot
measure that was approved by the voters
of that jurisdiction that prohibits or restricts
its conversion to non-agricultural uses.” -
§65584.04(e)
MCAG Consideration: Jurisdictional boundary
changes consider the location of prime
agricultural land. Merced County’s Local
Agency Formation Commission’s (LAFCO)
Agricultural Preservation Policy also uses “set
aside” programs to protect some farmland
when other agricultural areas are developed.

According to one respondent, the County has a
1-to-1 farmland set aside policy administered
by LAFCO. These set asides constrain farmland
conversion to housing.

Factor 3: Opportunities to Maximize the
Use of Public Transportation and Existing
Transportation Infrastructure
State Definition: “The distribution of household
growth assumed for purposes of a comparable
period of regional transportation plans and
opportunities to maximize the use of public
transportation and existing transportation
infrastructure.” - §65584.04(e)
MCAG Consideration: Transit service in
Merced County is limited. Generally, most local
agencies viewed existing bus transit service as
either too sparse or infrequent to be a major
driver for the location of new development.

The Transit Joint Powers Authority for Merced
County (T JPAMC) runs fixed routes between
the City of Merced, the City of Atwater, and
the unincorporated community of Winton. The
City of Merced has more transit than other
jurisdictions, with some services running every
30 minutes during daytime hours.

Commuter routes serve the City of Livingston,
the City of Los Banos, the unincorporated
communities of Delhi, Planada, and Le
Grand, and the City of Turlock in neighboring
Stanislaus County. Paratransit and micro
buses also serve the City of Gustine, the City
of Dos Palos, and the City of Los Banos. While
the availability of some bus service on select
19 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan corridors presents opportunities for transit
oriented development, broadly a lack of transit
service, particularly in rural areas, acts as a
constraint.

Factor 4: County-City Agreements to Promote
Growth in Incorporated Areas and Prevent
Conversion of Agricultural Land
State Definition: “Agreements between a
county and cities in a county to direct growth
toward incorporated areas of the county and
land within an unincorporated area zoned
or designated for agricultural protection or
preservation that is subject to a local ballot
measure that was approved by the voters
of the jurisdiction that prohibits or restricts
conversion to non-agricultural uses.” -
§65584.04(e)
MCAG Consideration: Although some cites—
such as Dos Palos and Gustine—said there
are few infill opportunities within city limits,
others are taking steps to encourage infill
development. The City of Livingston expressed
excitement and momentum behind ADU
construction.

The City of Los Banos wants to preserve
farmland on the outskirts of the city limits
and instead direct any expansion to infill
development and other areas of their SOI
without prime farmland. To aid in this effort,
they created a streamlined development
approval process at the City for infill
developments.

The City of Merced has also taken steps to
encourage infill development. For example,
the city offers facility fee reduction programs
for small and infill housing, CEQA exemptions
for qualifying projects, and have created a
library of “off the shelf” ADU, duplex, and triplex
buildings with development pre-approval.

Factor 5: Losses of Units in Income-Assisted
(I.E. Subsidized) Housing Developments
State Definition: “The loss of units contained
in assisted housing developments, as defined
in paragraph (9) of subdivision (a) of Section
65583, that changed to non-low-income
use through mortgage prepayment, subsidy
contract expirations, or termination of use
restrictions.” - §65584.04(e)
MCAG Consideration: Of all jurisdictions within
Merced County, only the County indicated in
its survey response that it has experienced a
loss of assisted housing developments within
the past 10 years. Most jurisdictions are not
anticipating losses (e.g. Merced, Los Banos),
but instead are interested in expanding the
amount of affordable housing they can provide.

Factor 6: Housing Cost Burden Rates
State Definition: “The percentage of existing
households at each of the income levels listed
in subdivision (e) of Section 65584 that are
paying more than 30 percent and more than 50
percent of their income in rent.”
MCAG Consideration: HCD provided MCAG
with housing cost burden rates for the Merced
County region. HCD found that Merced County
had higher rates of cost burden than its peer
regions and the nation as a whole, an indication
of the broader housing crisis affecting all of
California.
20 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Factor 7: Overcrowding Rates
State Definition: “The rate of overcrowding.” -
§65584.04(e)
MCAG Consideration: As with rates of
housing cost burden, HCD provided rates of
overcrowding in the Merced region. For MCAG,
the region’s overcrowding rate (8.75 percent) is
higher than the national average (3.35 percent).

Factor 8: Housing Needs of Farmworkers
State Definition: “The housing needs of
farmworkers.” - §65584.04(e)
MCAG Consideration: Like many Central Valley
counties, Merced County contains significant
prime agricultural lands and agricultural lands
of statewide or local significance. In fact, 57
percent of jurisdictions say there is a need for
farmworker housing over the course of a typical
year.

In jurisdictions where planners perceive an
unmet need for farmworker housing, the most
common reasons cited are a lack of funding
sources and low development capacity for local
affordable housing. United States Department
of Agriculture Rural Multifamily Housing
Rental properties exist in all unincorporated
jurisdictions except Atwater, plus the
unincorporated communities of Delhi, Le Grand,
and Planada.

Factor 9: Housing Needs of College Students
State Definition: “The housing needs generated
by the presence of a private university or a
campus of the California State University or
the University of California within any member
jurisdiction.” - §65584.04(e)
MCAG Consideration: UC Merced is the largest
university in the County and has been a major
growth area in recent years. It is the newest
UC campus, established in 2005, and now
enrolls over 8,000 students. This has created
significant student housing need centered in
the City of Merced, reflected in a much more
active housing pipeline than other jurisdictions
in the region (roughly 2,500 units built since
2017 and 4,000 additional units in its pipeline).

In response, under AB-3312 passed by the
state legislature, the City of Merced has gained
permission to annex over the next 12 months
a portion of the UC Merced campus, which
is currently within jurisdiction of the County,
and areas between the campus and City
within the next two years. The plan is to locate
growth between the existing City limits and
the university campus, focusing on housing
and amenities for students. This is turn should
reduce demand pressure in other areas of
the City currently brought on by the need for
student housing. The County stated it will
entitle that area for the City prior to annexation,
describing the potential for over 3,000 housing
units.

Merced County is also home to two campuses
of Merced Community College, but they do not
generate substantial additional housing needs.

One campus is in the City of Merced and
the other is located in the City of Los Banos.

Students enrolled at these campuses typically
live in Merced County and are obtaining credits
to transfer to larger colleges. However, the
Los Banos campus aspires to offer more
vocational training that focuses on healthcare
and industry and would attract people to live
in Los Banos to complete education needs for
higher wage jobs.
21 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Factor 10: Housing Needs of Individuals and
Families Experiencing Homelessness
State Definition: “The housing needs of
individuals and families experiencing
homelessness.” - §65584.04(e)
MCAG Consideration: The Merced City and
County Continuum of Care conducts a yearly
point-in-time count for houseless populations
living within the entire County. Overall, as of
the 2021 point in time count, there are an
estimated 835 houseless individuals living
within the county, with over half of that
population in the City of Merced itself. This
is up nearly 200 individuals from the 2020
count. Smaller jurisdictions carry a smaller
burden, but gaps appear between the data and
perception. For instance, the City of Dos Palos
estimated fewer than five houseless individuals
living in their jurisdiction. Yet, the 2021 point
in time count tallied 26 houseless individuals.

This may speak to the lack of visibility for
sheltered yet still houseless individuals.

Factor 11: Loss of Housing Units Due to
Governor-Declared Emergencies
State Definition: “The loss of units during a
state of emergency that was declared by the
Governor pursuant to the California Emergency
Services Act (Chapter 7 (commencing with
Section 8550) of Division 1 of Title 2), during
the planning period immediately preceding the
relevant revision pursuant to Section 65588
that have yet to be rebuilt or replaced at the
time of the analysis.” - §65584.04(e)
MCAG Consideration: No jurisdictions
indicated a loss of housing due to state-
declared emergencies.

Factor 12: Greenhouse Gas Emissions Targets
from the State Air Resources Board
State Definition: “The region’s greenhouse gas
emissions targets provided by the State Air
Resources Board pursuant to Section 65080.” -
§65584.04(e)
MCAG Consideration: Jurisdictions in the
region are using a variety of approaches to
reduce greenhouse gas emissions while
supporting housing growth.

Throughout the county, jurisdictions described
efforts and support for:
• Preserving farmland (e.g. Gustine,
Dos Palos, Livingston, Atwater), such
as a 1-to-1 set aside for farmland
development, administered by LAFCO.
• Promoting infill rather than continued
urban sprawl (e.g. Merced County,
Merced, Los Banos, Livingston)
• Encouraging mixed use development
(near unanimous support)
These represent potential consensus areas the
RHNA could leverage to attempt to allocate
housing need to lower the length of vehicle
trips and reduce greenhouse gas emissions.

Two cities in particular, Merced and Livingston,
have unique opportunities for infill, mixed use,
transit oriented development through their ACE
Rail expansion stations. Livingston shared a
well-defined vision in the form of a Specific
Plan to develop a dense, mixed-use, and
transit-oriented center around its station.

Beyond those broad themes and transit
oriented development opportunities,
jurisdictions cited a few other approaches.
22 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Above: Zoning for more multifamily development in areas with relatively little multifamily housing is an important component of MCAG’s Adopted RHNA Methodology.

Four of seven jurisdictions indicated they have used energy efficiency standards for new construction to support reduced emissions. Likewise a few jurisdictions indicated they had adopted non-automobile transportation plans: Los Banos with its Bike and Pedestrian Master Plan, and Merced with its citywide Bike Plan.

2.4 Prohibited Considerations §65584.04.(g)
State statute indicates that certain criteria cannot be used to justify a reduction in a jurisdiction’s share of the regional housing need. Those criteria include:

1. “Any ordinance, policy, voter-approved measure, or standard of a city or county that directly or indirectly limits the number of residential building permits issued by a city or county.”

2. “Prior underproduction of housing in a city or county from the previous regional housing need allocation.”

3. “Stable population numbers in a city or county from the previous regional housing needs cycle.”
23 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

3.1 Total and Income-Based Determination of Need
As discussed in section 2, MCAG received a regional housing need determination of 22,620. This includes sub-allocations by the four income categories discussed previously. HCD first provided a draft RHNA Determination to MCAG the Summer of 2021. Staff worked with HCD over the next several months to refine the determination for the region which was finalized in on December 1st, 2021. The figure below shows the determination in its final form as it was received from HCD. 3 Determination of Need
Figure 8: Determination of Need, Source: HCD
HCD Regional Housing Need Determination
MCAG: June 30, 2023 through January 31, 2032
24 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

3.2 Components of Determination of Need
MCAG’s determination is based on five factors: projected population growth, rates of vacancy, rates of overcrowding, replacement, and housing cost burden. HCD’s determination begins with population growth to establish the number of households that will need to be housed over the 8.6- year RHNA period. They then layer upon this, a series of adjustments that account for the other factors (vacancy rates, overcrowding, etc.). The dwelling unit need associated with each of these factors is summarized in the figure below and each factor is described in greater detail in the following subsections.

Figure 9: Components of Determination of Housing Need, Source: HCD

3.2.1 Forecasted Population Growth
The California Department of Finance (DoF) prepares demographic forecasts for reach region in the state. HCD’s determination of need for the Merced region starts with household forecasts developed by the DoF for the 8.6 year period covering MCAG’s RHNA cycle.

It should be noted that per California State statute 65884.01.a, the demographic forecast developed for the RTP/SCS may be used instead of the DoF forecast if certain conditions are met. Due to timing issues, the updated RTP/SCS forecast was not available when the HCD determination of need was finalized, thus the DoF forecast was used by default. 25 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

3.2.2 Vacancy Rate Adjustment
HCD assumes “healthy” housing markets to
exhibit vacancy rates of at least five percent.

Using HCD’s preferred method for calculating
vacancy rates from the Census Bureau’s 5-year
American Community Survey (ACS) occupancy
data, Merced County’s 2019 vacancy rate
was observed to be 2.13 percent. As Merced
County’s vacancy rate is well below what HCD
would consider “healthy”, an adjustment of 2.87
percent was made to MCAG’s determination of
need, resulting in an additional 2,888 needed
dwelling units.

3.2.3 Overcrowding Adjustment
HCD applies adjustments to regions that
exceed the national overcrowding rate of

3.35 percent. Rates of overcrowding in the
Merced region are estimated by the 5-year
ACS to be 8.75 percent, more than double
the national average. As such, HCD applied
an overcrowding adjustment of 5.4 percent ,
resulting in an additional 5,423 needed dwelling
units.

3.2.4 Replacement Adjustment
HCD applies a replacement adjustment of
between .5 percent and five percent to account
for housing obsolescence. This is based on
the current 10-year average of demolitions
tracked by the region in annual reports to the
DoF. For MCAG, this average is .4 percent;
thus the minimum of .5 percent was applied,
resulting in an additional 502 needed dwelling
units.

3.2.5 Cost Burden Adjustment
HCD applies an adjustment to the projected
need by comparing the difference in cost-
burden by income group for the region to
the cost-burden by income group for the
nation. The cost burden rate for lower income
households in the Merced region is 6.09
percent higher than national average, resulting
in 534 needed dwelling units for low-income
households. Similarly, the cost burden rate
for moderate and above-moderate income
households is 1.67 percent higher than the
national average, resulting in a 219 unit
increase in moderate and above-moderate
housing need.

Above: There are many barriers that must be overcome when building housing. The RHNA process tries to ensure that local development regulations are not one of those barriers. 26 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

4.1 Stakeholder Input
The adopted RHNA Methodology detailed in
this document incorporates input from local
jurisdictions and members of the public. The
main method of receiving input was through
the RHNA Steering Committee, which was
formed to guide the development of the
RHNA methodology. Members include a
representative from each of MCAG’s seven
local member agencies as well as several
at-large representatives of various regional
interests including Merced County Continuum
of Care, California Rural Legal Assistance
(CRLA), the Leadership Counsel for Justice and
Accountability (withdrew partway through the
process due to lack of capacity), DR Horton,
the Merced Bicycle Coalition, and the Central
Valley Coalition for Affordable Housing.

The following actions were taken to gather
input from the region’s stakeholders:
• A planning factors survey was
administered for jurisdictions to provide
information on the RHNA statutory
objectives and factors, including
affirmatively furthering fair housing
(January 2022 – February 2022)
• 12 consultation meetings were held
between MCAG and representatives
from each of its member jurisdictions
as well as at-large RHNA Steering
Committee members to discuss the
survey and RHNA factors (February
2022 – March 2022)
• Five meetings with the RHNA Steering
Committee in which the RHNA process
and methodological options were
discussed and ultimately voted on
(January 2022 – May 2022). These
RHNA Steering Committee meetings
were open to the public for comment
and questions.
• Two drop-in “office hours” where RHNA
Steering Committee representatives
could ask questions and discuss RHNA
methodology approaches.
• Attendance at one RTP/SCS workshop
to discuss integration between the
RHNA and the RTP/SCS and gather
input on potential adjustment factors
• An Excel spreadsheet tool was
distributed among Steering Committee
members to explore methodology
options for allocating housing need
throughout the region.
• A public hearing was held on July
21st, 2022 to gather comments on
the Proposed RHNA Methodology
Framework Memorandum.
• Public hearings were held on September
15th and November 17th, 2022 to
formally adopt the RHNA Methodology
and the RHNA Plan.
• A 45-day public comment period was
initiated on September 16th, 2022 to
provide jurisdictions time to appeal their
allocations.
4 Adopted RHNA Methodology
27 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

4.2 Methodology Overview
MCAG’s RHNA Methodology framework is
separated into three steps:

Step 1. Baseline total housing need is
allocated to each jurisdiction.

First, each jurisdiction is allocated a baseline
share of the region’s housing need equivalent
to the jurisdiction’s percentage share of
regional household growth from 2015 to 2035,
as allocated in the preferred land use scenario
from the 2018 RTP/SCS.

Step 2. Total housing need is adjusted based
on adjustment factors.

Next, additional data was used to adjust
jurisdictions’ baseline shares of the regional
housing need up or down. Data used to make
adjustments are referred to as adjustment
factors. As described in the following section,
several adjustment factors for total housing
need were initially explored, then narrowed
down.

Step 3: The proportion of below-moderate
income housing need is adjusted.

Once total need is adjusted, it is broken into
four income categories so that all jurisdictions
receive the same percentage (i.e. the
countywide percentage) of housing need for
each income category. Additional adjustment
factors are then used as the basis for adjusting
each jurisdiction’s proportion of below-
moderate income housing need up or down.

Ultimately, the selected adjustment factors in
steps 2 and 3 were required to further the five
RHNA objectives.

Figure 10: Overview of RHNA Methodology Steps
28 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

4.3 Adjustment Factors
Adjustment factors are a critical element of the RHNA Methodology Framework because they are how a methodology “furthers” each of the five RHNA Objectives mentioned previously. The RHNA Steering Committee considered a variety of adjustment factors related to the five objectives based on a series of agreed-upon “guiding principles”. In total, 12 adjustment factors were considered by the RHNA Steering Committee. These adjustment factors, their data source, and the RHNA objective they are intended to further, are summarized in the table below.

Adjustment Factor Options Source RHNA Objective
% Prime Ag Lands & Natural Areas CA Farmland Mapping and Monitoring Project
Infill, Equity, and
Environment
Housing Allocation in “Integrated
Planning” RTP Scenario
CA Dept of Conservation / The
Nature Conservancy
Infill, Equity, and
Environment
% of Population Within ¼ Mile of a Bus
Stop MCAG Bus Service Data Infill, Equity, and
Environment
% of Existing Housing Comprised of
Multifamily Homes
US Census American
Community Survey
Housing Supply and
Mix
Single Family Home Price % Increases Zillow Home Value Index Housing Supply and Mix
Percent of Existing Dwelling Units in
“High” or “Highest” Opportunity Areas
TCAC Opportunity Area Maps
(2022)
Affirmatively Further
Fair Housing
Ratio of Nearby Jobs to Housing US Census Longitudinal
Employer Household Dynamics
Jobs Housing
Balance
Ratio of Nearby Low-Wage Jobs to
Affordable Housing
US Census Longitudinal
Employer Household Dynamics
Jobs-Housing
Balance
Daily VMT per Household Bureau of Transportation
Statistics (LATCH Estimates)
Infill, Equity, and
Environment
Average Walk Distance to Retail UrbanFootprint Walk Access Module
Infill, Equity, and
Environment
Median Household Income US Census American
Community Survey
Regional Income
Parity
% Below Poverty Limit Households US Census American
Community Survey
Regional Income
Parity
Table 2: Considered RHNA Adjustment Factors
29 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Through five meetings and two drop-in office
hours, the RHNA Steering Committee refined
the above list of 12 factors to seven preferred
adjustment factors that furthered all five
statutory RHNA objectives. The following table
summarizes the seven preferred adjustment
factors, the RHNA objective they further, and
the methodology step in which each was
applied. How each of these adjustment factors
were calculated is discussed in Appendix D.

These preferred adjustment factors were
combined to create two total RHNA packages
and three below-moderate-income RHNA
packages for a total of six methodology
options. These were then combined with
the baseline allocation in Step 1 to create six
potential allocations.

4.4 Step 1: Baseline Total
RHNA Calculation
Description: Baseline total housing need
provides a starting point for allocating the
region’s Determination of Need of 22,620
units. Each jurisdiction is allocated its share
of 8.6-year RHNA based on the percentage of
household growth they were allocated in the
preferred scenario from the 2018 RTP/SCS.

Rationale: The rationale for using this method
to allocate total RHNA was to reflect growth
patterns that are consistent with regional
transportation investments and reduce VMT.

The allocation seeks to further the Housing
Supply and Mix objective and the Infill, Equity,
and Environment objective.

Adjustment Factor Options RHNA Objective RHNA Step
% Prime Ag Lands & Natural Areas Infill, Equity, and Environment Total RHNA (Step 2) Housing Allocation in “Integrated
Planning” RTP Scenario Infill, Equity, and Environment Total RHNA (Step 2) Ratio of Nearby Jobs to Housing Jobs Housing Balance Total RHNA (Step 2) % of Population Within ¼ Mile of a Bus
Stop Infill, Equity, and Environment Below-Moderate-
Income RHNA (Step 3)
% of Existing Housing Comprised of
Multifamily Homes Housing Supply and Mix Below-Moderate- Income RHNA (Step 3)
Percent of Existing Dwelling Units in
“High” or “Highest” Opportunity Areas
Affirmatively Further Fair
Housing
Below-Moderate-
Income RHNA (Step 3)
% Below Poverty Limit Households Regional Income Parity Below-Moderate- Income RHNA (Step 3)
Table 3: Selected RHNA Adjustment Factors
30 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

4.5 Step 2: Total Housing Need Adjustments
In Step 2, three adjustment factor packages were developed to adjust baseline total housing need from Step 1. Each package included two adjustment factors targeted at furthering two RHNA objectives: “#1: Infill, Equity and Environment” and “#3: Jobs Housing Balance”. The packages combined adjustment factors including jobs-housing balance, jobs-housing fit, prime agricultural land, and share of housing allocated to each jurisdiction in the “Integrated Planning Scenario” developed as part of the Resilient Merced project during the 2018 RTP/SCS cycle.

To create the adjustment packages, the unweighted variance from the base allocation for each factor was averaged and then applied to the base allocation. The result of these adjustments for each package are summarized in the table 5 on the following page. Technical documentation on how adjustment factor data affects baseline allocations is included in Appendix C. They are summarized in the figure below.

Jurisdiction
2018 RTP/SCS Household Allocation
Preferred Scenario (2015 - 2035)
Baseline Total RHNA
AllocationNet New
Households
(2015 - 2035)
Share of Net New
Households
(2015 - 2035)
Atwater 3,509 12.2% 2,759
Dos Palos 406 1.4% 319
Gustine 714 2.5% 561
Livingston 1,297 4.5% 1,020
Los Banos 4,695 16.3% 3,692
Merced 11,394 39.6% 8,960
Unincorporated County 6,750 23.5% 5,308
Total 28,765 100.0% 22,620
Table 4: Baseline Total RHNA Calculations (Step 1)
Figure 11: Step 1 Adjustment Factor Packages

31 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

4.6 Step 3: Below-Moderate-
Income Adjustment
Options
In Step 3, the share of below-moderate-income
housing need was varied from the region-wide
average based on the application of the four
“step 3” adjustment factors identified in table

3. The direction and magnitude of impact of
each of these adjustment factors for each
jurisdiction are summarized in the table 6 on
the following page.

These adjustment factors were combined in
various ways to create three below-moderate-
income adjustment option packages. All three
of these packages included the percent of each
jurisdictions’ population below the poverty line
and the percent of existing dwelling units areas
of “high” or “highest” opportunity as defined
by the 2022 Tax Credit Allocation Committee
(TCAC) Opportunity Area Maps.

Two of the three below-moderate-income
packages were further adjusted using the
percentage of housing in each jurisdiction
that is multifamily housing, and the share of
existing households with fixed route transit
access, respectively. The other package did
not include an additional adjustment factor.

Starting with the baseline distribution of total
housing need (Step 1), the two total housing
need packages (Step 2) and the three below-
moderate-income housing need packages
(Step 3) were then combined to create six
methodology options.

These methodology options are summarized in
the figure 12 on the following page. As stated
previously, technical documentation on how
adjustment factor data affects allocations is in
Appendix C.

Jurisdiction
Allocation
Based
on 2018

RTP/SCS
Household
Allocation
Package 1: Prime
Agriculture + Jobs-Housing
Balance
Package 2: Integrated
Planning Scenario + Jobs-
Housing Balance
Adjusted
Allocation
Percent
Difference
from
Baseline
Adjusted
Allocation
Percent
Difference
from
Baseline
Atwater 2,759 3,017 9% 2,553 -7%
Dos Palos 319 261 -18% 252 -21%
Gustine 561 346 -38% 437 -22%
Livingston 1,020 1,097 8% 1,067 5%
Los Banos 3,692 3,132 -15% 3,129 -15%
Merced 8,960 10,517 17% 10,908 22%
Unincorporated County 5,308 4,250 -20% 4,274 -19%
Total 22,620 22,620 - 22,620 -
Table 5: Total Housing Need Adjustment Options (Step 2) 32 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Jurisdiction
Access to
Opportunity
Percent in
Poverty
Level of
Transit
Service
Existing
Multifamily
Housing
% of Housing
Units in High/
Highest
Opportunity
Areas
% of
Population
Below the
Poverty Limit
% of
Population
Within 1/4
Mile of a Bus
Stop
% of Existing
Housing
Comprised of
Multifamily
Homes
Atwater 40% 21% 19% 21%
Dos Palos 0% 15% 0% 6%
Gustine 0% 13% 0% 11%
Livingston 81% 16% 12% 11%
Los Banos 20% 18% 7% 9%
Merced 43% 29% 29% 29%
Unincorporated
County 43% 17% 6% 5%
Table 6 Below-Moderate-Income Adjustment Factors and Their Impacts (Step 3) ADJUST: MORE

LOWER-INCOME

HOUSING NEED
ADJUST: LESS

LOWER-INCOME

HOUSING NEED
SMALL +/-

ADJUSTMENT
Figure 12: RHNA Methodology Options
33 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

4.7 The Adopted RHNA
Methodology
On May 18th, 2022 the RHNA Steering
Committee voted to recommend RHNA
Methodology Option 1C as the Proposed
RHNA Methodology for the Merced Region. In
unanimously recommending Option 1C, the
Steering Committee highlighted three primary
themes:

1. Recognize the Service Needs of Lowest-
Income Residents: Methodology options A
& B significantly reduce below-moderate-
income housing allocated to Merced. For
high-service-need individuals, housing in
Merced near services and transit is of prime
importance.

2. RTP Alignment Is Key: Alignment
with other regional planning efforts is
important. Similar themes appear in RTP
Scenario 3 and the RHNA methodology
options: promote infill, protect farmland,
reduce VMT, promote transit access

3. Manage Water Infrastructure Issues:

Methodology option 1C features
reductions or stable housing allocations
to areas with most severe infrastructure
issues and least control (primarily
Unincorporated area and Dos Palos, then
Livingston, Los Banos, and Atwater).

RHNA Methodology Option 1C also furthers
all five statutory RHNA objectives. The figure
below summarizes how each objective is
furthered by the adopted methodology.

Figure 13: How the Adopted Methodology Furthers the RHNA Objectives 34 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan RTP/SCS Alignment: Section §65584.04.
(m)(1) of housing element law instructs that
“the allocation plan shall allocate housing
units within the region consistent with
the development pattern included in the
sustainable communities strategy.” The draft
methodology aligns with the Merced region’s
RTP/SCS in two core ways.

First, the draft methodology uses the
household growth allocation for through the
Year 2035 from the 2018 RTP/SCS—the most
recent RTP/SCS available as of the start of
the 6th Cycle RHNA process—as its baseline
housing need allocation—the point from which
adjustments are made. This immediately
brings the RHNA into alignment with the
most recent RTP/SCS’s modeled housing
development pattern.

Second, the draft methodology employs
adjustment factors that align with the themes
and outcomes supported by the 2022
preferred RTP/SCS Scenario (which was
selected midway through the 6th Cycle RHNA
planning process). The 2022 preferred RTP/
SCS scenario promotes infill and farmland
preservation, increased access to transit, and
a shift in housing-mix emphasis from single-
family toward multifamily housing.

Water Supply and Management Issues:

Many jurisdictions cited infrastructure
capacity, as one of their chief concerns
heading into this RHNA Cycle. This issue is
complicated by two facts: first, that sewer
and water districts do not align perfectly with
jurisdictional boundaries; second, that water
use is significantly regulated by the state via
the Sustainable Groundwater Management
Act (SGMA) and subject to regional decision
making by coalitions of jurisdictions tasked
with water basin stewardship, called
Groundwater Sustainability Agencies (GSAs).

The issue, as it relates to housing, is threefold:

1. Supply - Jurisdictions are limited in their
groundwater draws by the plans GSAs
make and administer. Moreover, the
infrastructure for pumping, distributing,
and collecting sewerage and water is both
expensive and limited.

2. Quality - Naturally occurring and man-
made contaminants in groundwater
create a barrier to providing safe water
service. Treatment infrastructure to abate
contaminants is limited and expensive.

3. Control – Some jurisdictions do not have
direct control over water service to their
residents. Instead, that service is provided
by a third-party water district. Such
jurisdictions have limited ability to expand
service, even if the GSA would permit it.

Throughout the RHNA process, information
was provided to Steering Committee
members about how the methodologies under
consideration impact jurisdictions that lack
local control over water issues. Methodology
1C responds to regional water issues through
its use of non-water-related adjustment factors
that result in lower housing need allocated
to areas with the most severe infrastructure
issues and least control. These include the
Unincorporated area, which does not control
water service to its residents, and Dos Palos,
which is waiting on state funding for water
treatment infrastructure.

Following the May 18th, 2022 vote by the
35 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan RHNA Steering Committee to support
methodology option 1C, the Proposed
RHNA Methodology was released for public
comment on June 21st, 2022. After holding
a public hearing on July 21st, 2022, MCAG
staff forwarded RHNA Methodology Option
1C to HCD for review as the Draft RHNA
Methodology for the Merced region.

HCD completed its review on September 14th,
2022 and issued its determination that RHNA
Methodology Option 1C furthered all five RHNA
objectives. The Methodology was adopted by
MCAG’s Governing Board on September 15th,
2022.

4.8 Summary of
Jurisdictional
Allocations
The Adopted RHNA Methodology considers
all 12 of the statutorily required RHNA Factors
(per §65584.04.(e)) and furthers all five of the
RHNA Objectives per (§65584.D).

A complete summary of the adopted RHNA
Methodology summarized for each jurisdiction
and income group is included in table 7.

A more detailed summary of how each
adjustment factor impacted the summary table
below can be found in tables 8 and 9 on the
following page.

Jurisdiction
Lower Income Units Higher Income Units
Total
RHNA Very
Low Low
Very
Low +
Low
% of
Total
RHNA
(VL + L)
Moderate Above
Atwater 768 526 1,294 42.9% 508 1,215 3,017
Dos Palos 56 39 95 36.4% 49 117 261
Gustine 77 53 130 37.5% 64 152 346
Livingston 311 213 524 47.8% 169 404 1,097
Los Banos 719 493 1,212 38.7% 566 1,354 3,132
Merced 2,543 1,742 4,285 40.7% 1,838 4,394 10,517 Unincorporated
County 1,042 714 1,756 41.3% 736 1,758 4,250
Total 5,516 3,780 9,296 41.1% 3,930 9,394 22,620
Table 7: Cycle 6 (2023 – 2032) Final Adopted RHNA Methodology Summary Table 36 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Table 8: Weighting of Total Housing Need Adjustment Factors for the Adopted Methodology (Step 2) - Option 1C Jurisdiction
Amount of Nearby High Quality Agricultural Land (%) Ratio of Jobs-Within-A-15-Minute-Drive to Housing Summary of Total Allocation Adjusted
Allocation * Weight = Weighted
Adjustment (A)
Adjusted
Allocation * Weight = Weighted
Adjustment (B)
Before
Adjustments
(%)
Before
Adjustments
(HUs)
Adjusted
Allocation (%)
Sum (A,B)
Adjusted
Allocation
(HUs)
Adjustment
Atwater 11.8% 1/2 5.9% 14.8% 1/2 7.4% 12.2% 2,759 13.3% 3,017 257 Dos Palos 1.4% 1/2 0.7% 0.9% 1/2 0.4% 1.4% 319 1.2% 261 (58) Gustine 1.5% 1/2 0.7% 1.6% 1/2 0.8% 2.5% 561 1.5% 346 (215) Livingston 4.7% 1/2 2.4% 5.0% 1/2 2.5% 4.5% 1,020 4.8% 1,097 77 Los Banos 16.6% 1/2 8.3% 11.1% 1/2 5.5% 16.3% 3,692 13.8% 3,132 (560) Merced 46.4% 1/2 23.2% 46.6% 1/2 23.3% 39.6% 8,960 46.5% 10,517 1,557 Unincorporated County 17.5% 1/2 8.7% 20.1% 1/2 10.1% 23.5% 5,308 18.8% 4,250 (1,058) Total 100% - 50% 100% - 50% 100% 22,620 100% 22,620 -
Jurisdiction
Percent of Population Below the Poverty Line Percent of Housing Units in TCAC High Opportunity Areas
Percent of Population within 1/4 Mile of Transit
Stop
Summary of Below Moderate Income
Allocation
Adjusted
Allocation * Weight =
Weighted
Adjustment
(A)
Adjusted
Allocation * Weight =
Weighted
Adjustment
(B)
Adjusted
Allocation * Weight = Weighted
Adjustment (C)
Adjusted
Allocation (%)
Sum (A,B,C)
Adjusted
Allocation
(HUs)
Adjustment
Atwater 14.9% 1/3 5.0% 13.3% 1/3 4.4% 13.5% 1/3 4.5% 13.9% 1,294 54 Dos Palos 1.6% 1/3 0.5% 0.8% 1/3 0.3% 0.7% 1/3 0.2% 1.0% 95 (12) Gustine 2.2% 1/3 0.7% 1.0% 1/3 0.3% 0.9% 1/3 0.3% 1.4% 130 (12) Livingston 6.3% 1/3 2.1% 6.4% 1/3 2.1% 4.2% 1/3 1.4% 5.6% 524 73 Los Banos 17.1% 1/3 5.7% 11.6% 1/3 3.9% 10.5% 1/3 3.5% 13.0% 1,212 (75) Merced 34.1% 1/3 11.4% 47.7% 1/3 15.9% 56.4% 1/3 18.8% 46.1% 4,285 (37) Unincorporated County 23.8% 1/3 7.9% 19.2% 1/3 6.4% 13.7% 1/3 4.6% 18.9% 1,756 9 Total 100% - 33% 100% - 33% 100% - 33% 100% 9,296
Table 9: Weighting of Below-Moderate-Income Need Adjustment Factors for the Adopted Methodology (Step 3) - Option 1C 37 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan 5 Appendices
A. Acronym Glossary
• MCAG: Merced County Association of Governments
• RHNA: Regional Housing Needs Allocation
• AMI: Area Median Income
• HCD: The California Department of Housing and Community Development • DoF: California Department of Finance
• RTP/SCS: Regional Transportation Plan and Sustainable Communities Strategy • GHG: Greenhouse Gases
• LAFCO: Local Agency Formation Commission
• AB: Assembly Bill
• SB: Senate Bill
• T JPAMC: Transit Joint Powers Authority for Merced County • VMT: Vehicle Miles Traveled
• SOI: Sphere of Influence
• TCAC: California Tax Credit Allocation Committee
• TOD: Transit-Oriented Development
• ACE: Altamont Corridor Express Rail
• LATCH: Local Area Transportation Characteristics for Households • ACS: US Census Bureau’s American Community Survey
• LEHD: US Census Bureau’s Longitudinal Employer-Household Dynamics Data • WAC: LEHD’s Worker Area Characteristics Data
• HUD: US Department of Housing and Urban Development
• REAP: Regional Early Action Planning
38 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan B. HCD Regional Housing Needs Determination Letter

39 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

40 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

41 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

42 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

43 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan C. HCD Review of Draft RHNA Methodology

44 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

45 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

46 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

47 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan D. RHNA Methodology Options
As part of the RHNA process, 12 adjustment
factors were explored to develop 6 distinct
RHNA methodology options. They were
developed as follows.

First, the adjustment factors were refined from
the initial set of 12 to a final set of 7. Then, two
adjustment factor packages were developed to
allocate total RHNA (regardless of income) to
the region’s jurisdictions and three adjustment
factor packages were created to further
subdivide each jurisdictions’ total RHNA into
above and below-moderate income groups.

Together, these above and below-moderate
adjustment factor packages were combined to
create 6 methodology options which were then
vetted in partnership with the MCAG RHNA
Steering Committee, MCAG staff, and the
public.

Figure D1: Overview of RHNA Methodology Options
As figure D1 below shows, the 6 methodology
options are divided into two groups based on
which total RHNA adjustment factor package
was applied (group 1 vs group 2). Then, within
each group, the three below-moderate income
adjustment factor packages (A, B, C) are
applied.

Tables D1 - D12 on the following pages
summarize the adjustment factors and
weights used for each step in the methodology
process for each methodology option.

Detailed calculations and data sources are
further summarized in Appendix E: RHNA
Methodology Calculations.
48 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Jurisdiction
Amount of Nearby High Quality Agricultural Land (%) Ratio of Jobs-Within-A-15-Minute-Drive to Housing Summary of Total Allocation Adjusted
Allocation * Weight = Weighted
Adjustment (A)
Adjusted
Allocation * Weight = Weighted
Adjustment (B)
Before
Adjustments
(%)
Before
Adjustments
(HUs)
Adjusted
Allocation (%)
Sum (A,B)
Adjusted
Allocation
(HUs)
Adjustment
Atwater 11.8% 1/2 5.9% 14.8% 1/2 7.4% 12.2% 2,759 13.3% 3,017 257 Dos Palos 1.4% 1/2 0.7% 0.9% 1/2 0.4% 1.4% 319 1.2% 261 (58) Gustine 1.5% 1/2 0.7% 1.6% 1/2 0.8% 2.5% 561 1.5% 346 (215) Livingston 4.7% 1/2 2.4% 5.0% 1/2 2.5% 4.5% 1,020 4.8% 1,097 77 Los Banos 16.6% 1/2 8.3% 11.1% 1/2 5.5% 16.3% 3,692 13.8% 3,132 (560) Merced 46.4% 1/2 23.2% 46.6% 1/2 23.3% 39.6% 8,960 46.5% 10,517 1,557 Unincorporated County 17.5% 1/2 8.7% 20.1% 1/2 10.1% 23.5% 5,308 18.8% 4,250 (1,058) Total 100% - 50% 100% - 50% 100% 22,620 100% 22,620 -
Jurisdiction
Percent of Population Below the Poverty Line Percent of Housing Units in TCAC High Opportunity Areas Multifamily As Percent of Existing Housing Units Summary of Below Moderate Income Allocation
Adjusted
Allocation * Weight =
Weighted
Adjustment
(A)
Adjusted
Allocation * Weight =
Weighted
Adjustment
(B)
Adjusted
Allocation * Weight = Weighted
Adjustment (C)
Adjusted
Allocation (%)
Sum (A,B,C)
Adjusted
Allocation
(HUs)
Adjustment
Atwater 14.9% 1/3 5.0% 13.3% 1/3 4.4% 12.4% 1/3 4.1% 13.5% 1,259 19 Dos Palos 1.6% 1/3 0.5% 0.8% 1/3 0.3% 1.6% 1/3 0.5% 1.3% 123 16 Gustine 2.2% 1/3 0.7% 1.0% 1/3 0.3% 1.9% 1/3 0.6% 1.7% 158 16 Livingston 6.3% 1/3 2.1% 6.4% 1/3 2.1% 5.9% 1/3 2.0% 6.2% 577 126 Los Banos 17.1% 1/3 5.7% 11.6% 1/3 3.9% 17.7% 1/3 5.9% 15.5% 1,437 150 Merced 34.1% 1/3 11.4% 47.7% 1/3 15.9% 33.6% 1/3 11.2% 38.5% 3,576 (746) Unincorporated County 23.8% 1/3 7.9% 19.2% 1/3 6.4% 26.9% 1/3 9.0% 23.3% 2,166 419 Total 100% - 33% 100% - 33% 100% - 33% 100% 9,296
Table D2: Weighting of Below-Moderate-Income Need Adjustment Factors for the Adopted Methodology (Step 3) - Option 1A Table D1: Weighting of Total Housing Need Adjustment Factors for the Adopted Methodology (Step 2) - Option 1A OPT . 1A: HIGH QUALITY AG + JOBS-HOUSING BALANCE / POVERTY + OPPORTUNITY + % MULTIFAMIL Y 49 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Jurisdiction
Amount of Nearby High Quality Agricultural Land (%) Ratio of Jobs-Within-A-15-Minute-Drive to Housing Summary of Total Allocation Adjusted
Allocation * Weight = Weighted
Adjustment (A)
Adjusted
Allocation * Weight = Weighted
Adjustment (B)
Before
Adjustments
(%)
Before
Adjustments
(HUs)
Adjusted
Allocation (%)
Sum (A,B)
Adjusted
Allocation
(HUs)
Adjustment
Atwater 11.8% 1/2 5.9% 14.8% 1/2 7.4% 12.2% 2,759 13.3% 3,017 257 Dos Palos 1.4% 1/2 0.7% 0.9% 1/2 0.4% 1.4% 319 1.2% 261 (58) Gustine 1.5% 1/2 0.7% 1.6% 1/2 0.8% 2.5% 561 1.5% 346 (215) Livingston 4.7% 1/2 2.4% 5.0% 1/2 2.5% 4.5% 1,020 4.8% 1,097 77 Los Banos 16.6% 1/2 8.3% 11.1% 1/2 5.5% 16.3% 3,692 13.8% 3,132 (560) Merced 46.4% 1/2 23.2% 46.6% 1/2 23.3% 39.6% 8,960 46.5% 10,517 1,557 Unincorporated County 17.5% 1/2 8.7% 20.1% 1/2 10.1% 23.5% 5,308 18.8% 4,250 (1,058) Total 100% - 50% 100% - 50% 100% 22,620 100% 22,620 -
Jurisdiction
Percent of Population Below the Poverty Line Percent of Housing Units in TCAC High Opportunity Areas
Summary of Below Moderate Income
Allocation
Adjusted
Allocation * Weight =
Weighted
Adjustment
(A)
Adjusted
Allocation * Weight =
Weighted
Adjustment
(B)
Adjusted
Allocation (%)
Sum (A,B)
Adjusted
Allocation
(HUs)
Adjustment
Atwater 14.9% 1/2 7.5% 13.3% 1/2 6.7% 14.1% 1,313 73
Dos Palos 1.6% 1/2 0.8% 0.8% 1/2 0.4% 1.2% 109 2
Gustine 2.2% 1/2 1.1% 1.0% 1/2 0.5% 1.6% 151 9
Livingston 6.3% 1/2 3.2% 6.4% 1/2 3.2% 6.4% 591 140
Los Banos 17.1% 1/2 8.5% 11.6% 1/2 5.8% 14.3% 1,331 44 Merced 34.1% 1/2 17.1% 47.7% 1/2 23.9% 40.9% 3,804 (518) Unincorporated County 23.8% 1/2 11.9% 19.2% 1/2 9.6% 21.5% 1,997 250 Total 100% - 50% 100% - 50% 100% 9,296
Table D4: Weighting of Below-Moderate-Income Need Adjustment Factors for the Adopted Methodology (Step 3) - Option 1B Table D3: Weighting of Total Housing Need Adjustment Factors for the Adopted Methodology (Step 2) - Option 1B OPT . 1B: HIGH QUALITY AG + JOBS-HOUSING BALANCE / POVERTY + OPPORTUNITY 50 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Jurisdiction
Amount of Nearby High Quality Agricultural Land (%) Ratio of Jobs-Within-A-15-Minute-Drive to Housing Summary of Total Allocation Adjusted
Allocation * Weight = Weighted
Adjustment (A)
Adjusted
Allocation * Weight = Weighted
Adjustment (B)
Before
Adjustments
(%)
Before
Adjustments
(HUs)
Adjusted
Allocation (%)
Sum (A,B)
Adjusted
Allocation
(HUs)
Adjustment
Atwater 11.8% 1/2 5.9% 14.8% 1/2 7.4% 12.2% 2,759 13.3% 3,017 257 Dos Palos 1.4% 1/2 0.7% 0.9% 1/2 0.4% 1.4% 319 1.2% 261 (58) Gustine 1.5% 1/2 0.7% 1.6% 1/2 0.8% 2.5% 561 1.5% 346 (215) Livingston 4.7% 1/2 2.4% 5.0% 1/2 2.5% 4.5% 1,020 4.8% 1,097 77 Los Banos 16.6% 1/2 8.3% 11.1% 1/2 5.5% 16.3% 3,692 13.8% 3,132 (560) Merced 46.4% 1/2 23.2% 46.6% 1/2 23.3% 39.6% 8,960 46.5% 10,517 1,557 Unincorporated County 17.5% 1/2 8.7% 20.1% 1/2 10.1% 23.5% 5,308 18.8% 4,250 (1,058) Total 100% - 50% 100% - 50% 100% 22,620 100% 22,620 -
Jurisdiction
Percent of Population Below the Poverty Line Percent of Housing Units in TCAC High Opportunity Areas
Percent of Population within 1/4 Mile of Transit
Stop
Summary of Below Moderate Income
Allocation
Adjusted
Allocation * Weight =
Weighted
Adjustment
(A)
Adjusted
Allocation * Weight =
Weighted
Adjustment
(B)
Adjusted
Allocation * Weight = Weighted
Adjustment (C)
Adjusted
Allocation (%)
Sum (A,B,C)
Adjusted
Allocation
(HUs)
Adjustment
Atwater 14.9% 1/3 5.0% 13.3% 1/3 4.4% 13.5% 1/3 4.5% 13.9% 1,294 54 Dos Palos 1.6% 1/3 0.5% 0.8% 1/3 0.3% 0.7% 1/3 0.2% 1.0% 95 (12) Gustine 2.2% 1/3 0.7% 1.0% 1/3 0.3% 0.9% 1/3 0.3% 1.4% 130 (12) Livingston 6.3% 1/3 2.1% 6.4% 1/3 2.1% 4.2% 1/3 1.4% 5.6% 524 73 Los Banos 17.1% 1/3 5.7% 11.6% 1/3 3.9% 10.5% 1/3 3.5% 13.0% 1,212 (75) Merced 34.1% 1/3 11.4% 47.7% 1/3 15.9% 56.4% 1/3 18.8% 46.1% 4,285 (37) Unincorporated County 23.8% 1/3 7.9% 19.2% 1/3 6.4% 13.7% 1/3 4.6% 18.9% 1,756 9 Total 100% - 33% 100% - 33% 100% - 33% 100% 9,296
Table D6: Weighting of Below-Moderate-Income Need Adjustment Factors for the Adopted Methodology (Step 3) - Option 1C Table D5: Weighting of Total Housing Need Adjustment Factors for the Adopted Methodology (Step 2) - Option 1C OPT . 1C: HIGH QUALITY AG + JOBS-HOUSING BAL. / POVERTY + OPPORTUNITY + TRANSIT (ADOPTED METHODOLOGY) 51 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Jurisdiction
"Integrated Planning" Scenario Allocation Ratio of Jobs-Within-A-15-Minute-Drive to Housing Summary of Total Allocation Adjusted
Allocation * Weight = Weighted
Adjustment (A)
Adjusted
Allocation * Weight = Weighted
Adjustment (B)
Before
Adjustments
(%)
Before
Adjustments
(HUs)
Adjusted
Allocation (%)
Sum (A,B)
Adjusted
Allocation
(HUs)
Adjustment
Atwater 7.7% 1/2 3.9% 14.8% 1/2 7.4% 12.2% 2,759 11.3% 2,553 (207) Dos Palos 1.4% 1/2 0.7% 0.9% 1/2 0.4% 1.4% 319 1.1% 252 (67) Gustine 2.3% 1/2 1.1% 1.6% 1/2 0.8% 2.5% 561 1.9% 437 (124) Livingston 4.5% 1/2 2.2% 5.0% 1/2 2.5% 4.5% 1,020 4.7% 1,067 47 Los Banos 16.6% 1/2 8.3% 11.1% 1/2 5.5% 16.3% 3,692 13.8% 3,129 (563) Merced 49.9% 1/2 24.9% 46.6% 1/2 23.3% 39.6% 8,960 48.2% 10,908 1,948 Unincorporated County 17.7% 1/2 8.8% 20.1% 1/2 10.1% 23.5% 5,308 18.9% 4,274 (1,034) Total 100% - 50% 100% - 50% 100% 22,620 100% 22,620 -
Jurisdiction
Percent of Population Below the Poverty Line Percent of Housing Units in TCAC High Opportunity Areas Multifamily As Percent of Existing Housing Units Summary of Below Moderate Income Allocation
Adjusted
Allocation * Weight =
Weighted
Adjustment
(A)
Adjusted
Allocation * Weight =
Weighted
Adjustment
(B)
Adjusted
Allocation * Weight = Weighted
Adjustment (C)
Adjusted
Allocation (%)
Sum (A,B,C)
Adjusted
Allocation
(HUs)
Adjustment
Atwater 12.7% 1/3 4.2% 11.3% 1/3 3.8% 10.5% 1/3 3.5% 11.5% 1,068 19 Dos Palos 1.5% 1/3 0.5% 0.7% 1/3 0.2% 1.6% 1/3 0.5% 1.3% 119 16 Gustine 2.8% 1/3 0.9% 1.3% 1/3 0.4% 2.4% 1/3 0.8% 2.2% 201 21 Livingston 6.2% 1/3 2.1% 6.2% 1/3 2.1% 5.8% 1/3 1.9% 6.1% 563 124 Los Banos 17.1% 1/3 5.7% 11.6% 1/3 3.9% 17.8% 1/3 5.9% 15.5% 1,441 155 Merced 35.6% 1/3 11.9% 49.6% 1/3 16.5% 34.9% 1/3 11.6% 40.0% 3,719 (764) Unincorporated County 24.1% 1/3 8.0% 19.3% 1/3 6.4% 27.1% 1/3 9.0% 23.5% 2,185 429 Total 100% - 33% 100% - 33% 100% - 33% 100% 9,296
Table D8: Weighting of Below-Moderate-Income Need Adjustment Factors for the Adopted Methodology (Step 3) - Option 2A Table D7: Weighting of Total Housing Need Adjustment Factors for the Adopted Methodology (Step 2) - Option 2A OPT . 2A: INTEGRATED PLANNING SCENARIO + JOBS-HOUSING BAL. / POVERTY + OPPORTUNITY + MULTIFAMIL Y 52 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Jurisdiction
"Integrated Planning" Scenario Allocation Ratio of Jobs-Within-A-15-Minute-Drive to Housing Summary of Total Allocation Adjusted
Allocation * Weight = Weighted
Adjustment (A)
Adjusted
Allocation * Weight = Weighted
Adjustment (B)
Before
Adjustments
(%)
Before
Adjustments
(HUs)
Adjusted
Allocation (%)
Sum (A,B)
Adjusted
Allocation
(HUs)
Adjustment
Atwater 7.7% 1/2 3.9% 14.8% 1/2 7.4% 12.2% 2,759 11.3% 2,553 (207) Dos Palos 1.4% 1/2 0.7% 0.9% 1/2 0.4% 1.4% 319 1.1% 252 (67) Gustine 2.3% 1/2 1.1% 1.6% 1/2 0.8% 2.5% 561 1.9% 437 (124) Livingston 4.5% 1/2 2.2% 5.0% 1/2 2.5% 4.5% 1,020 4.7% 1,067 47 Los Banos 16.6% 1/2 8.3% 11.1% 1/2 5.5% 16.3% 3,692 13.8% 3,129 (563) Merced 49.9% 1/2 24.9% 46.6% 1/2 23.3% 39.6% 8,960 48.2% 10,908 1,948 Unincorporated County 17.7% 1/2 8.8% 20.1% 1/2 10.1% 23.5% 5,308 18.9% 4,274 (1,034) Total 100% - 50% 100% - 50% 100% 22,620 100% 22,620 -
Jurisdiction
Percent of Population Below the Poverty Line Percent of Housing Units in TCAC High Opportunity Areas
Summary of Below Moderate Income
Allocation
Adjusted
Allocation * Weight =
Weighted
Adjustment
(A)
Adjusted
Allocation * Weight =
Weighted
Adjustment
(B)
Adjusted
Allocation (%)
Sum (A,B)
Adjusted
Allocation
(HUs)
Adjustment
Atwater 12.7% 1/2 4.2% 11.3% 1/2 3.8% 12.0% 1,114 65
Dos Palos 1.5% 1/2 0.5% 0.7% 1/2 0.2% 1.1% 106 2
Gustine 2.8% 1/2 0.9% 1.3% 1/2 0.4% 2.1% 192 12
Livingston 6.2% 1/2 2.1% 6.2% 1/2 2.1% 6.2% 577 139
Los Banos 17.1% 1/2 5.7% 11.6% 1/2 3.9% 14.4% 1,335 49 Merced 35.6% 1/2 11.9% 49.6% 1/2 16.5% 42.6% 3,957 (526) Unincorporated County 24.1% 1/2 8.0% 19.3% 1/2 6.4% 21.7% 2,015 259 Total 100% - 50% 100% - 50% 100% 9,296
Table D10: Weighting of Below-Moderate-Income Need Adjustment Factors for the Adopted Methodology (Step 3) - Option 2B Table D9: Weighting of Total Housing Need Adjustment Factors for the Adopted Methodology (Step 2) - Option 2B OPT . 2B: INTEGRATED PLANNING SCENARIO + JOBS-HOUSING BALANCE / POVERTY + OPPORTUNITY 53 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Jurisdiction
"Integrated Planning" Scenario Allocation Ratio of Jobs-Within-A-15-Minute-Drive to Housing Summary of Total Allocation Adjusted
Allocation * Weight = Weighted
Adjustment (A)
Adjusted
Allocation * Weight = Weighted
Adjustment (B)
Before
Adjustments
(%)
Before
Adjustments
(HUs)
Adjusted
Allocation (%)
Sum (A,B)
Adjusted
Allocation
(HUs)
Adjustment
Atwater 11.8% 1/2 5.9% 14.8% 1/2 7.4% 12.2% 2,759 13.3% 3,017 257 Dos Palos 1.4% 1/2 0.7% 0.9% 1/2 0.4% 1.4% 319 1.2% 261 (58) Gustine 1.5% 1/2 0.7% 1.6% 1/2 0.8% 2.5% 561 1.5% 346 (215) Livingston 4.7% 1/2 2.4% 5.0% 1/2 2.5% 4.5% 1,020 4.8% 1,097 77 Los Banos 16.6% 1/2 8.3% 11.1% 1/2 5.5% 16.3% 3,692 13.8% 3,132 (560) Merced 46.4% 1/2 23.2% 46.6% 1/2 23.3% 39.6% 8,960 46.5% 10,517 1,557 Unincorporated County 17.5% 1/2 8.7% 20.1% 1/2 10.1% 23.5% 5,308 18.8% 4,250 (1,058) Total 100% - 50% 100% - 50% 100% 22,620 100% 22,620 -
Jurisdiction
Percent of Population Below the Poverty Line Percent of Housing Units in TCAC High Opportunity Areas
Percent of Population within 1/4 Mile of Transit
Stop
Summary of Below Moderate Income
Allocation
Adjusted
Allocation * Weight =
Weighted
Adjustment
(A)
Adjusted
Allocation * Weight =
Weighted
Adjustment
(B)
Adjusted
Allocation * Weight = Weighted
Adjustment (C)
Adjusted
Allocation (%)
Sum (A,B,C)
Adjusted
Allocation
(HUs)
Adjustment
Atwater 12.7% 1/3 4.2% 11.3% 1/3 3.8% 11.4% 1/3 3.8% 11.8% 1097 48 Dos Palos 1.5% 1/3 0.5% 0.7% 1/3 0.2% 0.7% 1/3 0.2% 1.0% 92 (12) Gustine 2.8% 1/3 0.9% 1.3% 1/3 0.4% 1.2% 1/3 0.4% 1.8% 164 (15) Livingston 6.2% 1/3 2.1% 6.2% 1/3 2.1% 4.1% 1/3 1.4% 5.5% 511 72 Los Banos 17.1% 1/3 5.7% 11.6% 1/3 3.9% 10.4% 1/3 3.5% 13.1% 1214 (72) Merced 35.6% 1/3 11.9% 49.6% 1/3 16.5% 58.4% 1/3 19.5% 47.9% 4448 (35) Unincorporated County 24.1% 1/3 8.0% 19.3% 1/3 6.4% 13.8% 1/3 4.6% 19.0% 1770 14 Total 100% - 33% 100% - 33% 100% - 33% 100% 9,296
Table D12: Weighting of Below-Moderate-Income Need Adjustment Factors for the Adopted Methodology (Step 3) - Option 2C Table D11: Weighting of Total Housing Need Adjustment Factors for the Adopted Methodology (Step 2) - Option 2C OPT . 2C: INTEGRATED PLANNING SCENARIO + JOBS-HOUSING BALANCE / POVERTY + OPPORTUNITY + TRANSIT 54 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan E. RHNA Methodology Calculations
This section discusses the calculations
the draft methodology employs to adjust
jurisdictions’ housing need allocations using
adjustment factor data.

The purpose of adjustment factors is to
raise or lower jurisdictions’ total or below-
moderate-income allocations to make the
allocation more reflective of the RHNA
Objectives. For example, using transit access
as an adjustment factor lowers the below-
moderate-income housing need allocations of
jurisdictions with less transit access and vice
versa. That helps the final allocation reflect the
“Infill, Equity, and Environment” objective.

Adjustment factors affect allocations through
the following series of calculations, shown in
Tables E1 - E3 on the following page:

1. Start with a baseline allocation: the 2018
RTP/SCS household allocation (Column A).

2. Convert the raw data for the adjustment
factor, in this case raw Median Household
Income data (Column B), into a rescaled
ranking from 0.67 to 1.33 (Column C). This
is done by using the following formula:

0.667 + (1.334 - 0.667) * (Maximum(Raw
Adjustment Factor Data) - Particular
Observation of the Adjustment Factor Data)
/ (Maximum(Raw Adjustment Factor Data)
– Minimum(Raw Adjustment Factor Data)).

This formula sets the “floor” of the rescaled
values at 0.67, then attributes up to an
additional 0.67 in value depending on
how large a particular observation in the
adjustment factor data is relative to the
mathematical range of the adjustment
factor data. Using this formula, the
smallest observation iis assigned a score
of 0.667 and the largest observation in
the adjustment factor data is assigned a
score of 1.334. All other observations are
assigned scores between 0.667 and 1.334.

3. Multiply the 0.667 to 1.334 rankings
(Column C) by the baseline allocation
(Column A) to apply the adjustment to the
baseline allocation, resulting in Column
D. This column will not add up to 100%,
meaning either more than 100% or less
than 100% of the region’s housing need is
being allocated. In this case, the amount is
105%

4. Adjust Column D so it sums to 100% by
dividing each jurisdiction’s value for Column
D by the sum of Column D. This yields
Column E, the allocation adjusted for the
adjustment factor in question.

5. This process is repeated for each
adjustment factor, yielding Table 9 below.

By averaging the adjusted allocations in
Table 9 for multiple adjustment factors and
applying weights, we can arrive at a final,
adjusted allocation that reflects multiple
factors and furthers the RHNA Objectives. The
methodologies proposed in this RHNA cycle all
used equal weights, meaning a simple average
of the adjusted allocation percentages for the
three adjustment factors was used calculate
the percentage of housing need allocated to
each jurisdiction.
55 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Table E1: Adjustment Factor Data Used in RHNA Methodologies Table E2: Calculations Demonstrating How Adjustment Factor Data is Processed into an Adjusted Allocation Table E3: Adjusted Allocations for Each Adjustment Factor Resulting from Processing Steps Above 56 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan RHNA Adjustment Factor Calculation
Instructions
A spreadsheet software such as Excel and GIS
platform such as R or ArcMap are required
to complete the calculation steps described
below.

1. Baseline Allocation (2018 RTP/SCS
Household Allocation as of Modeled Year
2035)
Description
A jurisdiction’s share of the region’s anticipated
household growths in through 2035, per the
adopted 2018 RTP/SCS preferred scenario.

This data was used to establish the baseline
total housing need allocation. It was not used
as an adjustment factor.

Source
MCAG 2018 RTP/SCS Preferred Scenario.

How to Calculate
• Gather the 2035 household allocation
information from MCAG’s 2018 RTP/SCS
Report in Excel or similar.
• South Dos Palos’ household allocation
is reported combined with Dos Palos’
household allocation in the RTP/SCS
report. Begin by disambiguating that. Since
South Dos Palos is forecasted to have
27% of those two jurisdictions’ combined
populations, subtract 27% from Dos Palos’
household allocation. Assign the removed
household allocation to the Unincorporated
County, which is what South Dos Palos is
within.
• Now that Dos Palos’ allocation is fixed,
divide each jurisdictions’ household
allocation by the region’s total households,
yielding each jurisdiction’s share of the
region’s households growth according to
the 2018 RTP/SCS.

2. Percent of a Jurisdiction’s SOI that is High
Quality Agricultural Land
Description
Percentage of a jurisdiction’s SOI land that
is categorized as prime agricultural land or
agricultural land of statewide significance by
the Department of Conservations Farmland
Mapping and Monitoring Project (FMMP).

Source
• FMMP important farmland finder data
• Jurisdiction sphere of influence shapefiles
How to Calculate
• In your preferred GIS platform, load
FMMP important farmland polygons and
jurisdiction’s SOI polygons.
• Clip FMMP polygons to SOI polygons, so
that each SOI has its own unique polygons
representing its farmland of statewide
significance, prime farmland, natural
vegetation, water, and grazing land. For
the unincorporated area, clip to the entire
unincorporated area rather than a specific
SOI polygon.
• Calculate the area in each SOI that is
farmland of statewide significance or prime
farmland
• Calculate the buildable area in each SOI
by subtracting the following from total
area: water, natural vegetation, or grazing
land (which tends to be heavily sloped and
unbuildable).
57 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan • Divide the farmland area by the net area
calculated above, yielding the percentage of
land that is high quality agricultural land.

3. Percent of Population within ¼ Mile of
Transit
Description
Percentage of population in each jurisdiction
served by any fixed route transit service.

Source
Merced Transit Agency jurisdiction-level data
on population served by buses.

How to Calculate
No calculations required. The data was used as
reported.

4. Integrated Planning” RTP Housing
Allocation
Description
Difference between the percentage of housing
allocated to each jurisdiction in the integrated
planning scenario and the percentage
of households in 2035 allocated to each
jurisdiction in the 2018 RTP/SCS preferred
scenario.

Sources
• MCAG 2018 RTP/SCS household allocation
by jurisdiction for 2018 (see the baseline
allocation calculations above).
• Integrated planning scenario
documentation, available through the CA
Department of Conservation and the Nature
Conservancy.

How to Calculate
Subtract each jurisdiction’s share of housing
units in the Integrated Planning Scenario from
the 2018 RTP Household Allocation.

Table E4: Calculating the Difference Between the 2018 RTP and Integrated Planning Scenario Housing Allocations

58 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

5. Jobs-Housing Balance
Description
Ratio of housing units to jobs accessible within
a 15-minute drive.

Sources
• 2019 5-Year American Community Survey
(ACS) Table B25001
• Longitudinal Employer Household
Dynamics Workplace Area Characteristics
(LEHD WAC) data for Merced County, all
jobs (2019)
How to Calculate
• Download the ACS housing unit counts
listed above at the block group level.
• Join the ACS data with Census block group
polygons geometries using the GEOID
identifiers.
• Download LEHD WAC data of counts of
jobs from the LEHD website. Aggregate the
blocks into their respective block groups.
• Perform a table join between the LEHD
WAC data and Census block group
polygons geometries using the GEOID
• Using a GIS platform, identify the Census
block group centroids within each Census
block group polygon.
• Spatially join the Census block group
centroids to Census place polygons for the
jurisdictions and the unincorporated county
area. This effectively assigns the ACS block
groups and their housing unit counts to
each jurisdiction and the unincorporated
area. Use a 1,000 foot buffer around
place polygons to ensure centroids at the
margins of a jurisdiction’s boundaries are
correctly joined.
• Calculate the percentage of each
jurisdiction’s housing units that are
contained within each Census block
group. If a block group contains 300 of a
jurisdiction’s 1,000 units, it has 30%. This
data will be used for a weighted average
calculation later.
• Use an isochrone creation service or
package, such as the free and open
source “openrouteservice” package in
R, to calculate the 15-minute drive time
isochrone from each Census block
group centroid. This, in effect, identifies
everywhere one can drive in 15 minutes
from a block group.
• Spatially join block group centroids with
jobs and housing counts to each isochrone
and sum up the jobs in the block groups
joined with each isochrone. This provides
you with the count of jobs reachable in a
15-minute drive from each block group.
• Divide jobs accessible in each isochrone by
housing units in the isochrone’s originating
block group. This provides a ratio of jobs-
accessible within a 15 minute drive to
housing units for each block group.
• For each jurisdiction’s composite block
groups, create a weighted average of the
above calculated ratio using the percentage
of each jurisdiction’s housing units that
fall within each Census block group, as
calculated several steps above. This yields
the typical ratio of jobs accessible within
15 minutes to housing units for each
jurisdiction.
59 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan

6. Population Below Poverty Limit
Description
Percentage of each jurisdiction’s population
that is below the federal poverty limit.

Source
2019 5-Year ACS Table for Poverty Status by
Sex by Age (B17001)
How to Calculate
• Look up the Table B17001 for each
jurisdiction.
• Divide the population in poverty by the total
population to calculate the percent.
• Identify the unincorporated area population
by summing the population in poverty for
incorporated cities, then subtracting that
sum from the countywide population in
poverty. Divide that number by the total
population of the unincorporated area

7. Existing Housing Units That Are
Multifamily
Description
Percentage of each jurisdiction’s housing units
that are in structures with greater than one
dwelling unit.

Source
2019 5-Year ACS Table for Units in Structure
(B25024)
How to Calculate
• Look up the Table B25024 for each of the
jurisdictions.
• Sum the housing units in structures with
more than one dwelling unit and divide that
sum by the total number of housing units.
• Identify the unincorporated area housing
units in structures with more than one unit
by summing that datapoint for incorporated
cities, then subtracting that sum from the
countywide number of housing units in
structures with more than one unit. Divide
that number by the total housing units of
the unincorporated area (identified using
the same strategy as described above).

8. Access to Opportunity (Housing Units in
TCAC High Opportunity Areas)
Description
Percentage of a jurisdiction’s households that
fall within Census tracts and block groups
designated by TCAC as offering High or
Highest opportunity levels.

Source
• TCAC Census tract and block group
opportunity categories
• 2019 5-Year ACS Table B25001 for counts
of housing units
How to Calculate
• In a GIS platform, table join TCAC
Opportunity Category data and ACS
housing unit counts with Census polygons
using the GEOID. TCAC Opportunity data
is given at both the Census tract and block
group level, necessitating the use of both
geometries simultaneously.
• Convert Census tract and block group
polygons to Census tract and block group
centroids to facilitate a spatial join.
60 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan • Spatially join the Census tract and block
group centroids to Census place polygons
for the jurisdictions and the unincorporated
county area. This effectively assigns
the ACS housing unit counts and TCAC
Opportunity data to each jurisdiction and
the unincorporated area. Use a 1000 foot
buffer around place polygons to ensure
centroids at the margins of a jurisdiction’s
boundaries are correctly joined.
• For each jurisdiction, sum the housing
units for the centroids that were spatially
joined to it. This yields each jurisdiction’s
total housing units as well as the housing
units within any TCAC High and Highest
opportunity tracts or block groups that
approximately fall within that jurisdiction.
• For each jurisdiction, divide housing units in
High or Highest opportunity areas by total
housing units. This yields the percentage
of a jurisdiction’s housing units that are in
High or Highest opportunity areas.
61 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan F . Comments Received on the Draft RHNA Methodology
MCAG released the Proposed RHNA Methodology Framework Memorandum for public comment on June 21st, 2022. A public hearing was held during the July 21st meeting of the MCAG Governing Board to solicit additional public comment. The public comment period subsequently closed on July 26th, 2022. A summary of comments received during the public comment period, as well as responses to those comments, is included below.

Comment #1
Received: July 19th, 2022
Transmission Method: Email
Commenter: Judy Evans, Merced Resident
Merced is in a valley, in a high desert environment. When used and managed properly, it sustains itself, which it has done for many many years. The land was covered with grass, crops, and animals which cooled and fed the land. We used to have dense fog, created by the system going on between all of them, which cooled and watered the land, putting water back in the aquifers.

Now we have concrete, which reflects the heat and keeps the water out of the land. I don’t remember the last time I saw fog.

We have already exceeded the limit of tolerance in regard to building. As far as the lack of housing, isn’t that from a lack of planning when we knew we would have an influx of people for the UC? Shouldn’t that have been addressed BEFORE it became a crisis? I know that people in governments want bigger and more of everything, but we need to just stop and look at the big picture. People moved to Merced to get out of the city and into a more calm, slower pace of life. This was the “country”. The buses running now are empty. We don’t need more people. It is bad for the environment, and unfair to those of us who plan to live here permanently. I am clearly against more buildings. Cities have a lot of people who come and go, never becoming part of the community. Merced is not a big city. Please don’t try to make it one.

Judy Evans
Merced Resident
62 MCAG Cycle 6 Regional Housing Needs Allocation (RHNA) Plan Response to Comment #1
Thank you for your interest in MCAG’s Regional Housing Needs Allocation (RHNA) process.

We understand and appreciate your concern for the region’s environmental quality. We acknowledge that population growth has impacted the Merced region’s landscape. While the region’s jurisdictions have no control over population growth, they do have control over land use regulations. These regulations, which include zoning, can help accommodate population growth in a way that is equitable, affordable, and considerate of its environmental impact.

Environmental impacts were frequently considered during the development of the RHNA methodology options and in the selection of the Draft RHNA Methodology. Within the description of the Draft RHNA Methodology, you will see that it respects sustainable growth patterns through its consistency with the Regional Transportation Plan and Sustainable Communities Strategy (RTP/SCS). In addition, the RHNA Methodology was evaluated in terms of its potential impact on water quality, supply, and management.

The RHNA process is mandated by the State of California’s Housing Element Law. MCAG has little control over the region’s total housing need, which is determined by the Department of Housing and Community Development (HCD) and the Department of Finance (DoF). The region’s housing need is determined not only by projected population growth, but also by the dire housing conditions being experienced by the region’s residents today. These include overcrowding of housing units and overpayment for housing. Ultimately, MCAG and its member jurisdictions are bound by Housing Element Law to distribute and accommodate the region’s housing need in a way that is equitable and sustainable for the benefit of current and future residents.