Evaluation of Alternative Methods for Calculating AMI in Washington — Report to the Legislature (August 2025)
Summary
This August 2025 report to the Legislature from the Washington State Department of Commerce, Housing Policy and Strategic Initiatives, evaluates alternative methods for calculating area median income (AMI) in Washington. It was authorized by the 2023-2025 operating supplemental budget (ESSB 5950) Section 127, with BERK Consulting and Novogradac named in the acknowledgments. The study evaluates six alternative methods and compares them to the current method, HUD Median Family Income (MFI). The table of contents lists four recommendations, beginning with not developing and implementing an alternative AMI for Washington, and appendices that include a 2025 table of HUD income limits for Washington counties.
Summary drafted by a model from the document's text below and checked by script against that text before publication. It is a navigation aid, not a reading of what the document proves. Where AI is used
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“Evaluation of Alternative Methods for Calculating AMI in Washington — Report to the Legislature (August 2025).”
Archived at Pandemic Darlings, https://pandemicdarlings.com/source-documents/2025-amistudy-legreport-final-pub-9018352e-6448-4e67-99d6-97b48d91948a-5da6fb0715/
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Evaluation of alternative
methods for calculating AMI
in Washington
Final report authorized by the 2023-2025 operating supplemental
budget (ESSB 5950) Section 127.
August 2025
Report to the Legislature
HOUSING POLICY AND Director Nguyễn
STRATEGIC INITIATIVES
v3.5
Acknowledgments
Washington State Department of Commerce
Tedd Kelleher, Acting Co-Assistant Director,
Housing Division
Kirsten Jewell, Acting Director of Policy, Housing
Division
Augustine Sughrua, Housing Policy Senior
Coordinator, Housing Division
Kayla Judd, Housing Policy Project Coordinator,
Housing Division
BERK Consulting
Kevin Ramsey, PhD, Associate Principal
Madalina Calen
Ana Costa
Dawn Couch
Josh Linden
Novogradac
Thomas Stagg
1011 Plum St. SE
P.O. Box 42525
Olympia, WA 98504-2525
www.commerce.wa.gov
This report is available in formats suitable for people
with disabilities. To submit a request, please call 360-
725-4000.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 2
Table of Contents
Key terms in this report................................................................................................................................ 5
Executive summary...................................................................................................................................... 7
Background ............................................................................................................................................................................... 7
Legislative directive ................................................................................................................................................................. 7
About this report ...................................................................................................................................................................... 7
Impacts of AMI on affordable housing in Washington ..................................................................................................... 8
Alternative AMI methods evaluated ..................................................................................................................................... 9
Summary of key findings and recommendations ........................................................................................................... 10
What is AMI? ............................................................................................................................................. 12
Common uses of AMI ........................................................................................................................................................... 12
HUD's method for calculating AMI ..................................................................................................................................... 13
Income limits associated with AMI .................................................................................................................................... 15
Washington programs with AMI-based income limits ................................................................................. 19
Concerns about HUD's AMI and related income limits ................................................................................. 21
AMI impacts where it is feasible to build new affordable housing............................................................................... 21
In areas with low AMI, many residents who need housing support are ineligible for housing assistance .......... 23
Rents based on AMI income limits can result in housing cost burden ....................................................................... 25
Misalignment between AMI and local incomes creates challenges to meeting housing needs............................ 26
AMI can increase faster than the incomes of affordable housing residents ............................................................. 27
Evaluation of alternative AMI methods ....................................................................................................... 28
AMI methods proposed for consideration ........................................................................................................................ 28
Alternative AMI methods selected for evaluation............................................................................................................ 28
Example 60% AMI income limits for each alternative .................................................................................................... 29
Impact and feasibility evaluation ........................................................................................................................................ 30
Recommendations and policy considerations ............................................................................................. 50
1) Do not develop and implement an alternative AMI for Washington .................................................................... 50
2) Tailor income limit targets to reflect local needs and conditions ........................................................................ 50
3) Differentiate income and rent limits to lower cost burden .................................................................................... 50
4) Revise income eligibility calculations to account for medical or dependent care expenses .......................... 50
Appendix A. Engagement summary report.................................................................................................. 51
Introduction............................................................................................................................................................................. 51
Engagement objectives ........................................................................................................................................................ 51
Advisory bodies ...................................................................................................................................................................... 51
Appendix B. Literature review .................................................................................................................... 64
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 3
2.0
Overview of AMI calculation methodology ....................................................................................................................... 64
Historical changes to HUD AMI calculation...................................................................................................................... 68
Limitations of HUD MFI ........................................................................................................................................................ 69
Income limits derived from HUD MFI ................................................................................................................................ 72
Impacts of HUD income limits ............................................................................................................................................ 76
Examples of alternative AMI or income limit calculations ............................................................................................. 78
Appendix C. Alternative AMI and impact analysis methodologies ............................................................... 81
Proposed alternatives ........................................................................................................................................................... 81
AMI methodology .................................................................................................................................................................. 81
VLI methodology .................................................................................................................................................................... 83
60% AMI income limit methodology .................................................................................................................................. 86
Impact analysis ...................................................................................................................................................................... 86
Appendix D. HUD MFI and income limits by area, 2025 ............................................................................... 88
2025 HUD income limits for Washington counties ......................................................................................................... 88
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 4
Key terms in this report
AMI (Area Median Income)
Generally, this is the median income of all households living in a defined geographic area. However, the term is
widely used to mean the Median Family Income (MFI) calculation published by the U.S. Department of Housing
and Urban Development (HUD). Unless otherwise noted, in this report, the term AMI means to HUD MFI.
Cost-burdened
HUD considers a household cost-burdened if it spends more than 30% of its income on housing costs. Cost-
burdened households typically have limited funds for other needs like food, transportation and health care.
Fair Market Rent (FMR)
The U.S. Department of Housing and Urban Development defines FMR as the 40th percentile of gross rents for
typical rental units occupied by recent movers in a local housing market. HUD updates FMR annually.
Family household
A group of people related by birth, marriage, or adoption who live together.
Household
A household is all the people who occupy a housing unit as their usual place of residence. A household can
have just one person or several. It can be composed of a family or unrelated people living together.
Household income
The combined income of all members of a household. Income may include wages, tips, bonuses, social
security benefits, unemployment, or other money received regularly.
HUD Median Family Income (HUD MFI)
Also known as AMI, HUD MFI is a calculation published annually for individual counties and multi-county
metropolitan areas. It is calculated by taking the latest available Census estimate of median family income and
projecting it forward to the current year.
Income limits
HUD publishes income limits that affordable housing programs use to determine eligibility and rents. These
income limits are typically calculated as a percentage of HUD MFI, and affordable housing practitioners often
refer to them with terms such as "50% AMI" or "80% AMI." Income limits are also adjusted by household size,
assuming that HUD MFI represents a 4-person household.
Low-income household
A household with a total income below 80% AMI for its geographic area.
Moderate-income household
A household with a total income between 80% and 120% of the AMI for its geographic area. While not always
eligible for subsidized housing, moderate-income households still face housing affordability challenges.
Median household income
The midpoint of all household incomes in a defined geographic area.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 5
Median family income (MFI)
The midpoint of all family household incomes in a geographic area. This calculation excludes non-family
households, such as people living alone. The Census publishes estimates at various geographic scales.
Very low-income household
A household with a total income below 50% AMI for its geographic area.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 6
Executive summary
Background
Housing affordability is an urgent challenge in Washington. In many areas, market housing costs are
unaffordable for low- and moderate-income households, resulting in high rates of housing cost burden,
housing insecurity and homelessness.1 Washington has a system of federal, state and local programs to
support the production and availability of affordable housing. As of 2023, there were an estimated 155,214
subsidized affordable housing units in Washington, about 5% of the total statewide housing stock.2 However,
the need for affordable housing in Washington is far greater than the available resources. One way
policymakers prioritize available resources is by limiting access to households that meet income eligibility
standards. These income limits determine which households are eligible to receive assistance. For many
programs, the income limits also determine the maximum allowable rent that can be charged to eligible
households.
In Washington, most income limits are based on Area Median Income (AMI), which refers to the U.S.
Department of Housing and Urban Development’s (HUD) annual estimate of Median Family Income (MFI) for
counties and metropolitan areas.
Because incomes and housing market conditions vary considerably across the state, HUD's income limits are
not always effective in identifying households with the greatest need for assistance. In some areas, there may
be significant gaps between the income level eligible for housing assistance and the income level needed to
afford market-rate housing. In other areas, income limits may be set so low that households working
minimum-wage jobs do not qualify for assistance. These outcomes create challenges for statewide efforts to
address local housing needs.
Legislative directive
In 2024, the Washington State Legislature included a proviso in its operating budget (Chapter 376, Laws of
2024 sec. 127§140) directing the Department of Commerce (Commerce) to conduct a study to evaluate the
impacts of current and alternative methods for calculating AMI in Washington. This report satisfies the
requirements of the proviso:
(140) $250,000 of the general fund-state appropriation for fiscal year 2025 is provided solely for the department to
evaluate alternative methods for calculating average median household income. The department must include in its
evaluation the feasibility of using median household income data by state legislative district as published by the
United States census bureau. The department must submit a report of recommendations to the appropriate
committees of the legislature by June 30, 2025.
About this report
Commerce contracted with BERK Consulting (BERK) in partnership with Novogradac. Advisors representing
several statewide and local housing assistance programs guided the work, which was also informed by
engagement with an advisory committee. The project team interviewed 27 subject matter experts and
surveyed more than 260 people representing all parts of the affordable housing system, including program
managers, developers, service providers, housing managers, and people who have experienced housing
insecurity. The insights gained through this engagement are integrated throughout this report, including the
1 See in particular, The Affordable Housing Advisory Board (AHAB) 2023-2028 Affordable Housing Advisory Plan.
2 Sources: Washington Center for Real Estate Research, 2024; Washington State Office of Financial Management, 2024.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 7
selection of alternatives and the evaluation approach. The team also gathered perspectives through a survey
open to the public.3
Because the scope and timeline of this project did not allow for direct engagement with all 29 federally
recognized tribes in Washington, the study did not address the specific impacts of changing the AMI standard
on tribal communities in this report. Due to the varied nature of tribal communities, each with distinct
economic conditions, housing availability, geographic contexts, and historical inequities, we anticipate that any
changes to the AMI standard would vary across tribes. This mirrors the broader pattern observed across
Washington, where the effects of AMI adjustments differ significantly based on local conditions.
Impacts of AMI on affordable housing in Washington
AMI varies significantly across different parts of Washington, as do income limits and rents for affordable
housing and housing assistance programs, which are typically calculated as a percentage of AMI. Affordable
housing practitioners often refer to them with terms such as "50% AMI" or "80% AMI." Income limits are also
adjusted by household size, since HUD MFI represents a four-person household. Exhibit 1 describes a 60% AMI
income limit by HUD area (county or metropolitan area) for 2024.4
Exhibit 1. 60% AMI income limit for a 4-person household by HUD area, 2024
Area Na me 60% AMI inc ome li mit for a 4 -p erson household by HUD area, 2024
Adams Cou nty, WA $54,00 0
Bellingham, WA MSA $63,35 0
Bremerton -Sil verdale, WA MSA $71,80 0
Clallam Cou nty, WA $55,10 0
Columbia County, WA $55,10 0
Ferry County, WA $54,00 0
Garfield Coun ty, WA $54,00 0
Grant Coun ty, WA $54,00 0
Grays Harbor County, WA $54,00 0
Island County, WA $61,20 0
Jefferson Coun ty, WA $54,00 0
Kennewick -Richla nd, WA MSA $59,95 0
Kittitas County, WA $59,40 0
Klickitat Coun ty, WA $54,00 0
Lewis County, WA $54,00 0
Lewiston, ID-W A MSA $50,60 0
Lincoln County, WA $54,00 0
Longview, WA MSA $54,00 0
Mason County, WA $55,10 0
Mount Vernon -Anacortes, WA MSA $60,10 0
Okanogan Coun ty, WA $54,00 0
Olympia-Tu mwa ter, WA MSA $67,60 0
Pacific Coun ty, WA $54,00 0
Pend Oreille Coun ty, WA $54,00 0
Portland -Va ncouver -Hillsboro, OR-W A MSA $70,80 0
San Juan Co unty, WA $60,90 0
Seattle -Bellevue WA HUD Metro FMR Area $90,40 0
Spokane, WA HUD Metro FMR Area $58,75 0
Steve ns County, WA HUD Metro FMR Area $54,00 0
Tacoma, WA HUD Metro FMR Area $69,50 0
Wahkiakum County, WA $54,00 0
Walla Walla, WA MSA $54,10 0
Wenatchee, WA MSA $55,60 0
Whitman Cou nty, WA $55,75 0
Yakima, WA MSA $54,00 0
Sources: HUD, 2024; BERK, 2025.
3 This engagement activity is detailed in Appendix A. Engagement summary report.
4 HUD released new 2025 AMI income limits following the completion of the analysis for this study. Numbers for 2025 are available in
Appendix D. HUD MFI and income limits by area, 2025
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 8
The impact of AMI also varies by affected group. Exhibit 2 summarizes these impacts when AMI is relatively
high or relatively low. For example, when AMI high-income limits are also high, more people seeking housing
assistance are eligible. It also allows for higher rents in affordable housing buildings. This increases housing
costs for many residents, increasing housing cost burdens. On the other hand, developers are more likely to
build new affordable housing because the higher rents help pay for construction and operating costs.
Exhibit 2. Summary of AMI impacts by affected group
Affected group Impacts in areas where AMI is relatively high Impacts in areas where AMI is relatively low
People seeking Income limits are higher, making more households Income limits are lower, which can result in fewer
housing assistance eligible for some housing assistance programs. households eligible for the housing assistance program.
Residents of Higher maximum rents can result in higher housing Lower maximum rents can result in relatively lower
income-qualified costs for residents who do not have vouchers to housing costs for residents without vouchers to support
affordable housing support rental payments. rental payments.
Higher maximum rents increase the financial Lower maximum rents decrease the financial feasibility
Developers of new
feasibility for new development. This makes of new development. Projects are less likely to be built
affordable housing
projects more likely to be built. without additional funding to subsidize production.
Higher maximum rents could increase potential
Lower maximum rents decrease potential revenue and
Operators of revenue and help cover operating costs. However,
make it more difficult to cover operating costs and
affordable housing this is limited by federal requirements and
sustain operations.
competition with market-rate units.
Sources: BERK, 2025; Novogradac, 2025.
Alternative AMI methods evaluated
This study evaluates six alternative methods for calculating AMI and compares them to the current method,
HUD MFI. These are listed in Exhibit 3.
Exhibit 3. Alternative AMI methods evaluated in this report
AMI alternative Geographic area Description
Metro Statistical
HUD Median Family
Area, HUD Metro This is the current AMI used for most housing assistance programs.
Income (MFI)
FMR Area,* County
State Legislative State Legislative
Estimates MFI for state legislative districts.
District MFI District
Estimates MFI by county (rather than MSA and HMFA). We evaluated two options for
County MFI (A & B calculating income limits. Option A increases limits in counties with high housing costs.
County
Options) Option B adjusts HUD limits upwards or downwards based on a comparison of county
MFI to HUD area MFI.
Estimates MFI by city. We evaluated two options for calculating income limits. Option A
City MFI (A & B
City increases limits in cities with high housing costs. Option B adjusts HUD limits upwards or
Options)
downwards based on a comparison of city MFI to HUD area MFI.
County Median Estimates the median income of all renter households (instead of family households) by
County
Renter county.
Source: BERK, 2025
* See the “HUD's method for calculating AMI” section for definitions.
Exhibit 4 presents a map comparing HUD's 2024 60% AMI income limit to 60% AMI based on the State
Legislative District MFI alternative to illustrate the variety of impacts an alternative AMI can have.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 9
Exhibit 4. Comparison of State Legislative District MFI alternative to HUD MFI (60%
AMI for 2024)
Legislative District County State legislative district MFI co mpare d to HU D MF I (60% AMI for 2024 )
State Legislative District 1 Snoho mish $10,95 0
State Legislative District 1 King $10,95 0
State Legislative District 2 Pierce -$1,7 50
State Legislative District 2 Thurston $150
State Legislative District 3 Spokane -$3,0
State Legislative District 4 Spokane -$3,1 50
State Legislative District 5 King $13,05
State Legislative District 6 Spokane -$4,1 50
State Legislative District 7 Okanogan $0
State Legislative District 7 Spokane -$4,7 50
State Legislative District 7 Steve ns $0
State Legislative District 7 Pend Oreille $0
State Legislative District 7 Ferry $0
State Legislative District 7 Douglas -$1,6 00
State Legislative District 7 Grant $0
State Legislative District 8 Benton $9,250
State Legislative District 8 Franklin $9,250
State Legislative District 9 Columbia $5,700
State Legislative District 9 Spokane $2,050
State Legislative District 9 Asotin $10,20
State Legislative District 9 Garfield $6,800
State Legislative District 9 Adams $6,800
State Legislative District 9 Lincoln $6,800
State Legislative District 9 Whitman $5,050
State Legislative District 9 Franklin $850
State Legislative District 10 Snoho mish -$25, 300
State Legislative District 10 Island $3,900
State Legislative District 10 Skagit $5,000
State Legislative District 11 King -$20, 850
State Legislative District 12 Snoho mish -$26, 000
State Legislative District 12 Chelan $8,800
State Legislative District 12 Douglas $8,800
State Legislative District 12 King -$26, 000
State Legislative District 13 Kittitas -$5,4
State Legislative District 13 Yakima $0
State Legislative District 13 Grant $0
State Legislative District 14 Yakima $0
State Legislative District 14 Klickitat $0
State Legislative District 15 Yakima $0
State Legislative District 15 Benton -$5,9 50
State Legislative District 15 Grant $0
State Legislative District 15 Adams $0
State Legislative District 15 Franklin -$5,9 50
State Legislative District 16 Benton -$5,0 50
State Legislative District 16 Walla Walla $800
State Legislative District 16 Franklin -$5,0
State Legislative District 17 Clark $2,150
State Legislative District 17 Skamania $2,150
State Legislative District 18 Clark -$1,6 00
State Legislative District 19 Wahkiakum $0
State Legislative District 19 Lewis $0
State Legislative District 19 Pacific $0
State Legislative District 19 Grays Harbor $0
State Legislative District 19 Cowlitz $0
State Legislative District 19 Thurston -$13, 600
State Legislative District 20 Lewis $6,700
State Legislative District 20 Cowlitz $6,700
State Legislative District 20 Clark -$10, 100
State Legislative District 20 Thurston -$6,9
State Legislative District 21 Snoho mish -$12, 900
State Legislative District 22 Thurston $200
State Legislative District 23 Kitsap $1,750
State Legislative District 24 Jefferson $0
State Legislative District 24 Clallam -$1,1 00
State Legislative District 24 Grays Harbor $0
State Legislative District 25 Pierce $1,300
State Legislative District 26 Kitsap $250
State Legislative District 26 Pierce $2,550
State Legislative District 27 Pierce -$200
State Legislative District 28 Pierce -$12, 750
State Legislative District 29 Pierce -$15, 500
State Legislative District 30 King -$30, 200
State Legislative District 31 King -$9,3 50
State Legislative District 31 Pierce $11,55 0
State Legislative District 32 Snoho mish -$14, 150
State Legislative District 32 King -$14, 150
State Legislative District 33 King -$30, 700
State Legislative District 34 King -$3,7 50
State Legislative District 35 Kitsap -$4,3 00
State Legislative District 35 Mason $12,40
State Legislative District 35 Thurston -$100
State Legislative District 36 King $40,05
State Legislative District 37 King -$10, 250
State Legislative District 38 Snoho mish -$27, 000
State Legislative District 39 Snoho mish -$19, 900
State Legislative District 39 Skagit $10,40
State Legislative District 40 Whatcom $2,700
State Legislative District 40 San Juan $5,150
State Legislative District 40 Skagit $5,950
State Legislative District 41 King $44,65
State Legislative District 42 Whatcom -$5,2 50
State Legislative District 43 King $42,70
State Legislative District 44 Snoho mish $6,800
State Legislative District 45 King $31,30
State Legislative District 46 King 10
State Legislative District 47 King -$18, 500
State Legislative District 48 King $25,65 0
State Legislative District 49 Clark -$16, 000
Sources: HUD, 2024; BERK, 2024.
Summary of key findings and recommendations
Our evaluation considers the feasibility of implementing each AMI alternative method and an analysis of how
these impacts may vary across different parts of Washington.
Summary of key findings:
No net increase in housing assistance: Changing AMI calculation methods would not result in more
households receiving assistance. Instead, more households would compete for the same resources
due to the programs' funding and capacity limits.
Limits on applying alternative methods: If Washington adopted an alternative AMI, it would only apply
to state and local programs. Any programs that distribute federal funds or tax credits must still comply
with federal requirements and cannot adopt an alternative AMI calculation if it is higher than HUD MFI.
Mixed impacts and equity trade-offs: Most alternatives would raise AMI in some areas and lower it in
others, potentially benefiting some households needing assistance while harming others, depending on
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 10
location. Some households would gain eligibility under alternatives, but others, especially under the
County Median Renter method, would lose eligibility (nearly 250,000 households statewide).
No guaranteed benefits for current affordable housing residents: Affordable housing properties
already built or under construction are typically governed by contractual agreements that are not
affected by future program changes. Therefore, current residents would not necessarily experience the
potential benefits of a change to AMI.
Housing production risks: Alternative methods could have significant, unintended consequences for
future affordable housing production, including more complicated funding systems due to different
federal and state requirements and increased funding gaps due to lower income limits and rents.
These effects might dissuade developers and investors from developing affordable housing.
Summary of recommendations:
Do not adopt a statewide alternative AMI: Risks outweigh benefits and could disrupt housing
production without significantly improving access.
Tailor income limits locally: Allow flexible income limits based on local incomes and housing market
conditions (e.g., Commerce's HTF already does this in rural areas).
Lower rent burden via adjusted rent limits: Consider basing rents on lower AMI levels or a percentage
of local Fair Market Rent (FMR).
Revise income calculations: Wherever possible, state programs should allow deductions for major
expenses such as dependents, childcare, medical expenses, or disability assistance.
The complete evaluation of these alternative AMI methods is included in this report, which is organized into
five sections:
1. What is AMI?
2. Washington programs with AMI-based income limits
3. Concerns about HUD's AMI and related income limits
4. Evaluation of alternative AMI methods
5. Policy considerations and recommendations
More detailed information can be found in the four technical appendices.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 11
What is AMI?
AMI stands for “Area Median Income.” This general term refers to the median (or mid-point) of all household
incomes within a geographic area. However, the term is widely used to refer specifically to the HUD's Median
Family Income (MFI) estimate. This measure is calculated by HUD annually for individual counties and multi-
county metropolitan areas. Unless indicated otherwise, references to "AMI" in this report refer to HUD MFI.
Common uses of AMI
There are two primary uses of AMI in Washington. First, it is used to determine household eligibility for housing
assistance. Second, it is used to determine the maximum allowable rent for an affordable housing unit.
Determining eligibility for housing assistance
Many affordable housing programs use income limits based on AMI to determine if a household qualifies for
housing assistance. To determine eligibility, the household’s income is typically compared to a published
income limit derived from AMI. HUD publishes several income limits expressed as a percentage of AMI, such
as 30% AMI, 50% AMI, and 80% AMI. These income limits are adjusted by household size to reflect that it takes
more income to afford housing suitable for a large family than for a single adult residence. Affordable housing
programs can reference one or more income limits. Some programs use a lower income limit (such as 30%
AMI) to prioritize support for extremely low-income households. Another program may use somewhat higher
income limits (such as 120% AMI) to target assistance for moderate-income households. In this way, HUD's
system of income limits provides flexibility for programs to address the needs of different kinds of households
that are not well served by the market.
Determining rent for affordable housing units
AMI is also used to determine the maximum allowable rents for affordable housing units, which typically
correspond to income limits. HUD's rent limits vary by unit size based on assumptions about the number of
household members per bedroom. For instance, HUD bases the maximum allowable rent for a 2-bedroom
apartment on the income of a 3-person household.5
Exhibit 5 provides an example for Benton County. In 2024, AMI was $99,900, and 60% of AMI was $59,940.
HUD applies this limit to a four-person household and adjusts it for other household sizes. The 60% AMI limit
for a three-person household in 2024 was $54,000, or $4,500 monthly. HUD then calculated the maximum
allowable monthly rent (including utilities) for a 2-bedroom unit to be no more than 30% of the income of a 3-
person household. In this case, 30% of the monthly income for a 60% AMI household ($4,500) is $1,350.
5 See Income and Rent Limits for All Tax Credit and Bond Financed Properties (WSHFC, 2024) for HUD’s rent limits by income level and
unit size for tax credit and bond-financed affordable housing properties.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 12
Exhibit 5. 60% AMI rent limits for a 2-bedroom unit in Benton County, 2024
Note: HUD income limits are rounded to the nearest $50. See FY 2024 VLI Income Limits Calculation
Source: HUD, 2024. BERK, 2025.
HUD's method for calculating AMI
This section describes how HUD calculates AMI. It is organized into three parts. First, we describe the
geographic areas that HUD uses to estimate AMI. Next, we describe the source data. Finally, we describe
adjustments used to account for inflation.
Geographic areas used for calculating AMI
While HUD publishes AMI estimates for each county in Washington, the geographic area used to calculate
those AMI values varies. HUD uses three different area types for calculating AMI, which are defined below.
Exhibit 6 shows the geographic boundaries used for all HUD AMI calculations in Washington.
Metropolitan Statistical Area (MSA)
These areas are defined by the U.S. Census Bureau (Census). They include a core city or population center and
adjacent communities. MSA boundaries are based on county boundaries. An MSA (shown in orange in Exhibit
6) can be composed of a single or multiple combined counties. In some cases, MSAs cross state boundaries,
as is the case for the Portland-Vancouver-Hillsboro, OR-WA MSA.
HUD Metropolitan Fair Market Rent Areas (HMFA)
HUD divides some MSAs into smaller areas called HMFAs. For example, Seattle-Tacoma-Bellevue, WA, is a
single MSA; however, HUD divides it into two HMFAs: Seattle-Bellevue, WA HMFA and Tacoma, WA HMFA. The
HUD HMFA areas are shown in purple in Exhibit 6.
Non-metropolitan counties
These are counties that are not included in an MSA. Typically, these are counties that do not contain a large
city. Washington has 20 non-metropolitan counties, shown in grey in Exhibit 6.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 13
Exhibit 6. MSAs, HMFAs, and non-metropolitan counties used for AMI calculation
Area Na me Type
Adams Cou nty, WA Non-Me tropoli tan Coun ty
Bellingham, WA MSA Metropolitan Statistical Area
Bremerton -Sil verdale, WA MSA Metropolitan Statistical Area
Clallam Cou nty, WA Non-Me tropoli tan Coun ty
Columbia County, WA Non-Me tropoli tan Coun ty
Ferry County, WA Non-Me tropoli tan Coun ty
Garfield Coun ty, WA Non-Me tropoli tan Coun ty
Grant Coun ty, WA Non-Me tropoli tan Coun ty
Grays Harbor County, WA Non-Me tropoli tan Coun ty
Island County, WA Non-Me tropoli tan Coun ty
Jefferson Coun ty, WA Non-Me tropoli tan Coun ty
Kennewick -Richla nd, WA MSA Metropolitan Statistical Area
Kittitas County, WA Non-Me tropoli tan Coun ty
Klickitat Coun ty, WA Non-Me tropoli tan Coun ty
Lewis County, WA Non-Me tropoli tan Coun ty
Lewiston, ID-W A MSA Metropolitan Statistical Area
Lincoln County, WA Non-Me tropoli tan Coun ty
Longview, WA MSA Metropolitan Statistical Area
Mason County, WA Non-Me tropoli tan Coun ty
Mount Vernon -Anacortes, WA MSA Metropolitan Statistical Area
Okanogan Coun ty, WA Non-Me tropoli tan Coun ty
Olympia-Tu mwa ter, WA MSA Metropolitan Statistical Area
Pacific Coun ty, WA Non-Me tropoli tan Coun ty
Pend Oreille Coun ty, WA Non-Me tropoli tan Coun ty
Portland -Va ncouver -Hillsboro, OR-W A MSA Metropolitan Statistical Area
San Juan Co unty, WA Non-Me tropoli tan Coun ty
Seattle -Bellevue , WA HUD Metro FMR Area HUD Metropoli tan Fair Market Rent Area
Spokane, WA HUD Metro FMR Area HUD Metropoli tan Fair Market Rent Area
Steve ns County, WA HUD Metro FMR Area HUD Metropoli tan Fair Market Rent Area
Tacoma, WA HUD Metro FMR Area HUD Metropoli tan Fair Market Rent Area
Wahkiakum County, WA Non-Me tropoli tan Coun ty
Walla Walla, WA MSA Metropolitan Statistical Area
Wenatchee, WA MSA Metropolitan Statistical Area
Whitman Cou nty, WA Non-Me tropoli tan Coun ty
Yakima, WA MSA Metropolitan Statistical Area
Sources: HUD, 2025; BERK, 2025.
AMI source data
HUD's calculation of AMI begins with an estimate of median family income from the Census American
Community Survey (ACS). To understand what these estimates represent, it is essential to understand three
key definitions.
Median
This is a statistical term for the midpoint of a series of numbers, such as household incomes. Median is
different from average. While a few extremely high-income households can skew the average income in an
area, the median household income cannot. Half of all households have an income higher than the median,
and half of all households have an income lower than the median.
Family household
The Census defines a family household as a group of people living together who are related by birth, marriage,
or adoption. This definition excludes people living alone, unmarried couples with no children, and unrelated
people living together.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 14
Family income
According to the Census, family income includes “money income received on a regular basis […] before
payments for personal income taxes, Social Security, union dues, Medicare deductions, etc.,” received in the
past 12 months.6
Median family income is an estimate of the median income of all family households in a geographic area.
Households that don't fit the definition of a family (e.g., roommates, housemates) are excluded from the
calculations.
Adjusting ACS median family income to account for inflation
There is a lag between when American Community Survey (ACS) census survey data is collected and when
new estimates are released publicly. The latest available ACS estimates of median family income tend to be
about two years old. However, incomes increase over time in most areas, like inflation. So, HUD uses a method
to adjust median family income estimates to the current year at the same rate as inflation, using the Consumer
Price Index (CPI)7Economists use this measure to track the pace of inflation over time. Exhibit 7 shows HUD's
formula for adjusting the 2022 ACS median family income to the 2024 HUD MFI using CPI.8
Exhibit 7. Basic formula for calculating 2024 AMI
2024 𝐶𝑃𝐼
2022 ACS Median Family Income × ( ) = 2024 AMI (HUD MFI)
2022 𝐶𝑃𝐼
Income limits associated with AMI
AMI is not typically used as an income limit to determine eligibility for housing assistance. Instead, HUD
calculates and publishes several income limits derived from AMI. The names often used for these income
limits, such as 50% AMI or 30% AMI, imply that they are a simple calculation based on AMI. However, the
names are misleading because HUD's calculations can include several adjustments. For example, if AMI
increases by more than 10% from the previous year, HUD will increase income limits by no more than 10%.
These adjustments limit the impact of changes to AMI on program eligibility and affordable housing rents.
Exhibit 8 summarizes the adjustments that HUD uses when calculating Very Low Income (VLI), a widely used
income limit, also known as 50% AMI. The exhibit shows that in 2024, VLI equaled 50% AMI in only six counties
in Washington. For the remaining counties, another adjustment determined VLI. Exhibit 9 presents the
adjustments that determined VLI in each area of Washington in 2024.
6 Family income does not include irregular income, such as gifts or capital gains, and noncash benefits, such as food stamps, health
benefits, subsidized housing, and goods produced and consumed on a farm (U.S. Census Bureau, 2021).
7 The Consumer Price Index (CPI) is a measure of the average change over time in the prices paid by urban consumers for a market
basket of consumer goods and services. (U.S. Bureau of Labor Statistics 2025)
8 See Appendix B. Literature review for a more details discussion of inflation adjustment.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 15
Exhibit 8. HUD Very Low Income (VLI) limit adjustments and Washington counties
affected, 2024
# of counties where VLI is
Adjustment Description
determined by this adjustment
50% of AMI (HUD By default, VLI is calculated as 50% of AMI (HUD MFI). However,
6
MFI) additional adjustments may subsequently change this calculation.
This adjustment places a floor that VLI cannot fall below. It impacts
State non-metro
areas where VLI is less than 50% of the state's MFI of all non- 16
median
metropolitan counties. In 2024, this was $45,000 for Washington.
In areas with high housing costs relative to area incomes, HUD
High housing cost increases VLI upward so that a higher percentage of the population 3
can qualify for Section 8 assistance.
Annual decrease This adjustment places a floor to prevent VLI from decreasing to less
0
floor than 95% of the previous year’s limit.
HUD caps VLI so it cannot rise more than 10% from the previous
Annual increase cap 14
year's limit.
Source: HUD, 2024; Novogradac, 2024; BERK, 2025.
Exhibit 9. Calculation adjustment that determines VLI by HUD area in 2024
Area Na me Calcul ation adj ustment that determin es VLI by HU D are a i n 20 24
Adams Cou nty, WA State N on-Me tro Median
Bellingham, WA MSA 10% Ceiling
Bremerton -Sil verdale, WA MSA Equal to 50% AM I
Clallam Cou nty, WA 10% Ceiling
Columbia County, WA 10% Ceiling
Ferry County, WA State N on-Me tro Median
Garfield Coun ty, WA State N on-Me tro Median
Grant Coun ty, WA State N on-Me tro Median
Grays Harbor County, WA State N on-Me tro Median
Island County, WA Equal to 50% AM I
Jefferson Coun ty, WA State N on-Me tro Median
Kennewick -Richla nd, WA MSA Equal to 50% AM I
Kittitas County, WA 10% Ceiling
Klickitat Coun ty, WA State N on-Me tro Median
Lewis County, WA State N on-Me tro Median
Lewiston, ID-W A MSA Equal to 50% AM I
Lincoln County, WA State N on-Me tro Median
Longview, WA MSA State N on-Me tro Median
Mason County, WA 10% Ceiling
Mount Vernon -Anacortes, WA MSA 10% Ceiling
Okanogan Coun ty, WA State N on-Me tro Median
Olympia-Tu mwa ter, WA MSA 10% Ceiling
Pacific Coun ty, WA State N on-Me tro Median
Pend Oreille Coun ty, WA State N on-Me tro Median
Portland -Va ncouver -Hillsboro, OR-W A MSA High Housing Cost
San Juan Co unty, WA 10% Ceiling
Seattle -Bellevue , WA HUD Metro FMR Area 10% Ceiling
Spokane, WA HUD Metro FMR Area 10% Ceiling
Steve ns County, WA HUD Metro FMR Area State N on-Me tro Median
Tacoma, WA HUD Metro FMR Area High Housing Cost
Wahkiakum County, WA State N on-Me tro Median
Walla Walla, WA MSA Equal to 50% AM I
Wenatchee, WA MSA 10% Ceiling
Whitman Cou nty, WA 10% Ceiling
Yakima, WA MSA State N on-Me tro Median
Sources: HUD, 2024; Novogradac, 2024; BERK, 2025.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 16
Adjusting income limits for household size
HUD uses the methodology in Exhibit 7 to calculate VLI for a four-person household. HUD also publishes
income limits for other household sizes. For example, the income threshold for determining if a household
qualifies as VLI is higher for a five-person household than for a two-person household. This is based on the
idea that more income is typically required to support more household members. Exhibit 10 presents the
household size adjustment factors for HUD income limits. For each person fewer than four, the AMI is reduced
by 10%, down to 70% of the four-person household base for a single-person household. For each person
beyond four, the AMI increases by 8%. For example, a five-person household is 108% of the four-person base,
and a six-person household is 116%.
Exhibit 10. Household size adjustment factors for HUD income limits
Note: For each additional person over eight, the four-person income limit is multiplied by an additional 8 percent.
Source: HUD, 2024.
Adjusting income limits for different percentages of AMI
VLI is only one income limit published by HUD. Most other income limits published by HUD are derived directly
from VLI, rather than AMI. For example, HUD calculates 60% AMI by multiplying VLI by 120%. In other words,
60% AMI is not calculated as simply 60% of HUD MFI, despite its name. Exhibit 11 presents a map of HUD's
60% AMI income limits for a four-person household in every HUD area across Washington. It shows a wide
range of values, from a high of $90,400 in the Seattle-Bellevue, WA HUD Metro FMR Area (King and Snohomish
counties) to a low of $50,600 in Asotin County.9
HUD calculates other percentages of AMI income limits based on VLI similarly. HUD applies additional
adjustments for some income limits, such as Extremely Low Income (30% AMI) and Low Income (80% AMI).
See Appendix C. Alternative AMI and impact analysis methodologies for more details.
9 Asotin County (shown on the map in the bottom right most corner) is part of an MSA shared with Idaho and therefore not subject to
Washington's state non-metro median adjustment. Many counties in Washington have a 60% AMI income limit of $54,000 due to the
state non-metro median adjustment to VLI.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 17
Exhibit 11. 60% AMI income limit for a 4-person household by HUD area, 2024
Area Na me 60% AMI inc ome li mit for a 4 -p erson househo ld by HUD area, 2024
Adams Cou nty, WA $54,00 0
Bellingham, WA MSA $63,35 0
Bremerton -Sil verdale, WA MSA $71,80 0
Clallam Cou nty, WA $55,10 0
Columbia County, WA $55,10 0
Ferry County, WA $54,00 0
Garfield Coun ty, WA $54,00 0
Grant Coun ty, WA $54,00 0
Grays Harbor County, WA $54,00 0
Island County, WA $61,20 0
Jefferson Coun ty, WA $54,00 0
Kennewick -Richla nd, WA MSA $59,95 0
Kittitas County, WA $59,40 0
Klickitat Coun ty, WA $54,00 0
Lewis County, WA $54,00 0
Lewiston, ID-W A MSA $50,60 0
Lincoln County, WA $54,00 0
Longview, WA MSA $54,00 0
Mason County, WA $55,10 0
Mount Vernon -Anacortes, WA MSA $60,10 0
Okanogan Coun ty, WA $54,00 0
Olympia-Tu mwa ter, WA MSA $67,60 0
Pacific Coun ty, WA $54,00 0
Pend Oreille Coun ty, WA $54,00 0
Portland -Va ncouver -Hillsboro, OR-W A MSA $70,80 0
San Juan Co unty, WA $60,90 0
Seattle -Bellevue , WA HUD Metro FMR Area $90,40 0
Spokane, WA HUD Metro FMR Area $58,75 0
Steve ns County, WA HUD Metro FMR Area $54,00 0
Tacoma, WA HUD Metro FMR Area $69,50 0
Wahkiakum County, WA $54,00 0
Walla Walla, WA MSA $54,10 0
Wenatchee, WA MSA $55,60 0
Whitman Cou nty, WA $55,75 0
Yakima, WA MSA $54,00 0
Sources: HUD, 2024; BERK, 2025.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 18
Washington programs with AMI-based income limits
Our team identified dozens of affordable housing grant or loan programs in Washington. Some administer
federal funding while others administer state or local funding. In all cases, the income limits used to determine
program eligibility or rent costs are derived from AMI. However, these programs use a wide range of income
limits from 30% AMI up to 115% AMI or more. In this way, each prioritizes assistance for different kinds of
households with different needs.
A 2018 report by HUD identified at least two dozen different federal programs (managed by HUD, the Federal
Reserve, USDA, Treasury, Federal Deposit Insurance Corporation, and Federal Housing Finance Agency) that
use AMI-based income limits. Exhibit 12 lists the programs that are most widely used in Washington. Although
these are federal programs, many are administered by state or local agencies. For example, HUD's HOME and
National Housing Trust Fund (HTF) programs are administered by Commerce, and the Low-Income Housing
Tax Credits (LIHTC) and tax-exempt bond programs are administered by the Washington State Housing
Finance Commission (WSHFC).
For each program in Exhibit 12, federal laws or guidelines determine eligibility income limits for households to
receive support. However, the state or local agency administering the program is often permitted to add its
own income limits as long as they set them lower than the federal requirements. For example, in a LIHTC
project, federal law may require the housing to be affordable at 60% AMI. However, as part of its process for
awarding these tax credits, WSHFC prioritizes projects that agree to set aside a portion of their units to be
affordable to households with incomes less than 30% AMI. To address Washington's diverse local market
conditions, WSHFC has different income set-aside priorities in the application process for King County, other
metropolitan and non-metropolitan counties.
Exhibit 12. Commonly used federal housing programs with AMI-based income limits
Program Eligibility income limit
Difficult Development Areas designation 60% AMI
HOME Investment Partnership Program 60% and 65% AMI
National Housing Trust Fund (NHTF) 30% AMI*
Indian Housing 30%*, 50%, and 80% AMI
Low-income housing tax credits (LIHTC) Between 20% and 80% AMI*
Low-Income Housing Preservation and Resident Homeownership Act of 1990 80-95% AMI
National Homeownership Trust Act of 1990 95% AMI or 115% AMI for high-cost areas
Public Housing 30%*, 50%, and 80% AMI
Section 202 & 811 Supportive Housing Programs 50% and 80% AMI
Section 236 Preservation Program 80% AMI
Housing Choice Voucher Program 30%*, 50%, and 80% AMI
Tax-Exempt Bonds 50% AMI*
USDA Rural Development 50% and 80% AMI
Note: Income limits marked with an * include additional adjustments.
Source: Assessment of Small Area Median Family Income Estimates (HUD, 2018).
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 19
Exhibit 13 lists several housing programs run by state and local jurisdictions, and the income limit standards
used. As with the federal programs in Exhibit 12, all of these programs use income standards derived from
AMI. They also use HUD's HOME rent limits, which are based on AMI and consistent with eligibility income
limits.10
Exhibit 13. Examples of state and local housing programs that use AMI-based income
limits
Commerce Housing Trust Fund: No higher than 80% AMI, priority for 30% AMI.
ARCH Housing Trust Fund: 30-80% AMI
ARCH Land Use and MFTE incentives: 30-80% AMI
Seattle Office of Housing Funded Rental Housing: 30-80% AMI
Seattle Office of Housing's Incentive Zoning, MFTE (Programs 3-5), Mandatory Housing Affordability: 30-80%
AMI. See Seattle Office of Housing's income and rent limits.
Tacoma MFTE program: 70% AMI
Vancouver Affordable Housing Fund: 50% AMI and 80% AMI
Sources: Novogradac, 2025; BERK, 2025.
10 One exception is the City of Seattle Office of Housing, which limits rent increases based on the annual increase in the Rent of Primary
Residence component of the Consumer Price Index for All Urban Consumers for Seattle-Tacoma-Bellevue. See FY 2024 Income and
Rent Limits. This can result in maximum rents that differ from published HUD rent limits based on AMI.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 20
Concerns about HUD's AMI and related income limits
Survey and interview respondents expressed many concerns about AMI-based income limits. Their concerns
varied considerably. This is because AMI impacts different people in different ways. Exhibit 14 summarizes
both positive and negative impacts of AMI by affected group. It differentiates impacts in areas where AMI is
relatively high, such as the Seattle-Bellevue HMFA, and areas where AMI is relatively low, such as most non-
metropolitan (i.e., predominantly rural) counties. For example, when AMI is high, income limits are also high.
This makes more people seeking housing assistance eligible for housing assistance programs. It also allows
for higher rents in affordable housing buildings. This increases housing costs for many residents, which can
result in an increased housing cost burden. On the other hand, developers are more likely to build new
affordable housing because the higher rents can help pay for construction and operational costs.
Exhibit 14. Summary of AMI impacts by affected group
Affected group Impacts in areas where AMI is relatively high Impacts in areas where AMI is relatively low
Income limits are lower, which can result in fewer
People seeking Income limits are higher, making more households
households eligible for the housing assistance
housing assistance eligible for some housing assistance programs.
program.
Residents of Higher maximum rents can result in higher housing Lower maximum rents can result in relatively lower
income-qualified costs for residents who do not have vouchers to housing costs for residents without vouchers to
affordable housing support rental payments. support rental payments.
Lower maximum rents decrease the financial
Higher maximum rents increase the financial
Developers of new feasibility of new developments, making projects
feasibility for new development. This makes projects
affordable housing less likely to be built without additional funding to
more likely to be built.
subsidize production.
Higher maximum rents could increase potential
Lower maximum rents decrease potential revenue
Operators of revenue and help cover operating costs. However, this
and make it more difficult to cover operating costs
affordable housing is limited by federal requirements and competition with
and sustain operations.
market-rate units.
Source: Novogradac, 2025; BERK, 2025.
In this section, we summarize major themes among the concerns expressed by respondents, including:
AMI impacts where it is feasible to build new affordable housing
In areas with low AMI, many residents who need housing support are ineligible for housing assistance
Rents based on AMI income limits result in housing cost burden
Misalignment between AMI and local incomes creates challenges to meeting housing needs
AMI can increase faster than the incomes of affordable housing residents
AMI impacts where it is feasible to build new affordable housing
Most affordable housing in Washington is constructed by private developers who use low-income housing tax
credits (LIHTC). These developers search for opportunities where projects are financially feasible.11 They
consider many factors, such as land costs, construction costs, local demand for affordable housing,
availability of local incentives, and additional funding sources. They also consider the maximum rents they can
11 Typically, an affordable housing developer is seeking a debt service coverage ratio of 115%. This means that their net income after
covering operating expenses and necessary reserves is 115% of their debt service. This allows for enough of a margin to maintain
financial sustainability and avoid defaulting on debt (Source: Novogradac, 2025).
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 21
charge based on local AMI-based rent limits and market rents. Rents determine the potential revenue for the
project following construction and, therefore, the funding available to pay for operations and debt service.12
Finding financially feasible opportunities is more challenging for affordable housing developers in areas with
lower AMIs. This is because the maximum rent allowed is lower due to the lower income limits. Additional
subsidies could help address the feasibility challenge, but there is limited availability of public funding to
support affordable housing development. As a result, AMI impacts the geographic distribution of affordable
housing production.
To illustrate the impacts of AMI on project feasibility, the following three exhibits illustrate two identical
affordable housing projects in King and Pierce counties. In this hypothetical example, both developments have
the same land and construction costs, tax credit equity, deferred developer fees, and low- or no-interest-rate
loans from local government. They also have the same mix of units by size and affordability level, including
units required to be affordable at 50% AMI. Both projects have the same operating costs. Because Pierce
County has a lower AMI than King, the rents charged in Pierce are also lower ($400 lower or 23% less). This
limits the expected income and, therefore, the amount of supportable debt the developer can take on. As a
result, the development in Pierce County would require an additional $12 million in gap financing to make the
project financially sustainable. Without that gap financing, the project would likely not move forward.13
Exhibit 15. Comparison of LIHTC-funded affordable housing developments in King
and Pierce counties
County HUD MFI (100% AMI) HUD VLI* (50% AMI)
Pierce $112,300 $57,900
King $147,400 $75,350
Exhibit 16. Allowable monthly rent amount for a 50% AMI unit
Pierce County $1,303
King County $1,696
12 Another important player in affordable housing development is the tax credit investor. These are typically banks or other institutions
that buy low-income housing tax credits from affordable housing developers, providing the developer with capital to fund construction.
These investors only reap the benefit of the tax credits if the affordable housing project fully complies with all affordability
requirements for a period of 15 years. As a result, investors closely scrutinize project plans, including the mix of units by affordability
level, to verify that compliance success is likely. Some interviewees report that many investors have a strong preference for projects
that have simple affordability requirements. Projects that have multiple income limit targets or multiple income limit standards are
viewed as having increased compliance risk. This can result in less investor interest in projects with more complicated AMI
requirements. Consequently, developers of such projects may receive less money for each credit sold.
13 Some other ways to increase the financial feasibility of this project include increasing the income limit to 60% AMI or reducing the
number of units required to be affordable at the deeper target of 50% AMI.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 22
Exhibit 17. Funding needed to support development at 50% AMI rent
Pierce County $40 $6 $15 $31 $12
King County $40 $6 $26 $31
$0 $20 $40 $60 $80 $100
Millions
Tax Credit Equity Deferred Developer Fee Supportable Debt Soft Loans (e.g. City and County Funds) Additional Gap Finanacing
* HUD VLI reflects adjustments and does not equal 50% of HUD MFI. King County is in the Seattle-Bellevue, WA HUD Metro FMR Area, and Pierce County
is in the Tacoma, WA HUD Metro FMR Area.
Sources: HUD, 2024; Novogradac, 2024; BERK, 2024.
Competition with market-rate units also impacts feasibility
There are also situations where maximum rents based on AMI are close to or even higher than market rents.14
In these cases, market-rate units may be more attractive to tenants due to the simpler and faster application
and approval process. To compete, affordable housing operators in these areas may need to reduce rents to
fill units. However, doing so reduces revenue. If revenue potential is reduced far enough due to competition, it
also decreases the likelihood of new affordable housing development.
In areas with low AMI, many residents who need housing support
are ineligible for housing assistance
In some areas where AMI is relatively low, people earning minimum wage or even social security have incomes
that are too high to qualify for some housing assistance programs, and yet, they still cannot afford market
rents. Exhibit 18 presents an example of this for Yakima County. It shows the following:
A person with the average social security income in Washington does not qualify for a 30% AMI unit in
Yakima. This severely reduces the population of eligible residents who could live in a unit with that
income limit.15
A person with a full-time minimum wage job has an income higher than both 30% and 50% AMI income
limits. They are ineligible for affordable housing supported by programs that use these limits, including
all projects funded through Washington's HTF. However, they would be eligible at 60% AMI, which is the
limit for many LIHTC properties.
14 In 2025, HUD's Fair Market Rent (an estimation of typical market rent) for a two-bedroom rental was greater than the maximum
allowed rent at 60% AMI in 19 counties across Washington. In these counties, an affordable housing provider would likely need to lower
their rents below the maximum allowed to compete with market units.
15 Due to this fact, Commerce's HTF program does not typically fund housing with income limits below 50% AMI in Yakima and much of
eastern Washington.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 23
There is a relatively small gap between the income that qualifies for a 60% AMI affordable housing unit
($37,800) and the income needed to afford a Fair Market Rent (FMR)16 studio apartment ($39,600).
People with incomes in this gap may have difficulty finding affordable housing options. In some
counties, this gap is much wider.
Exhibit 18. HUD income limits and example 1-person household incomes in Yakima
County, 2024
. 30% AMI $18,900
50% AMI (VLI) $31,500
60% AMI $37,800
Average Social Security income $22,239
Full-Time minimum wage income $33,862
Income needed to afford FMR studio apartment $39,600
$0 $10,000 $20,000 $30,000 $40,000
Sources: HUD, 2024; Social Security Administration, 2024; BERK, 2024.
Exhibit 19 shows how variation in AMI-based income limits can impact the ability of a typical low-income
household to access affordable housing. Specifically, it maps outcomes for a four-person household with two
people working minimum wage jobs17 and two dependents. It classifies each area in Washington into one of
three categories:
1. Areas where the household's income is less than 60% AMI, and, therefore, they would be eligible for
most affordable rental housing programs.
2. Areas where the household's income is greater than 60% AMI, but they can afford FMR. In these areas,
the household would likely find market-rate housing that is affordable.
3. Areas where the household's income exceeds 60% AMI, and they cannot afford FMR. In these areas,
many households may fall into a gap where they cannot afford market-rate housing and do not qualify
for most affordable housing.
16 Fair Market Rent (FMR) refers to HUD's official estimate of the 40th percentile rent for a dwelling unit within a defined area. "40th
percentile" is a statistical measure similar to median, except that 60% of all rents in the area are higher, and 40% of all rents in the area
are lower. FMR includes both the cost of shelter plus all major utilities (except phone, TV, and internet) (HUD, 2025).
17 This analysis is based on the Washington statewide minimum wage in 2024 of $16.28 per hour. Some individual cities have higher
minimum wages.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 24
Exhibit 19. Eligibility of a 4-person household with two minimum wage jobs for a 60%
AMI unit
Area Na me Eligibility of a 4-person ho usehold with two mini mu m wage jobs for a 60 % AMI unit
Adams Cou nty, WA Not eligible, but can afford market rent
Bellingham, WA MSA Not eligible and cannot afford market rent
Bremerton -Sil verdale, WA MSA Eligible for a 60% AMI unit
Clallam Cou nty, WA Not eligible and cannot afford market rent
Columbia County, WA Not eligible, but can afford market rent
Ferry County, WA Not eligible, but can afford market rent
Garfield Coun ty, WA Not eligible, but can afford market rent
Grant Coun ty, WA Not eligible, but can afford market rent
Grays Harbor County, WA Not eligible, but can afford market rent
Island County, WA Not eligible and cannot afford market rent
Jefferson Coun ty, WA Not eligible and cannot afford market rent
Kennewick -Richla nd, WA MSA Not eligible and cannot afford market rent
Kittitas County, WA Not eligible and cannot afford market rent
Klickitat Coun ty, WA Not eligible, but can afford market rent
Lewis County, WA Not eligible and cannot afford market rent
Lewiston, ID-W A MSA Not eligible, but can afford market rent
Lincoln County, WA Not eligible, but can afford market rent
Longview, WA MSA Not eligible and cannot afford market rent
Mason County, WA Not eligible and cannot afford market rent
Mount Vernon -Anacortes, WA MSA Not eligible and cannot afford market rent
Okanogan Coun ty, WA Not eligible, but can afford market rent
Olympia-Tu mwa ter, WA MSA Not eligible and cannot afford market rent
Pacific Coun ty, WA Not eligible, but can afford market rent
Pend Oreille Coun ty, WA Not eligible, but can afford market rent
Portland -Va ncouver -Hillsboro, OR-W A MSA Eligible for a 60% AMI unit
San Juan Co unty, WA Not eligible and cannot afford market rent
Seattle -Bellevue , WA HUD Metro FMR Area Eligible for a 60% AMI unit
Spokane, WA HUD Metro FMR Area Not eligible and cannot afford market rent
Steve ns County, WA HUD Metro FMR Area Not eligible, but can afford market rent
Tacoma, WA HUD Metro FMR Area Eligible for a 60% AMI unit
Wahkiakum County, WA Not eligible, but can afford market rent
Walla Walla, WA MSA Not eligible and cannot afford market rent
Wenatchee, WA MSA Not eligible and cannot afford market rent
Whitman Cou nty, WA Not eligible, but can afford market rent
Yakima, WA MSA Not eligible and cannot afford market rent
Sources: HUD, 2024; BERK, 2025. Market rent refers to the HUD Fair Market Rent for a 3-bedroom unit in 2024.
Rents based on AMI income limits can result in housing cost
burden
According to HUD, a household is considered cost-burdened if it spends more than 30% of its income on
housing costs. These households have limited money left over each month to cover essential expenses, such
as food, transportation, health care, and childcare. Currently, the method used to set income limits and rents
for most affordable housing programs in Washington results in nearly all residents of affordable housing units
being cost-burdened if they are not receiving rental assistance. The household needs an income below the
income limit to qualify for an affordable housing unit. However, the rent for that same unit is set at 30% of the
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 25
income limit.18 This results in the household paying more than 30% of their income on rent, which, by HUD's
definition, is more than the household can afford.
In some cases, households have additional rental assistance, such as HUD Housing Choice Vouchers, which
cover the difference between rent and what the household can afford (30% of household income). According
to a 2024 study by Commerce and WSHFC, about 57% of households living in rent-restricted affordable
housing units receive these kinds of rental subsidies.
Misalignment between AMI and local incomes creates challenges
to meeting housing needs
There is a great deal of income disparity in many regions of Washington. Different cities within the same
metropolitan region can have significantly different median family incomes. Because HUD calculates AMI on a
county, MSA, or HMFA basis, the income limits apply to large areas that may contain communities with very
different income levels and can obscure significant differences in income across individual communities
within the same region.
Exhibit 20 provides an example of these disparities in the Seattle-Bellevue, WA HUD Metro FMR Area. In 2024,
the regional AMI for the HMFA was $147,400. We see wide variation when HUD’s calculation method is applied
at the city level, using the same methodology but focused on smaller geographic units. For example, the AMI
for Kent would be nearly $43,000 lower than the regional AMI, reflecting the lower income levels of residents in
that community. In contrast, if calculated for the city of Seattle alone, the AMI would be approximately $41,400
higher than the regional AMI. This misalignment creates challenges, especially in lower-income cities like Kent,
where rents based on the higher regional AMI may be unaffordable for most local households.
Exhibit 20. Comparison AMI (HUD MFI) for Seattle-Bellevue, WA HMFA to City MFI,
2024
Seatle-Bellevue, WA HMFA $147,400
Seattle $188,800
Renton $128,700
Kent $104,600
Edmonds* $151,000
Carnation* $159,100
Burien* $105,900
Bellevue $188,100
Notes: Calculations by Novogradac based on 2022 Census ACS 1-year estimates and HUD’s 2024 trend factor of 1.0618. *For cities designated with an
asterisk, there was no 1-year ACS available, so the 5-year ACS was used.
Sources: Census ACS one-year estimates, 2022; Census ACS five-year estimates, 2018-2022; Novogradac, 2025; BERK, 2025.
18 Income limits are based on the actual number of residents in a unit. However, rent limits are based on the number of bedrooms in the
unit, which assumes a certain number of people per bedroom. For example, in a two-bedroom unit, the rent would be based on a three-
person household but may be occupied by a five-person household or a two-person household. Therefore, there is often a disconnect
between the rent limit and the income limit used to qualify the household. This can lead to households being over- or under-rent-
burdened based on their household size and how close their income is to the limit.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 26
AMI can increase faster than the incomes of affordable housing
residents
In some areas experiencing an influx of higher-income households, AMI can increase rapidly from year to year.
This happened in the Seattle area when technology companies were rapidly hiring high-wage workers, and high
housing costs limited who could afford to move into the area. This can also happen in rural communities when
remote workers or retirees relocate to the area. In either case, AMI increases because more households are at
the higher end of the income spectrum, skewing the median higher. However, this doesn't mean the income of
all households is rising at the same rate. Workers in low-wage jobs or people living on fixed incomes, such as
Social Security, may experience little or no increase in income. When this happens, residents of affordable
housing units start to see a greater share of their income going towards housing each year.
HUD includes an adjustment in the VLI calculation method to partially address this problem. It caps the annual
increase in VLI by the lesser of 10% or two times the change in national median income. However, 10% is
typically far more than inflation and low-wage salary increases. Therefore, the adjustment does not fully
mitigate this challenge.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 27
Evaluation of alternative AMI methods
The Legislature asked Commerce to evaluate alternative methods for measuring AMI in Washington. In this
section, we summarize the survey and interview respondents' input on potential alternative AMI methods. We
then introduce four selected alternative AMI methods for evaluation. Next, we present our evaluation of the
feasibility and impacts of implementing the alternatives.
AMI methods proposed for consideration
During our engagement process, respondents identified several issues they think could be addressed by an
alternative AMI method. Exhibit 21 summarizes the proposed ideas by theme and associated example metrics
or relevant data sources. We also summarize whether each theme is addressed in the alternatives selected for
evaluation in this study. In some cases, we found that themes identified by respondents could be more
effectively addressed by actions other than an alternative AMI method. These findings are detailed in Appendix
A. Engagement summary report.
Exhibit 21. Alternative AMI methods proposed by survey and interview respondents
Theme Addressed in this study's selected alternatives?
Use smaller geographic units to better
Yes. All four alternatives include different geographic boundaries from HUD MFI.
reflect local incomes.
Calculate AMI based on the incomes of Yes. One alternative focuses on median renter household income instead of median family
people who need housing assistance. household income.
Income limits should reflect market
Partially. Most alternatives include a high housing cost adjustment based on local market
housing affordability or the cost of
rents.
living.
Limit the annual increase and/or Partially. Some alternatives account for HUD VLI adjustments, which include caps and
decrease of AMI. floors on yearly change.
No. AMI standards don’t need to change to address this concern. Rather, it requires
Account for the number of dependents,
developing new methods for calculating an individual household’s adjusted income after
childcare costs, medical costs, etc.
deducting certain costs.
Source: BERK, 2025.
Alternative AMI methods selected for evaluation
In this study, we evaluated four alternative AMI methodologies and compared them to HUD MFI. The
alternatives are summarized in Exhibit 22, including the geographic areas for which AMI is calculated and a
brief description. Because housing assistance programs typically reference income limits derived from AMI,
we also calculate an equivalent to VLI and 60% AMI19 for all geographic areas. Appendix C. Alternative AMI and
impact analysis methodologies provides a detailed description of the calculation method for each alternative
and AMI, VLI, and 60% AMI calculations for all areas.
19 In HUD's MTSP income limit methodology, 60% AMI is calculated at simply 120% of VLI. We apply this same adjustment to calculate
an equivalent 60% AMI income limit for each alternative AMI method.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 28
Exhibit 22. Alternative AMI methods evaluated in this study
AMI alternative Geographic area Description
HUD Median This is the current AMI used for most housing assistance programs. Our evaluation
MSA, HMFA,
Family Income compares the impacts and feasibility of this AMI to the potential impacts and feasibility of
County
(MFI) alternative AMI methods listed below.
Estimates MFI for state legislative districts. We calculated MFI by state legislative district
State Legislative State Legislative
using the same data sources and method as HUD to implement it. The only adjustment
District MFI District
used for calculating income limits is the state non-metro median floor.
Estimates MFI by county (rather than MSA and HMFA). We evaluated two options for
County MFI (A & B calculating income limits. Option A increases limits in counties with high housing costs.
County
Options*) Option B adjusts HUD limits upwards or downwards based on a comparison of county MFI
to HUD area MFI.
Estimates MFI by city. We evaluated two options for calculating income limits. Option A
City MFI (A & B
City increases limits in cities with high housing costs. Option B adjusts HUD limits upwards or
Options*)
downwards based on a comparison of city MFI to HUD area MFI.
Estimates the median income of all renter households (instead of family households) by
County Median county. Because renter households are typically smaller than the average family household,
County
Renter this method includes a household size adjustment to align AMIs for comparability to other
methods.
*Option A: No ceilings and floors adjustment; Option B: Washington Center for Real Estate Research methodology.
Source: BERK, 2025.
Example 60% AMI income limits for each alternative
Exhibit 23 compares a 60% AMI calculation for a four-person household in Federal Way using each alternative
AMI method. It also shows a household's income with two workers, each earning the Washington state
minimum wage ($16.28 in 2024).
With the current HUD MFI, a four-person household with two minimum wage workers would qualify for
an affordable unit at 60% AMI.
However, the same household would exceed the income threshold under the Legislative District, City
MFI B and County Median Renter alternative AMI methods.
Exhibit 24 shows the same comparison for the city of Yakima.
Most alternatives have no change to 60% AMI.
This is because most alternatives are subject to the state non-metro median adjustment that places
a floor on how low VLI can be.
The exceptions are the City MFI B and County Median Renter alternatives.
In all alternatives, a four-person household with two minimum wage earners has an income that
exceeds 60% AMI.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 29
Exhibit 23. 60% AMI in Federal Way by AMI alternative,4-person household, 2024
$120,000
$101,750
$97,300
$100,000 $90,400 Income: 2 minimum wage
$86,650
jobs, $80,246
$80,000
$60,200 $63,000
$60,000 $55,250
$40,000
$20,000
$0
HUD MFI Legislative District County MFI - A County MFI - B City MFI - A City MFI - B County Median
MFI Renter
Sources: HUD, 2024; BERK, 2025.
Exhibit 24. 60% AMI in the City of Yakima by AMI Alternative (4-person household),
2024
$90,000 Income: 2 minimum wage
jobs, $80,246
$80,000
$70,000
$60,000 $54,000 $54,000 $54,000 $54,000 $54,000 $51,900
$50,000
$40,000
$30,050
$30,000
$20,000
$10,000
$0
HUD MFI Legislative District County MFI - A County MFI - B City MFI - A City MFI - B County Median
MFI Renter
Sources: HUD, 2024; BERK, 2025.
Impact and feasibility evaluation
If Washington adopted an alternative AMI method, many different state and local agencies would have the
option to apply that new standard in their housing assistance programs.20 The impacts of adopting an
alternative AMI would vary depending on which programs use the new standard. Rather than evaluating the
potential impact on each program, this evaluation considers general implementation challenges if a program
adopts an alternative AMI method.
20 Note some state programs, such as HTF, are currently bound by state statutes that mandate the use of HUD AMI to determine
eligibility. This could be changed by an act of the state Legislature.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 30
This analysis addresses five types of impacts and feasibility challenges that may be associated with
implementing an alternative AMI method. Exhibit 25 presents a summary of findings. We did not identify an
alternative that clearly improved the status quo.
The findings of this evaluation are much more nuanced than this summary exhibit implies. The following
sections detail these findings related to each category listed in Exhibit 25, including how these impacts vary by
geography.
Exhibit 25. Summary of potential impact and feasibility of alternatives compared to
the status quo
Legislative County MFI City MFI County
Type of impact
District MFI (A and B) (A and B) Median Renter
Data availability and reliability Minor Minor Minor Minor
Impacts on current residents of affordable housing No impact No impact No impact No impact
Program management feasibility Major Minor Major Minor
Affordable housing production and operation Major Major Major Major
Impacts on households in need of assistance Minor Minor Minor Minor
Source: Novogradac, 2025; BERK, 2025.
Data for calculating alternative AMIs is available and reliable in most
areas
With the exception of HUD MFI, all of the alternatives would require a state agency or third party to calculate
and publish tables for use by state and local housing programs. However, the calculations are not
complicated. They can be done using widely available public data from the American Community Survey (ACS)
and the Bureau of Labor Statistics. The primary consideration is the margin of error. ACS estimates of MFI are
based on a sample of households. Areas that are much smaller in population typically have a much smaller
sample of households reflected in the ACS data. As a result, the estimates for these areas also have a larger
margin of error.21 To address this issue, HUD uses two standards to evaluate whether MFI estimates from the
ACS are reliable enough for use in calculating HUD MFI:
1. The margin of error (MOE) for the ACS estimate is less than 50% of the estimate itself.
2. The ACS estimate is based on at least 100 survey cases.
To evaluate alternative AMI methods, we sought to apply the same standards for assessing data reliability.
Unfortunately, the number of survey cases for ACS estimates is not publicly available, so we only applied the
first standard (MOE) to evaluate reliability.
Our evaluation found that all areas in the State Legislative District MFI and County MFI alternatives passed
HUD's first reliability test. However, for the City MFI alternative, ten out of 212 cities had an MOE greater than
21 Margin of error (MOE) is a statistical measure used to evaluate the level of confidence that an estimate based on a sample is
accurate for the entire population. The MOEs for published ACS estimates are provided at a 90% confidence level. For example, the
2022 ACS estimate of MFI for Adams County was $47,538 with an MOE of $9,674. This means that there is a 90% chance that the
actual median family income in Adams County is between $37,864 and $57,212. The low value in this range is calculated as estimate
minus MOE. The high value is estimate plus MOE.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 31
50% of the City MFI estimate. These cities all have populations under 4,000 residents. Finally, a single county
(Wahkiakum) did not meet this reliability standard for the County Median Renter AMI alternative. Its population
has fewer than 5,000 residents.
Implementing an alternative AMI would result in significant program
management feasibility challenges
Dozens of state and local programs provide housing assistance or support affordable housing development. If
Washington were to produce an alternative AMI, it would not automatically apply to all such programs. Rather,
agencies that manage these programs would need to change the program rules or standards to reference the
alternative AMI and associated income limits. We identify several potential implementation challenges that
agencies would need to consider when implementing any alternative AMI.
Reconciling alternative AMI with existing federal requirements
Programs that distribute federal funds or tax credits must comply with federal requirements for income limits
and rents. Examples include Low Income Housing Tax Credits managed by WSHFC and the National Housing
Trust Fund managed by Commerce. While these agencies may have the discretion to require deeper
affordability (lower income limits), they cannot increase income limits above HUD limits. If any of these
programs were to adopt an alternative AMI, they would need to determine whether the alternative AMI was
higher or lower than the federal income limit for each area in Washington. In some areas, this determination
could change from year to year. Program managers would also need to develop new compliance monitoring
protocols to ensure all projects comply with both sets of income limits. These changes would have a high
potential to increase the complexity and cost of program management compared to the status quo.
For housing programs funded by the state Legislature, such as HTF, income limits are typically defined by
state statutes, many of which reference HUD's income limits. Adopting an alternative AMI method would
require the Legislature to change those statutes to allow greater flexibility.
Managing alternative geographic boundaries
Each alternative changes the geographic boundaries for measuring AMI compared to the current practice
(HUD MFI). This could result in implementation challenges for programs managed by state, county, or regional
agencies that may need to comply with multiple different AMI standards within an area where they previously
had just one. This kind of change would be least impactful for alternatives calculated at the county scale, as
HUD also uses county boundaries for most areas in Washington. The City MFI and Legislative District MFI
alternatives would have a greater impact statewide, as none of the geographic boundaries would align with
HUD MFI areas.
Commerce's HTF program provides a good example of the challenge of changing AMI boundaries. Commerce
monitors compliance with income limit requirements for properties that receive HTF funds. With the City MFI
alternative, they would need to determine which city each property is located within, or whether a property is
located in an unincorporated area and therefore potentially subject to a different AMI standard. This would
require geographic information systems (GIS) analysis, because the city that appears in a mailing address is
not based on jurisdictional boundaries. Implementing this change would require more administrative effort and
create more opportunities for confusion and error. These challenges would be increased with the Legislative
District MFI alternative.
Exhibit 26 shows a map of legislative districts focusing on the Seattle metropolitan region. Districts are drawn
to include approximately the same population. Therefore, they are much smaller in more densely populated
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 32
areas and larger in rural areas. Districts regularly cross both county and city boundaries. Finally, and most
importantly, most Washington residents are unfamiliar with the district areas and boundaries. This has high
potential for confusion among people seeking housing assistance and errors or misunderstandings among
housing providers seeking to comply with the new requirements.
Exhibit 26. State Legislative Districts in Washington
Legislative District Overlapp ing Cou nty
State Legislative District 1 Snoho mish County
State Legislative District 1 King County
State Legislative District 2 Pierce County
State Legislative District 2 Thurston County
State Legislative District 3 Spokane Coun ty
State Legislative District 4 Spokane Coun ty
State Legislative District 5 King County
State Legislative District 6 Spokane Coun ty
State Legislative District 7 Okanogan Coun ty
State Legislative District 7 Spokane Coun ty
State Legislative District 7 Steve ns County
State Legislative District 7 Pend Oreille Coun ty
State Legislative District 7 Ferry County
State Legislative District 7 Douglas County
State Legislative District 7 Grant Coun ty
State Legislative District 8 Benton Coun ty
State Legislative District 8 Franklin County
State Legislative District 9 Columbia County
State Legislative District 9 Spokane Coun ty
State Legislative District 9 Asotin Coun ty
State Legislative District 9 Garfield Coun ty
State Legislative District 9 Adams Cou nty
State Legislative District 9 Lincoln County
State Legislative District 9 Whitman Cou nty
State Legislative District 9 Franklin County
State Legislative District 10 Snoho mish County
State Legislative District 10 Island County
State Legislative District 10 Skagit County
State Legislative District 11 King County
State Legislative District 12 Snoho mish County
State Legislative District 12 Chelan Coun ty
State Legislative District 12 Douglas County
State Legislative District 12 King County
State Legislative District 13 Kittitas County
State Legislative District 13 Yakima County
State Legislative District 13 Grant Coun ty
State Legislative District 14 Yakima County
State Legislative District 14 Klickitat Coun ty
State Legislative District 15 Yakima County
State Legislative District 15 Benton Coun ty
State Legislative District 15 Grant Coun ty
State Legislative District 15 Adams Cou nty
State Legislative District 15 Franklin County
State Legislative District 16 Benton Coun ty
State Legislative District 16 Walla Walla County
State Legislative District 16 Franklin County
State Legislative District 17 Clark County
State Legislative District 17 Skamania Coun ty
State Legislative District 18 Clark County
State Legislative District 19 Wahkiakum County
State Legislative District 19 Lewis County
State Legislative District 19 Pacific Coun ty
State Legislative District 19 Grays Harbor County
State Legislative District 19 Cowlitz Coun ty
State Legislative District 19 Thurston County
State Legislative District 20 Lewis County
State Legislative District 20 Cowlitz Coun ty
State Legislative District 20 Clark County
State Legislative District 20 Thurston County
State Legislative District 21 Snoho mish County
State Legislative District 22 Thurston County
State Legislative District 23 Kitsap Coun ty
State Legislative District 24 Jefferson Coun ty
State Legislative District 24 Clallam Cou nty
State Legislative District 24 Grays Harbor County
State Legislative District 25 Pierce County
State Legislative District 26 Kitsap Coun
State Legislative District 26 Pierce County
State Legislative District 27 Pierce County
State Legislative District 28 Pierce County
State Legislative District 29 Pierce County
State Legislative District 30 King County
State Legislative District 31 King County
State Legislative District 31 Pierce County
State Legislative District 32 Snoho mish County
State Legislative District 32 King County
State Legislative District 33 King County
State Legislative District 34 King County
State Legislative District 35 Kitsap Coun ty
State Legislative District 35 Mason County
State Legislative District 35 Thurston County
State Legislative District 36 King County
State Legislative District 37 King County
State Legislative District 38 Snoho mish County
State Legislative District 39 Snoho mish County
State Legislative District 39 Skagit County
State Legislative District 40 Whatcom Co unty
State Legislative District 40 San Juan Co unty
State Legislative District 40 Skagit County
State Legislative District 41 King County
State Legislative District 42 Whatcom Co unty
State Legislative District 43 King County
State Legislative District 44 Snoho mish County
State Legislative District 45 King County
State Legislative District 46 King County
State Legislative District 47 King County
State Legislative District 48 King County
State Legislative District 49 Clark County
Source: OFM, 2024; BERK, 2025.
There are also potential impacts regarding equity. Housing market conditions do not change dramatically
when you cross the boundary from one city or district to the next in a single metropolitan region. Yet, two
different households living across the street from one another in neighboring cities or districts would be
subject to different income limits to determine their eligibility for assistance. Likewise, two different
affordable housing properties located in neighboring cities or districts would have different income and rent
limits.
There are affordable housing programs managed at the city scale. A City MFI alternative would be less
complicated to implement for these programs. However, state or federal income limit requirements often
constrain local housing programs. For example, Multifamily Tax Exemption (MFTE) is a program enabled by
state statute that requires affordable units to be affordable to eligible households with income no higher than
defined by HUD income limit standards. So, unless the Legislature changes that requirement, MFTE income
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 33
limits must not exceed those based on HUD MFI. If a city wished to implement the City MFI alternative, it would
need to cross-reference those income limits annually with HUD income limits and publish an income limit table
showing the lower of the two.
Communicating the new requirements
All housing programs identified in this study have income limits based on HUD MFI. Affordable housing
developers, service providers, and people seeking housing assistance often interact with multiple housing
programs. If any program decides to use an alternative AMI, this change will likely confuse program users and
beneficiaries. For example, many online resources allow users to look up income limits for a selected area.
These resources reference the HUD income limit and may not acknowledge local alternative AMIs. This could
lead program users to mistakenly think they qualify or don't qualify for housing, resulting in missed
opportunities, confusion, and frustration.
To address this problem, program managers would need to develop educational materials, update program
guidance, and proactively communicate the change to all interested parties. This would result in higher
administrative costs in the short term. These communication challenges would be ongoing, given that many
affordable housing developers and investors work across state lines and are not accustomed to unique
requirements in Washington.
Administrative costs
Implementing an alternative AMI would result in additional program administration costs. For instance, if the
HTF program adopted an alternative AMI, program managers working at Commerce would need to:
Create new program guidelines and communication material
Present new guidelines to raise awareness
Provide technical assistance to grant applicants unfamiliar with the new AMI income and rent limits
Additional application review time to ensure consistency with new AMI income and rent limits and any
applicable federal requirements
Develop new compliance monitoring protocols for projects funded after adopting the new AMI
Implement the new compliance monitoring protocols while also maintaining the previous protocols for
monitoring projects funded before the new AMI was adopted22
All these activities would require, at a minimum, additional staff time and resources to implement. The costs
associated with these resources could result in less funding available to support affordable housing
production.
Implementing an alternative AMI could negatively impact affordable
housing production and operation
As discussed earlier, only financially feasible affordable housing is built. The housing owner must be able to
pay for necessary operating expenses, maintenance, and debt payments. There are two ways in which
adopting an alternative AMI could negatively impact financial feasibility and reduce the likelihood of new
affordable housing production:
22 Income limit requirements for affordable housing that is already built or currently under development are typically set by contract,
which would not be impacted by future changes to program policies. So, changes to AMI would not impact the compliance
requirements for these properties.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 34
1. Reduced rental revenue
2. Increased compliance costs due to the increased complexity of managing multiple AMI standards
Reduced rental revenue
Some development costs for affordable housing are covered by public funding or tax credits, but rental income
is still essential to keep housing financially viable. If an alternative AMI lowers an area's income and rent limits,
it will also lower the total rent that can be collected from tenants. Unless there is additional public funding to
cover the revenue gap created by the lower rents, this change will make it harder for a new affordable housing
project to be financially feasible. As a result, areas with lower income limits could see less new affordable
housing construction.
If a program decides to implement the City MFI or Legislative District MFI alternative, there would also be
geographic and equity implications. These alternatives could result in higher or lower income limits in different
communities within the same county or region. Because building costs are relatively stable across a county or
region, building in areas with lower income limits would become much less likely without additional public
subsidy. This could result in lower-income communities receiving less new affordable housing production
than higher-income communities.
Increased complexity of compliance
As mentioned earlier, affordable housing developers typically assemble multiple funding sources from multiple
programs to fund projects. If one of the programs requires compliance with income limits based on an
alternative AMI, then the housing provider would need to comply with multiple sets of income limits based on
the different AMIs. Housing providers typically rely on property management software to support the leasing of
units and compliance with all income requirements. The software may not be able to integrate the alternative
AMI or may require costly custom programming to implement the alternative AMI. The alternative AMI will also
need to be updated each year and compared to the standard AMI to determine which is most restrictive and
which applies to specific tenants and units in the project. This increases the complexity of compliance and,
therefore, the staff time required, as well as the likelihood of confusion and mistakes.
Increased complexity results in additional costs and risks associated with developing and operating affordable
housing. For example, suppose a property owner funded in part by LIHTC accidentally violates the federal
income or rent limit. In that case, they face financial penalties that include losing future and past tax credits,
losing the tax-exemption on the bonds, or triggering repayment of debt. Because of this added complexity and
increased risk, developers may avoid using subsidies that require an alternative AMI. This could decrease the
number of affordable units that can be built with available resources.
This challenge is especially pronounced in the alternatives implemented at the city or legislative district scale.
Many affordable housing providers operate multiple properties. Currently, all properties in the same region are
subject to the same set of income limits based on HUD MFI. This would change if the alternative AMI used
different boundaries. A more detailed discussion of this challenge is found in the section of this report,
Managing alternative geographic boundaries.
Finally, this increased complexity would have the potential to cause confusion and frustration among program
users who may qualify for assistance under one income limit standard and not another. This, too, would create
new challenges for affordable housing operators seeking to identify qualified renters.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 35
Reduced utilization of federal resources
Under the current AMI system, state and local funding sources typically align with federal resources. This
allows Washington to leverage its local funding alongside federal funding. The federal government provides
Washington with annual allocations of LIHTC and tax-exempt bonds.23 The tax-exempt bonds are administered
by Commerce and are used to support various infrastructure programs, including affordable housing projects.
Historically, Washington has used all of the tax-exempt bonds that it is allocated. In contrast, some states do
not use all of their tax-exempt bond allocation, resulting in the loss of those federal resources and less new
affordable housing.24 Washington has successfully used all allocated tax-exempt bonds due to relatively high
AMI in the major metropolitan regions and local funding sources that fill gaps to make projects feasible. If
state and local funders adopt lower-income limit requirements, it may result in projects that are no longer
feasible. If projects are not feasible, they will not be built, and the federal resources will not be used. This
would result in less affordable housing production and less use of local funding.
Implementing an alternative AMI could potentially benefit some
households in need of housing assistance while harming others
Because many affordable housing developments layer multiple funding sources with different income and rent
limit requirements, the actual impacts of an alternative AMI applied to a single program may be limited in
practice. However, for this evaluation, we examine how 60% AMI income and rent limits would change under
each alternative without regard to potential interaction with federal income limit requirements. These impacts
vary significantly in different communities.
If a housing program adopts an alternative AMI, it could result in changes to income limit thresholds used to
determine eligibility for housing assistance and rents for affordable housing units. This is illustrated in Exhibit
27, which compares our 60% AMI income limits for the Legislative District MFI Alternative to HUD's published
60% AMI for the same area. Areas below HUD MFI (shown in blue) would see income limits and rent limits
increase, while areas above HUD MFI (shown in red and orange) would see decreases. Areas in gray would see
little or no change. The areas of most significant change are in King and Snohomish counties, where HUD MFI
is highest, and there are significant disparities in income across different communities.
Changes to AMI in Washington would not result in additional households
receiving assistance
The need for affordable housing in Washington far exceeds the available resources to provide assistance.
Housing authorities across the state maintain long waitlists of eligible households seeking housing support.
Changing the income limit to expand eligibility would not result in any additional households receiving
assistance. Instead, there would just be more households competing for the same limited resources.
23 A state receives an amount of federal LIHTC and tax-exempt bonds based on its population. This is commonly referred to as an
allocation of LIHTC or tax-exempt bonds. For 2024, a state received $3 of annual tax credits for each person in the state (approximately
$220M of credits) and $130 of tax-exempt bonds for each person in the state (approximately $976M of tax-exempt bonds). If a state
does not use all its credits or tax-exempt bonds in the timeline permitted by the IRS, the state agency must return its unused credits.
24 Source: Novogradac, 2025.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 36
Exhibit 27. Comparison of State Legislative District MFI alternative to HUD MFI (60%
AMI for 2024)
Legislative District County State legislative district MFI co mpare d to HU D MF I (60% AMI for 2024 )
State Legislative District 1 Snoho mish $10,95 0
State Legislative District 1 King $10,95 0
State Legislative District 2 Pierce -$1,7 50
State Legislative District 2 Thurston $150
State Legislative District 3 Spokane -$3,0
State Legislative District 4 Spokane -$3,1 50
State Legislative District 5 King $13,05
State Legislative District 6 Spokane -$4,1 50
State Legislative District 7 Okanogan $0
State Legislative District 7 Spokane -$4,7 50
State Legislative District 7 Steve ns $0
State Legislative District 7 Pend Oreille $0
State Legislative District 7 Ferry $0
State Legislative District 7 Douglas -$1,6 00
State Legislative District 7 Grant $0
State Legislative District 8 Benton $9,250
State Legislative District 8 Franklin $9,250
State Legislative District 9 Columbia $5,700
State Legislative District 9 Spokane $2,050
State Legislative District 9 Asotin $10,20
State Legislative District 9 Garfield $6,800
State Legislative District 9 Adams $6,800
State Legislative District 9 Lincoln $6,800
State Legislative District 9 Whitman $5,050
State Legislative District 9 Franklin $850
State Legislative District 10 Snoho mish -$25, 300
State Legislative District 10 Island $3,900
State Legislative District 10 Skagit $5,000
State Legislative District 11 King -$20, 850
State Legislative District 12 Snoho mish -$26, 000
State Legislative District 12 Chelan $8,800
State Legislative District 12 Douglas $8,800
State Legislative District 12 King -$26, 000
State Legislative District 13 Kittitas -$5,4
State Legislative District 13 Yakima $0
State Legislative District 13 Grant $0
State Legislative District 14 Yakima $0
State Legislative District 14 Klickitat $0
State Legislative District 15 Yakima $0
State Legislative District 15 Benton -$5,9 50
State Legislative District 15 Grant $0
State Legislative District 15 Adams $0
State Legislative District 15 Franklin -$5,9 50
State Legislative District 16 Benton -$5,0 50
State Legislative District 16 Walla Walla $800
State Legislative District 16 Franklin -$5,0
State Legislative District 17 Clark $2,150
State Legislative District 17 Skamania $2,150
State Legislative District 18 Clark -$1,6 00
State Legislative District 19 Wahkiakum $0
State Legislative District 19 Lewis $0
State Legislative District 19 Pacific $0
State Legislative District 19 Grays Harbor $0
State Legislative District 19 Cowlitz $0
State Legislative District 19 Thurston -$13, 600
State Legislative District 20 Lewis $6,700
State Legislative District 20 Cowlitz $6,700
State Legislative District 20 Clark -$10, 100
State Legislative District 20 Thurston -$6,9
State Legislative District 21 Snoho mish -$12, 900
State Legislative District 22 Thurston $200
State Legislative District 23 Kitsap $1,750
State Legislative District 24 Jefferson $0
State Legislative District 24 Clallam -$1,1 00
State Legislative District 24 Grays Harbor $0
State Legislative District 25 Pierce $1,300
State Legislative District 26 Kitsap $250
State Legislative District 26 Pierce $2,550
State Legislative District 27 Pierce -$200
State Legislative District 28 Pierce -$12, 750
State Legislative District 29 Pierce -$15, 500
State Legislative District 30 King -$30, 200
State Legislative District 31 King -$9,3 50
State Legislative District 31 Pierce $11,55 0
State Legislative District 32 Snoho mish -$14, 150
State Legislative District 32 King -$14, 150
State Legislative District 33 King -$30, 700
State Legislative District 34 King -$3,7 50
State Legislative District 35 Kitsap -$4,3 00
State Legislative District 35 Mason $12,40
State Legislative District 35 Thurston -$100
State Legislative District 36 King $40,05
State Legislative District 37 King -$10, 250
State Legislative District 38 Snoho mish -$27, 000
State Legislative District 39 Snoho mish -$19, 900
State Legislative District 39 Skagit $10,40
State Legislative District 40 Whatcom $2,700
State Legislative District 40 San Juan $5,150
State Legislative District 40 Skagit $5,950
State Legislative District 41 King $44,65
State Legislative District 42 Whatcom -$5,2 50
State Legislative District 43 King $42,70
State Legislative District 44 Snoho mish $6,800
State Legislative District 45 King $31,30
State Legislative District 46 King 10
State Legislative District 47 King -$18, 500
State Legislative District 48 King $25,65 0
State Legislative District 49 Clark -$16, 000
Sources: HUD, 2024; BERK, 2024.
As of 2021, nearly 370,000 households statewide with incomes above 60% AMI were cost-burdened or lived in
substandard housing.25 These households cannot find suitable, affordable housing and do not qualify for most
housing assistance programs. Exhibit 28 compares how this number would change under each alternative. If
the City MFI A, City MFI B, or County MFI A alternatives were implemented, there would be minimal net change
in the total number of households eligible at 60% AMI. County MFI B would result in a moderate net reduction,
while the County Median Renter alternative would result in a significant increase.
25 Source: HUD CHAS, 2024 (based on 2017-2021 Census ACS 5-year estimates); BERK, 2025.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 37
Exhibit 28. Total households in Washington that are cost-burdened or live in
substandard housing and would not qualify for assistance at 60% AMI, 2021
County Median Renter 617,512
Legislative District MFI Data unavailable
County MFI - B 321,862
County MFI - A 359,810
City MFI - B 373,634
City MFI - A 372,381
HUD MFI (current AMI) 367,744
Note: Sufficient data is unavailable to complete this analysis for the Legislative District MFI alternative.
Source: HUD CHAS, 2024 (based on 2017-2021 Census ACS 5-year estimates); BERK, 2025.
While some alternatives show little change in statewide totals, that summary masks impacts at the local level.
Exhibit 29 shows the number of households that would either gain or lose eligibility for assistance at 60% AMI,
by alternative. The County Median Renter alternative would have the most significant impact, as it lowers AMI
and income limits in every area across the state. This would result in nearly 250,000 households losing their
eligibility for support at 60% AMI. For other alternatives, the impacts vary by location. As a result, some
households would lose their eligibility, while others could potentially gain eligibility for programs that do not
have federal requirements.
Exhibit 29. Estimated households that are cost-burdened or live in substandard
housing and would gain or lose eligibility for housing assistance at 60% AMI by
alternative, 2021
County Median Renter 249,768
0
Legislative District MFI Data unavailable
County MFI - B 3,871
49,752
County MFI - A 9,350
17,284
City MFI - B 38,516
32,626
26,863 Households that would lose eligibility
City MFI - A
22,226
Households that would gain eligibility
Note: Sufficient data is unavailable to complete this analysis for the Legislative District MFI alternative.
Source: HUD CHAS, 2024 (based on 2017-2021 Census ACS 5-year estimates); BERK, 2025.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 38
Because many affordable housing developments layer multiple funding sources with different income and rent
limit requirements, the actual impacts of an alternative AMI applied to a single program may be limited in
practice. However, for this evaluation, we examine how 60% AMI income and rent limits would change under
each alternative without regard to potential interaction with federal income limit requirements. We find these
impacts vary significantly in different communities. Exhibit 30 shows several example cities in Washington,
organized by two dimensions that would significantly impact the outcomes of a change in AMI method: AMI
and market rents. High AMI refers primarily to Seattle-Bellevue, WA HMFA, or King and Snohomish counties,
where the AMI is considerably higher than elsewhere in Washington. In this row, there are two types of cities:
those with relatively high costs, such as Bellevue, and those with relatively low costs, such as Federal Way.26
The matrix also includes examples of cities in HUD areas that we classify as medium AMI and low AMI.
Exhibit 30. Matrix of example WA cities by AMI level and housing market conditions
Source: BERK, 2025.
The following sections share potential impacts on households seeking housing assistance for a sample of
cities in each part of this matrix. Complete data for nearly all cities in Washington is available for download.
Impacts in Bellevue (high AMI and high cost)
Exhibit 31 presents our analysis of each alternative for Bellevue. The 60% AMI income limits (shown as
columns) are for a three-person household (HH), and the rent limits are for a two-bedroom home. It also shows
some representative annual incomes for comparison. Market rent27 for a two-bedroom home is $3,550 per
month. This is particularly high for Washington. A household needs an income of nearly $142,000 to afford this
rent. Also provided for comparison are annual incomes associated with a single full-time minimum wage job
and two full-time minimum wage jobs, based on Washington's statewide minimum wage.
Exhibit 32 presents the estimated percentage of total households in Bellevue that would be eligible for housing
assistance at 60% AMI by alternative. This analysis is based on conditions as of 2021, the most recent data
available for analysis.28 Alternatives that raise the income limit increase the percentage of households that
26 The word "relatively" is important here. Market rents in Federal Way are still quite high and unaffordable for many residents.
Nonetheless, relative to other cities in the same HUD area (such as Bellevue and Kirkland), rents in Federal Way are much lower.
27 The charts in this section show our estimate of HUD Fair Market Rent (FMR) for individual cities. FMR is HUD's official estimate of
the 40th percentile rent for a dwelling unit within a defined area. "40th percentile" is a statistical measure similar to median, except that
60% of all rents in the area are higher, and 40% of all rents in the area are lower. FMR includes the cost of shelter and all major utilities
(except phone, TV, and internet) (HUD, 2025).
28 We used HUD CHAS for households by income level based on 2017-2021 ACS data. This analysis also reflects a calculation of 60%
AMI by alternative for the year 2021. See Appendix C. Alternative AMI and impact analysis methodologies for details.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 39
would be eligible at 60% AMI. Alternatives that lower the income limit would reduce the number of households
eligible. In the charts that follow, FTE indicates full-time equivalent employment.
Exhibit 31. Bellevue 60% AMI for 3-Person HH by alternative with comparison
incomes, 2024
HUD MF I City MFI - A City MFI - B County MF I - A County MF I - B Legislative District MFI County M edia n Renter
60% AMI income limi t $81,35 0 $111,7 50 $103,7 50 $91,60 0 $87,55 0 $121,5 50 $49,75 0
WA minimu m wage FTE $33,86 2 $33,86 2 $33,86 2 $33,86 2 $33,86 2 $33,86 2 $33,86 2
Two WA minimum wage FTE $67,72 5 $67,72 5 $67,72 5 $67,72 5 $67,72 5 $67,72 5 $67,72 5
Average Social Security Inco me (SSI ) $22,23 9 $22,23 9 $22,23 9 $22,23 9 $22,23 9 $22,23 9 $22,23 9
Two average SSI $44,47 9 $44,47 9 $44,47 9 $44,47 9 $44,47 9 $44,47 9 $44,47 9
Income neede d to afford market rent $141,9 88 $141,9 88 $141,9 88 $141,9 88 $141,9 88 $141,9 88 $141,9 88
BERK estima ted market rent $3,550 $3,550 $3,550 $3,550 $3,550 $3,550 $3,550
Rent for 60% AMI Uni t $2,034 $2,794 $2,594 $2,290 $2,189 $3,039 $1,244
% difference betwe en 60% AMI rent and market rent -43% -21% -27% -35% -38% -14% -65%
Sources: HUD, 2024; BERK, 2025.
Exhibit 32. Bellevue percentage of total households eligible at 60% AMI, 2021
HUD MFI 19%
City MFI - A 23%
City MFI - B 25%
County MFI - A 21%
County MFI - B 21%
Legislative District MFI 26%
County Median Renter 12%
Sources: HUD, 2024; BERK, 2025.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 40
Impacts of current conditions (HUD MFI) in Bellevue — status quo alternative
There is a large gap between the income needed to afford market rent for a two-bedroom apartment and
HUD’s 60% AMI for a three-person household ($81,350). This means that the 60% AMI income limit effectively
targets households whose needs are unmet by the housing market. This includes households with two full-
time minimum wage earners. As of 2021, about 19% of all households of all sizes (not just three-person
households) had incomes at or below HUD's 60% AMI.
Many households in Bellevue with incomes higher than 60% AMI still cannot afford market rent. These
households are not well served by programs that provide units at 60% AMI, but they could be served by
programs that target higher incomes, such as 80% or 100% AMI.
Impacts of City MFI, County MFI, and Legislative District MFI alternatives in Bellevue
The City, County, and Legislative District MFI alternatives all increase 60% AMI compared to HUD. This is
because the median income in Bellevue is higher than the surrounding region, and the median income in King
County is higher than the entire Seattle-Bellevue, WA HMFA. In each case, the higher income limit would
reduce the large gap between 60% AMI and income needed to afford market rent and increase the percentage
of households eligible at 60% AMI. However, these alternatives also increase the rents for units affordable at
60% AMI.
Impacts of the County Median Renter alternative in Bellevue
The County Median Renter alternative dramatically lowers the 60% AMI three-person household income limit to
less than $50,000. This is significantly less than the income of a household with two full-time minimum wage
earners, but still more than that of a household with a single full-time minimum wage earner. As a result, the
alternative reduces the percentage of households eligible for assistance at 60% AMI (down to just 12% as of
2021).
This alternative would also dramatically lower rents to a more affordable level for many low-income
households, providing significant benefits for some households. However, development feasibility would be
expected to fall significantly with this alternative. New development would likely require significantly more
subsidies, meaning fewer new housing units per dollar of public investment.
Impacts in Sultan (high AMI and low cost)
Sultan is a small city surrounded by rural areas in Snohomish County. Because it is part of the Seattle-Bellevue,
WA HMFA, HUD assigns it the same AMI and income limits as it does for Bellevue and the rest of the region.
Yet both income and housing market conditions in Sultan are very different. This results in different impacts on
both the current AMI and alternatives, as illustrated in Exhibit 33. After which, we describe these impacts in
more detail.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 41
Exhibit 33. Sultan 60% AMI for a 3-person household by alternative with comparison
incomes, 2024
HUD MF I City MFI - A City MFI - B County MF I - A County MF I - B Legislative District MFI County M edia n Renter
60% AMI income limi t $81,35 0 $54,75 0 $52,30 0 $77,30 0 $71,60 0 $63,45 0 $44,75 0
WA minimu m wage FTE $33,86 2 $33,86 2 $33,86 2 $33,86 2 $33,86 2 $33,86 2 $33,86 2
Two WA minimum wage FTE $67,72 5 $67,72 5 $67,72 5 $67,72 5 $67,72 5 $67,72 5 $67,72 5
Average Social Security Inco me (SSI ) $22,23 9 $22,23 9 $22,23 9 $22,23 9 $22,23 9 $22,23 9 $22,23 9
Two average SSI $44,47 9 $44,47 9 $44,47 9 $44,47 9 $44,47 9 $44,47 9 $44,47 9
Income neede d to afford market rent $69,61 2 $69,61 2 $69,61 2 $69,61 2 $69,61 2 $69,61 2 $69,61 2
BERK estima ted market rent $1,740 $1,740 $1,740 $1,740 $1,740 $1,740 $1,740
Rent for 60% AMI Uni t $2,034 $1,369 $1,308 $1,933 $1,790 $1,586 $1,119
% difference betwe en 60% AMI rent and market rent 17% -21% -25% 11% 3% -9% -36%
Sources: HUD, 2024; BERK, 2025.
Exhibit 34. Sultan's percentage of total households eligible at 60% AMI, 2021
HUD MFI 39%
City MFI - A 28%
City MFI - B 29%
County MFI - A 35%
County MFI - B 38%
Legislative District MFI 30%
County Median Renter 15%
Sources: HUD, 2024; BERK, 2025.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 42
Impacts of current conditions (HUD MFI) in Sultan — status quo alternative
In 2024, the income needed to afford market 2-bedroom rent ($69,612) was less than HUD's 60% AMI for a 3-
person household ($81,350). This comparison is similar for other household and unit sizes. As a result, there
was no incentive to develop 60% AMI affordable housing without greater public subsidy. On the other hand, the
high AMI results in a relatively large percentage (39%) of households being eligible for assistance.
Impacts of alternatives in Sultan
All the alternatives decrease 60% AMI compared to HUD. This is because the median income in Sultan is lower
than the surrounding region, and the median income in Snohomish County is lower than the entire Seattle-
Bellevue, WA HMFA. However, the impacts of the County MFI and Legislative District MFI alternatives are less
significant than they are for the City MFI and County Median Renter alternatives.
The City MFI and County Median Renter alternatives have 60% AMI income limits that are significantly less
than the income of a household with two full-time minimum wage earners, but still more than a household with
a single full-time minimum wage earner. As a result, these alternatives reduce the percentage of households
that would be eligible for assistance at 60% AMI (down to 28-29% for the City MFI options and just 15% for
County Median Renter as of 2021). They also reduce the rents for a 60% AMI unit to significantly below market
conditions. This has the potential to benefit lower-income households, provided that affordable housing
developers have access to additional subsidies to support production.
Impacts in Bainbridge Island (medium AMI and high cost)
Like Bellevue, Bainbridge Island has relatively high housing costs. However, AMI in Kitsap County is
significantly lower than in King and Snohomish counties. So, the potential impacts of an alternative AMI are
somewhat different, as shown in Exhibit 35 and Exhibit 36.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 43
Exhibit 35. Bainbridge Island 60% AMI for 3-person households by alternative with
comparison incomes, 2024
HUD MF I City MFI - A City MFI - B County MF I - A County MF I - B Legislative District MFI County M edia n Renter
60% AMI income limi t $64,70 0 $103,3 50 $103,3 00 $64,60 0 $64,60 0 $66,20 0 $44,60 0
WA minimu m wage FTE $33,86 2 $33,86 2 $33,86 2 $33,86 2 $33,86 2 $33,86 2 $33,86 2
Two WA minimum wage FTE $67,72 5 $67,72 5 $67,72 5 $67,72 5 $67,72 5 $67,72 5 $67,72 5
Average Social Security Inco me (SSI ) $22,23 9 $22,23 9 $22,23 9 $22,23 9 $22,23 9 $22,23 9 $22,23 9
Two average SSI $44,47 9 $44,47 9 $44,47 9 $44,47 9 $44,47 9 $44,47 9 $44,47 9
Income neede d to afford market rent $112,1 47 $112,1 47 $112,1 47 $112,1 47 $112,1 47 $112,1 47 $112,1 47
BERK estima ted market rent $2,804 $2,804 $2,804 $2,804 $2,804 $2,804 $2,804
$2,584
Rent for 60% AMI Uni t $1,618 $2,583 $1,615 $1,615 $1,655 $1,115
% difference betwe en 60% AMI rent and market rent -42% -8% -8% -42% -42% -41% -60%
Sources: HUD, 2024; BERK, 2025.
Exhibit 36. Bainbridge Island percentage of total households eligible at 60% AMI,
2021
HUD MFI 13%
City MFI - A 24%
City MFI - B 27%
County MFI - A 13%
County MFI - B 16%
Legislative District MFI 13%
County Median Renter 6%
Sources: HUD, 2024; BERK, 2025.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 44
Impacts of current conditions (HUD MFI) in Bainbridge Island — status quo alternative
There is a large gap between the income needed to afford market rent for a two-bedroom apartment and
HUD’s 60% AMI for a three-person household ($64,700). This means that the 60% AMI income limit effectively
targets households whose needs are unmet by the housing market. As of 2021, about 13% of all households
(not just three-person households) had incomes at or below HUD's 60% AMI.
There are many households in Bainbridge Island with an income that is higher than the 60% AMI limit that still
cannot afford market rent. This includes households with two full-time minimum wage earners. These
households are not well served by programs that provide units at 60% AMI, but they could be served by
programs that target higher incomes, such as 80% or 100% AMI.
Impacts of City MFI alternatives on Bainbridge Island
The City MFI alternatives significantly increase the 60% AMI compared to HUD. This is because the median
income in Bainbridge Island is significantly higher than the rest of Kitsap County. In each case, the higher
income limit would reduce the large gap between 60% AMI and income needed to afford market rent and
increase the percentage of households eligible at 60% AMI. However, these alternatives also increase the rents
for units affordable at 60% AMI.
Impacts of the County Median Renter alternative on Bainbridge Island
The County Median Renter alternative dramatically lowers the 60% AMI three-person household income limit to
less than $45,000. This is significantly less than the income of a household with two full-time minimum wage
earners, but still more than that of a household with a single full-time minimum wage earner. As a result, the
alternative reduces the percentage of households eligible for assistance at 60% AMI (down to just 6% as of
2021).
This alternative would also dramatically lower rents to a more affordable level for many low-income
households, providing significant benefits for some households. However, development feasibility would be
expected to fall significantly with this alternative. New development would require significantly more subsidies,
meaning fewer new housing units per dollar of public investment.
Impacts in Pasco (medium AMI and low cost)
Pasco is a growing medium-sized city in the Kennewick-Richland, WA MSA. Housing costs in Pasco are
relatively lower than in the rest of the region.
Exhibits 37 and 38 show findings for this city, with a discussion of impacts below.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 45
Exhibit 37. Pasco 60% AMI for 3-person households by alternative with comparison
incomes, 2024
HUD MF I City MFI - A City MFI - B County MF I - A County MF I - B Legislative District MFI County M edia n Renter
60% AMI income limi t $54,00 0 $48,60 0 $43,95 0 $48,60 0 $46,75 0 $48,60 0 $38,85 0
WA minimu m wage FTE $33,86 2 $33,86 2 $33,86 2 $33,86 2 $33,86 2 $33,86 2 $33,86 2
Two WA minimum wage FTE $67,72 5 $67,72 5 $67,72 5 $67,72 5 $67,72 5 $67,72 5 $67,72 5
Average Social Security Inco me (SSI ) $22,23 9 $22,23 9 $22,23 9 $22,23 9 $22,23 9 $22,23 9 $22,23 9
Two average SSI $44,47 9 $44,47 9 $44,47 9 $44,47 9 $44,47 9 $44,47 9 $44,47 9
Income neede d to afford market rent $53,28 2 $53,28 2 $53,28 2 $53,28 2 $53,28 2 $53,28 2 $53,28 2
BERK estima ted market rent $1,332 $1,332 $1,332 $1,332 $1,332 $1,332 $1,332
Rent for 60% AMI Uni t $1,350 $1,215 $1,099 $1,215 $1,169 $1,215 $971
% difference betwe en 60% AMI rent and market rent 1% -9% -18% -9% -12% -9% -27%
Sources: HUD, 2024; BERK, 2025.
Exhibit 38. Pasco percentage of total households eligible at 60% AMI, 2021
HUD MFI 31%
City MFI - A 27%
City MFI - B 22%
County MFI - A 27%
County MFI - B 25%
Legislative District MFI 27%
County Median Renter 16%
Sources: HUD, 2024; BERK, 2025.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 46
Impacts of current conditions (HUD MFI) in Pasco — status quo alternative
In 2024, the income needed to afford market rent ($53,282) was slightly less than HUD's 60% AMI ($54,000).
This severely limits the benefits of 60% AMI affordable housing for meeting local housing needs and reduces
the incentive for developers to produce this housing without greater public subsidy.
In Pasco, a three-person household with two full-time minimum wage earners is not eligible for support at 60%
AMI. However, a three-person household with a single minimum wage income would be eligible. As of 2021,
about 31% of all households in Pasco would qualify for assistance at 60% AMI.
Impacts of alternatives in Pasco
All of the alternatives decrease 60% AMI compared to HUD. This is because the median income in Pasco is
lower than the surrounding region, and the median income in Franklin County is lower than the entire
Kennewick-Richland, WA MSA. However, most of the alternatives reduce 60% AMI by a relatively small amount.
The City MFI B and County Median Renter alternatives have the most significant impact on 60% AMI, bringing
down the income limits and rents for affordable housing. As a result, these alternatives reduce the percentage
of households that would be eligible for assistance at 60% AMI (down to 22% for the City MFI B and just 16%
for County Median Renter as of 2021). These limits are still higher than a household with a single full-time
minimum wage earner. They also reduce the rents for a 60% AMI unit to significantly below market conditions.
This has the potential to benefit lower-income households, provided that affordable housing developers have
access to additional subsidies to support production.
Impacts in Yakima (low AMI and low cost)
Exhibit 39 and Exhibit 40 show our analysis of the impacts of the alternatives in the City of Yakima. Yakima
County is one of many rural counties in Washington with HUD income limits that are impacted by the state
non-metro median adjustment to VLI. This means that income limits in each of these counties are increased
above a simple calculation of County 50% MFI. We applied this same adjustment to the City MFI A, County MFI
A, and Legislative District MFI alternatives. As a result, there is very little difference between the alternatives
and HUD MFI, except for the County Median Renter alternative. This outcome is consistent across nearly all
communities in counties impacted by this adjustment.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 47
Exhibit 39. City of Yakima 60% AMI for 3-person households by alternative with
comparison incomes, 2024
HUD MF I City MFI - A City MFI - B County MF I - A County MF I - B Legislative District MFI County M edia n Renter
60% AMI income limi t $48,60 0 $48,60 0 $46,70 0 $48,60 0 $48,60 0 $48,60 0 $27,05 0
WA minimu m wage FTE $33,86 2 $33,86 2 $33,86 2 $33,86 2 $33,86 2 $33,86 2 $33,86 2
Two WA minimum wage FTE $67,72 5 $67,72 5 $67,72 5 $67,72 5 $67,72 5 $67,72 5 $67,72 5
Average Social Security Inco me (SSI ) $22,23 9 $22,23 9 $22,23 9 $22,23 9 $22,23 9 $22,23 9 $22,23 9
Two average SSI $44,47 9 $44,47 9 $44,47 9 $44,47 9 $44,47 9 $44,47 9 $44,47 9
Income neede d to afford market rent $54,43 1 $54,43 1 $54,43 1 $54,43 1 $54,43 1 $54,43 1 $54,43 1
BERK estima ted market rent $1,361 $1,361 $1,361 $1,361 $1,361 $1,361 $1,361
Rent for 60% AMI Uni t $1,215 $1,215 $1,168 $1,215 $1,215 $1,215 $676
% difference betwe en 60% AMI rent and market rent -11% -11% -14% -11% -11% -11% -50%
Sources: HUD, 2024; BERK, 2025.
Exhibit 40. Yakima percentage of total households eligible at 60% AMI, 2021
HUD MFI 35%
City MFI - A 35%
City MFI - B 40%
County MFI - A 35%
County MFI - B 38%
Legislative District MFI 35%
County Median Renter 16%
Sources: HUD, 2024; BERK, 2025.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 48
Impacts of current conditions (HUD MFI) in Yakima — status quo alternative
In 2024, the income needed to afford a 2-bedroom market rent ($54,431) was somewhat higher than HUD's
60% AMI for a three-person household ($48,600). This indicates that the 60% AMI income limit effectively
targets households whose needs are unmet by the housing market. This includes households with a single full-
time minimum wage earner. As of 2021, about 35% of all households (not just three-person households) had
incomes at or below HUD's 60% AMI.
Exhibit 39 shows a narrow band of households in Yakima with incomes higher than the 60% AMI limit who still
could not afford market rent. Few households are likely to fall into this gap. Households with two full-time
minimum wage earners have significantly more income and are able to afford market rents.
Impacts of City, County, and Legislative District MFI alternatives in Yakima
These alternatives have very little impact on 60% AMI compared to HUD. This is due to the state non-metro
median income adjustment for VLI, which HUD uses as a floor for income limits in lower-income areas of the
state. This same adjustment was applied to most of these alternatives (County MFI B and City MFI B
alternatives excluded).
Impacts of the County Median Renter alternative in Yakima
The County Median Renter alternative significantly reduces 60% AMI, bringing down the income limits and
rents for affordable housing. However, the limit is so low that not even a single full-time minimum wage earner
would be eligible for assistance. This severely limits the percentage of households that would be eligible for
assistance (16% or less than half compared to current conditions).
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 49
Recommendations and policy considerations
1) Do not develop and implement an alternative AMI for Washington
The findings in this study confirm that there are many challenges with AMI and concerns about its impacts on
housing programs. However, developing and implementing an alternative AMI would not provide short-term
benefits for affordable housing residents. It could also have significant, unintended negative consequences for
the future production of affordable housing. If the goal of an alternative AMI is to prioritize existing housing
resources more effectively for populations in need, there are other ways to achieve this outcome.
2) Tailor income limit targets to reflect local needs and conditions
Statewide housing program managers should look for ways to tailor income limits better to reflect local needs
and conditions. An example is Commerce's Housing Trust Fund (HTF), which allows for different income limits
when funding projects in rural communities and much of eastern Washington compared to the rest of the
state. This is due to relatively lower AMIs in those areas. HTF and others can build on this approach by
consistently aligning income limits with local incomes and housing market conditions. Commerce could
support this process by providing annual data to assess this alignment.29
3) Differentiate income and rent limits to lower cost burden
HUD's rent limits for subsidized housing units are calculated to be affordable for households at the upper limit
of income eligibility. As a result, households with incomes below this upper limit spend more than they can
afford on housing. Affordable housing policymakers could consider basing rent caps on a lower AMI level. For
example, if the income limit for a unit is 60% AMI, then rent could be set to be affordable for a 50% AMI
household. Alternatively, an upper limit for rents could be set to be no higher than 80% of the local FMR.30
4) Revise income eligibility calculations to account for medical or
dependent care expenses
While HUD adjusts income limits for household size, the agency does not account for major expenses that can
impact the income available to pay for housing costs. Some federal programs, such as USDA Rural
Development's 502 home loan program, have guidelines for adjusting an applicant's income to include
deductions for dependents, childcare expenses, disability assistance, and medical expenses. Programs that
use state funding could allow for similar deductions when determining income eligibility. However, these types
of changes could not be applied to programs that use federal resources.
29 Another opportunity is to adjust the unit set-aside matrix in the LIHTC allocation process. When applying to the WSHFC for LIHTC,
developers obtain points for agreeing to lower income and rent restrictions than required by federal statute. As proposed in a previous
report from Commerce and WSHFC, we recommend that WSHFC evaluate how adjusting the LIHTC point system could reduce rent
burden, better target units to local needs, and reach households not currently served by the points system. This would involve
evaluating the 9% Tax Credit Program’s Additional Low-Income Set-Aside Menu, which provides a matrix of options that developers
select as their ongoing affordability commitment for incentive points when applying for allocations of tax credits under this program.
The matrix offers options, allowing developers to serve households across a prescribed mix of income levels. For example, one current
option is to commit to half of the units serving households at 30% AMI, 25% serving 40% AMI, and 25% serving 60% AMI. WSHFC could
examine portfolio data for outcomes related to rent burden and adjust matrix options as appropriate to address unintended
consequences resulting in rent burden for residents. This could incorporate a policy for using the Average Income Test (AIT or income
averaging) as an option in addition to adjustments to the current options.
30 HUD publishes Small Area FMRs for every ZIP code. These estimate the cost of an area's 40th percentile market rental unit.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 50
Appendix A. Engagement summary report
Introduction
The Engagement summary report describes the objectives, methods, and findings of engagement activities
conducted to support this study. The summary is presented in four sections:
1. Engagement objectives
2. Advisory bodies
3. Engagement activities
4. Presentations
Engagement objectives
The engagement activities were designed to gather input and information from interested parties to inform the
analysis and recommendations. Commerce and the project team identified the following information needs:
Perspectives on the challenges and strengths of the current AMI calculation method
The impact of the current AMI method on efforts to address underserved housing needs in Washington
Geographic areas that are potentially underserved due to the current AMI method
Impacts of the current AMI method on residents needing housing assistance
Administrative, data, or funding impacts of the current AMI method on developers and operators of
affordable housing
Examples of alternative AMI calculation methods in use or suggested
Administrative, data, or funding challenges and opportunities associated with alternative AMI methods
Implementation challenges and opportunities associated with adopting an alternative AMI across
Washington’s housing assistance programs
In addition to gathering information and input to inform the study analysis and recommendation, the program
of engagement activities is also designed to accomplish the following process goals:
Ensure transparency in the analysis and decision-making
Access key expertise early to improve the methods, analysis, and recommendations
Include consultation of program implementers who use AMI calculations, direct beneficiaries of those
programs, and those who need housing assistance but do not qualify for available programs
Develop recommendations informed by the concerns and experiences of interested parties that would
be impacted by any changes to the AMI calculation method
Advisory bodies
The study benefited from the guidance of two advisory bodies that provided advice throughout the study
process.
Internal Advisory Workgroup
Role and contributions
The Internal Advisory Workgroup included managers of state programs that changes to AMI could impact. The
group met four times to review draft deliverables and provide guidance. These individuals provided
information on potential implementation challenges that could arise from any changes to the AMI calculation
in Washington.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 51
Exhibit 41. Internal Advisory Workgroup composition
Teri Lawless, Commerce Housing Division, Multifamily Housing Unit
Alex Smith, Commerce Housing Division, Data Performance Unit
Melodie Pazolt, Commerce Housing Division, Office of Apple Health and Homes
Ann Campbell, Commerce Housing Division, Homelessness Assistance Unit
Kirsten Jewell, Commerce Housing Division, Housing Policy and Strategic Initiatives Unit
Tedd Kelleher, Commerce Housing Division, Housing Policy and Strategic Initiatives Unit
Laura Hodgson, Commerce Local Growth Management Division, Growth Management Services Unit
Jesse Warren, King County Department of Finance
Taylor Danielson, Department of Social and Health Services, Research and Data Analysis
TyeRae Guined, Commerce Housing Division, Multifamily Housing Unit
Advisory Committee
Composition
The composition of the Advisory Committee (AC) was guided by the legislative funding provision and the
project goal of assessing the benefits and drawbacks of various methods of calculating AMI. The AC included
members who use AMI calculations to administer programs and policies, developers of affordable housing,
and representatives of affordable housing program beneficiaries.
Role and contributions
The AC provided advice on identifying and evaluating alternative methods for calculating AMI. The AC's input
was considered and noted, while Commerce made the final decision regarding the study findings and
recommendations.
Exhibit 42. Advisory Committee composition
Amy Falcone
Kirkland City Council; AHAB
o Kirkland Councilmember; AHAB member for the Association of Washington Cities
Brian Lloyd
Beacon Development Group
o Vice President
Carl Schroeder
Association of Washington Cities
o Government Relations Deputy Director
Conor Hansen
SRM Development; AHAB
o Managing Principal, Affordable Housing; AHAB member for Residential Construction
Curtis Steinhauer
Washington Association of Counties
o Policy Coordinator
David Ellsworth
Northwest Community Land Trust Coalition
o Homeownership Program Director
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 52
o NWCLTC Board Member
Kelli Larsen
City of Seattle Office of Housing
o Director of Strategic Initiatives
Korbie Jorgensen Haley
Office of Rural and Farmworker Housing
o Director of Housing Development
Lowel Krueger
Yakima Housing Authority; AHAB
o Executive Director; AHAB member for PHA
Michone Preston
Habitat for Humanity of Washington State; AHAB
o CEO; AHAB Chair
Patience Malaba or Jesse Simpson
Housing Development Consortium of Seattle-King County
o Executive Director
o Director of Government Relations and Policy
Rachael Myers
Washington Low Income Housing Alliance
o Executive Director
Wubet Biratu
Washington State Housing Finance Commission
o Division Director, Asset Management and Compliance
Engagement activities
Survey
The survey was a web-based tool to gather input on respondents' diverse needs and perspectives. It was
widely distributed with assistance from AC members, Commerce program staff, and other identified interested
parties.
Goals
The survey included questions about respondents’ views on:
The strengths and areas for improvement of the current AMI method and the potential impacts of
changing it.
Alternative AMI calculation methods for housing purposes. This input informed the models the study
evaluated and the evaluation criteria.
The survey also included a question about interest in providing additional input, helping us identify individuals
whose perspectives warranted further exploration and who were interested in engaging more with the project.
Process:
The web-based survey, which featured multiple-choice and open-ended questions, was distributed to
participants via email and Commerce newsletters.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 53
The survey was open from December 9 to January 10.
The raw survey response data were cleaned and prepared for analysis.
The open-response questions were analyzed using a hybrid coding system to identify distinct concepts
and ideas. The codes were organized into broader themes to structure the findings. The analysis was
iterative, allowing for refinement of the themes to ensure alignment with the data and study objectives.
Responses
A total of 834 survey responses were received, 264 of which included answers to at least one open-ended
question. Because only the open-ended questions in the questionnaire focused on AMI, only these 264
responses were included in the analysis. Participants were asked to select the roles or perspectives they felt
applied to them and could choose multiple options, which included:
Lived experience of housing instability or homelessness
Service provider to people who struggle with homelessness or housing instability
Housing assistance program manager or staff
Affordable housing developer or administrator
City or county government employee
State government employee
Elected or appointed official
Public Housing Authority (PHA) employee
Community advocate or another member of the public
Tribal representative
Other
Exhibit 43 shows the number of times survey respondents selected each category. Most respondents (62%)
selected more than one option. Based on these connections, we grouped our analysis into four key categories:
affordable housing developers, government officials, affordable housing operators and service providers, and
community members and people with lived experience of housing instability or homelessness.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 54
Exhibit 43. Roles and perspectives
Service provider 130
Lived experience of housing instability or homelessness 118
Housing assistance program manager or staff 86
Community advocate or member of the public 77
Affordable housing developer or administrator 61
City or county government employee 54
State government employee 15
Public housing authority employee 11
Elected or appointed official 6
Tribal representative 1
Other 84
0 20 40 60 80 100 120 140
Source: BERK, 2025.
People were asked to select the county where they lived and/or did most of their work to address housing
needs based on their responses to the roles and perspectives question. Exhibit 44 shows the locations
selected by respondents, highlighting that the highest number of responses came from the most populous
counties, while some counties had no respondents.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 55
Exhibit 44. Primary county for housing work or county of residence
County Primary Cou nty for Ho using W ork or County o f Resi denc e
Adams Cou nty 0
Asotin Coun ty 0
Benton Coun ty 1
Chelan Coun ty 4
Clallam Cou nty 8
Clark County 21
Columbia County 0
Cowlitz Coun ty 5
Douglas County 1
Ferry County 1
Franklin County 1
Garfield Coun ty 0
Grant Coun ty 1
Grays Harbor County 5
Island County 8
Jefferson Coun ty 7
King County 70
Kitsap Coun ty 10
Kittitas County 3
Klickitat Coun ty 1
Lewis County 0
Lincoln County 0
Mason County 2
Okanogan Coun ty 3
Pacific Coun ty 0
Pend Oreille Coun ty 0
Pierce County 17
San Juan Co unty 1
Skagit County 6
Skamania Coun ty 0
Snoho mish County 19
Spokane Coun ty 21
Steve ns County 2
Thurston County 15
Wahkiakum County 1
Walla Walla County 2
Whatcom Co unty 8
Whitman Cou nty 3
Yakima County 6
Source: BERK, 2025.
Interviews
Goals
Interviews were designed to explore and expand upon the information gathered through the survey and
advisory committees by engaging with individuals whose work could be impacted by changes to AMI and
those with experience in housing assistance programs.
Process:
Participants were selected based on a combination of input from advisory groups, survey responses,
and the study team's knowledge of interested parties that would be impacted by a change in AMI. This
approach ensured that the selected participants were well-aligned with the project’s requirements and
research questions, providing valuable insights from a diverse pool of individuals.
The project team conducted semi-structured interviews, allowing participants to respond to a set of
core questions while also encouraging them to elaborate and share additional insights. Interviews were
held via Microsoft Teams. With participants' consent, most interviews were transcribed for detailed
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 56
analysis. Some interviews included multiple participants from the same organization, as shown in
Exhibit 45.
Exhibit 45. Interview participants
Name Organization Geography Perspective represented
TyeRae Guined Commerce HD Multifamily Housing Statewide Funding program manager
Unit
Wubet Biratu Washington State Housing Finance Statewide Housing finance
Lisa Vatske Commission
Jackie Moynahan
Emily Thompson GMD Development, LLC WA, ID, MT, AK For-profit rental housing developer
Conor Hansen SRM Development Western US For-profit rental housing developer
Rachael Simpson Bellwether Housing Executive King County Non-profit rental housing developer and operator
Susan Boyd Director
Ann Melone US Bank WA + Western Tax credit investor
US
Kaylin Bettinger Upper Valley MEND Leavenworth Non-profit service provider, community land
area trusts, and rental housing manager.
Chris Lambert Catholic Charities Housing Services Yakima County Service provider
Heather Blough Housing Kitsap Kitsap County Service provider
Michelle Gladstone-Wade Commerce Office of Tribal Statewide Tribal housing needs
Alden Andy Relations
Lynda Jensen
Mary Miller
Alyson Moon Mary's Place King County Service provider
Miriam Clithero
Hannah Miyagishima
Jessica Safley
Elizabeth Archambault Seattle Lived experience
Joy Hunt Black Home Initiative Seattle Lived experience
Sharon Lee Low Income Housing Institute Puget Sound Non-profit housing developer and manager
John Torrence
Jon Grant
Dennis Sills Plymouth Housing King County Non-profit housing developer and manager
Chris Mack
Elliot Hart
Timeline
Exhibit 46 shows the timeline of engagement activities. The project kicked off in early November. The survey
took place between early December and mid-January. Interviews occurred in January and February. The
Internal Advisory Workgroup met four times between November and March, while the Advisory Committee met
three times between December and March.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 57
Exhibit 46. Timeline of engagement activities
Findings
Given the urgency and complexity of the affordable housing crisis in Washington, questions about housing
often provoke a wide range of responses. As a result, perspectives on AMI methods shared by interview and
survey participants were frequently intertwined with broader issues surrounding the effectiveness of the
state's affordable housing system. This summary of findings prioritizes responses related to current and
alternative AMI calculation methods while acknowledging the broader insights shared, which contribute to a
more holistic understanding of the housing landscape.
Financial feasibility of affordable housing production
Several survey respondents and interviewees highlighted that the current AMI calculation and associated
income limits provide a predictable and consistent framework for determining eligibility for housing assistance
and the rent for affordable units. Financial feasibility was a concern expressed primarily by affordable housing
developers, government officials, and affordable housing operators and service providers. According to
affordable housing developers, this predictability benefits developers and funders by offering clear guidelines
for project planning, financing and ensuring compliance. They have also claimed that HUD's AMI is relatively
easy to administer and well-understood by interested parties.
Government officials, affordable housing developers, operators, and service providers also mentioned
integrating income limit requirements across different funding sources. One government official from the City
of Everett stated that:
"Using HUD MFI-based limits allows Everett's programs to integrate federal and state resources more easily. As
many funding sources already require or reference HUD metrics, adhering to these standards streamlines the
blending of multiple funding streams-such as CDBG, HOME, and state grants-into a single project. This synergy
ensures that local affordable housing initiatives can be efficiently financed and that developers, nonprofits, and
service providers know what to expect."
One developer, reflecting on the costs associated with different AMI calculations, shared that:
"Administrative consistency with language, rent standards, etc., is critical — we cannot afford to waste more money
on administrative process to manage the differences between the various funding sources (sometimes 6 in a given
project). The HUD-based system is one that everyone understands."
Affordable housing operators and service providers echoed that perspective. One respondent highlighted the
challenges of releasing a recent RFP with two funding sources, each with different income determinations,
making it difficult to educate applicants and allocate funds. Another participant pointed out that the United
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 58
States Department of Agriculture (USDA) uses a different AMI figure than the state, causing conflicts for
homebuyers qualifying for USDA programs but not for state programs, particularly downpayment assistance.
However, challenges arise as rents for affordable housing units increasingly align with market rates,
particularly in areas with relatively low market rents and high AMI, leading to competition between subsidized
and market-rate housing. Affordable housing developers, operators, and service providers have encountered
challenges in filling certain units, particularly those at the 60% AMI level, which compete directly with market
rents. This can hinder the development and operation of affordable housing units, as tenants may opt for
market-rate units to avoid the bureaucratic complexities often associated with subsidized housing. The
solutions proposed by affordable housing developers, operators, and service providers include more gap
funding and operational subsidies, which may limit the number of units jurisdictions can produce or lead to the
concentration of affordable housing projects in areas where gap funding is more accessible, impacting the
geographic distribution of affordable housing.
The finding that while some households qualify for housing assistance, they can also afford market-rate rents
suggests that assistance may not be effectively reaching those in greatest need. Affordable housing
developers, operators, and service providers, as well as community members and people with experience of
housing instability or homelessness, emphasize the need to serve households at lower income levels, such as
30% and 40% AMI, but highlight that resources to serve those income limits are limited. One affordable
housing developer, operator, and service provider mentioned that some failures with Permanent Supportive
Housing (PSH) projects have led to stricter policy and increased reluctance when investing in these kinds of
housing projects. They also mentioned that units targeting households within these income limits, along with
larger units, are generally easier to fill and retain due to their limited availability relative to need. However,
many pointed out that achieving this goal requires additional funding and long-term subsidies.
Affordable housing developers, operators, and service providers mentioned that shifting to an alternative AMI
could introduce uncertainty or resistance among funders and investors who value the predictability and
simplicity of the federal standard. One interviewee highlighted the important role of LIHTC tax credit investors,
who often work across state lines and can be risk-averse. Changing the AMI could increase the perceived risk
for these investors, especially as smaller developers and operators may face challenges with the added
complexity and associated costs. Additionally, some claimed that introducing a new AMI calculation method
would lead to an administrative burden, increase costs, and potentially limit the number of affordable housing
units that can be built and operated due to the additional compliance requirements. One affordable housing
operator and service provider explained that their Community Land Trust’s homeownership program ties the
future resale price of a home to the increase in AMI over time. If AMI were calculated differently, the
appreciation model within their homeownership program could be altered. Additionally, their rental program
determines monthly rent and income qualifications based on AMI, meaning any changes in the calculation
method could affect their business model and the pool of community members who qualify. With very narrow
margins, such changes could significantly impact their long-term sustainability.
Program management feasibility
Several survey respondents and interviewees emphasized that AMI provides consistent, readily available, well-
documented data widely utilized by federal, state, and local governments, housing authorities, researchers,
investors, and developers. This was one of the key benefits of the current AMI calculation method, according
to affordable housing operators and providers, developers, government officials, community members and
people with experience of housing instability or homelessness.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 59
This consistency can have varying impacts on different people. One individual with experience stated that the
transparency and wide availability of HUD's AMI provide tenants with a sense of housing stability, as they will
know their rent amount each month and year. According to them, using HUD's AMI can:
"reduce organizational/ administrative costs by having a standard that program staff can simply plug into their
budgets as well as allowing qualified tenants in the program knowledge of what their rent will be as it is based on a
federal government standard and not the direct decision of each individual non-profit housing organization."
Government officials emphasized that relying on HUD's AMI eliminates the need for municipalities to establish
or justify their own income benchmarks. One of them, from the City of Everett, highlighted that:
"the alignment with a federally recognized standard simplifies local program administration, ensuring that Everett's
staff can focus on effectively delivering services rather than recalculating income limits. It also helps maintain
consistency across different projects and funding streams, minimizing confusion for both staff and applicants."
Study participants also highlighted that using HUD's AMI reduces the perception of arbitrary or politicized
decision-making by showing that eligibility thresholds are derived from a well-established federal calculation.
This transparency can bolster trust among residents who want to understand why they do or do not qualify for
assistance. Respondents also emphasized that having a patchwork of AMI calculations across jurisdictions
and programs would complicate efforts to compile meaningful progress indicators and assess the impact of
investments on housing affordability. One government official mentioned that using alternative AMIs would
complicate data compilation for Consolidated and Annual Action Plans, making it harder for HUD reviewers to
evaluate these submissions. Additionally, local jurisdictions are required by the Growth Management Act to
document housing affordability goals in their comprehensive plans. Housing affordability goals are quantified
based on units affordable to households at specified income levels derived from HUD’s AMI. Another
government official noted that county-level income data from the American Community Survey 5-Year
Estimates were used in a previous report. However, when the county compiled a database of income-restricted
units in the area, the affordability of these projects was based on HUD's AMI. This made it difficult to compare
the data directly to the housing goals in the report. In summary, variations in AMI calculations can complicate
the process of documenting and tracking goals.
Several affordable housing operators and service providers echoed this perspective, emphasizing that many
housing programs are required to use HUD's income limit standards, and adding other standards could lead to
confusion. Therefore, adopting a new AMI at the state level would likely have a limited impact or complicate
programs with multiple funding sources. According to one of them:
"We often layer in funding from a federal source, so would be bound by using HUD MFI when using those funds. It
can also be challenging to do outreach about our program if there are different income limits for different
opportunities."
On a related note, an interviewee from an organization supporting individuals experiencing homelessness
noted that variation between funders in terms of income limits would increase the potential for mistakes in
referrals from the Coordinated Entry system, potentially leading to public relations challenges and aggravating
the bureaucratic burden imposed on someone experiencing homelessness and seeking emergency
assistance. Because many funding sources already reference HUD metrics, adhering to these standards
simplifies blending multiple funding streams into a single project. Additionally, respondents noted that
changing the geographic boundaries for AMI could require program managers to oversee multiple districts,
complicating their compliance and performance analysis responsibilities. Managers would need to conduct
separate market and performance analyses for each area while maintaining distinct rent and income
guidelines for every district. This complexity could make it difficult for providers and the public to understand
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 60
the appropriate AMI and rent levels. As a result, ongoing training and support for those implementing these
changes would be essential.
Alignment between AMI and local incomes
A common theme expressed by respondents from all groups is concerns about the mismatch between AMI
and the financial realities of local communities across the state. Some survey respondents and interviewees
noted that the annual updates to AMI may fail to keep pace with rapid shifts in the housing market, resulting in
outdated eligibility criteria. Affordable housing developers, operators and service providers observed that, in
some cases, AMI fails to reflect local income trends. Sometimes, it remains flat while incomes change; other
times, incomes grow faster than AMI, and at other points, AMI experiences significant increases relative to
income, such as a 20% jump, as noted by one person. Overall, these respondents expressed that AMI remains
an imperfect tool, often failing to capture the complexity of local economic conditions.
Eligibility for housing assistance
Community members and people with experience living in affordable housing, as well as affordable housing
operators and service providers, highlighted that AMI is too low in some locations, causing families in need,
including those living on minimum wage or social security income, to be disqualified despite being unable to
afford housing in the broader market. According to a service provider, one of the challenges associated with
the current AMI calculation method is that it:
"May disqualify folks who are homeless with income but can't get approved to rent a unit on their own. They may
make too much to be eligible for a program or subsidy, but they don't make enough to get approved to rent a unit on
their own."
On a similar note, a person with experience living in affordable housing argued that:
"Some challenges of using income limits based on HUD MFI to base program eligibility on include not being able to
serve folks who hold low wage jobs with income that is above the HUD standard but not sufficient to compete for
market rate housing."
The risk for low-income households reliant on housing programs can be significant. One person with
experience shared a cautionary tale of a small change in income jeopardizing one's housing situation:
"Fear of receiving $1 too much income and losing KCHA.31 That situation happened to a friend. Earning $1 more than
allowed income isn't enough income to pay rent, household expenses, food, car/transportation expenses, etc."
Respondents from all groups emphasized that AMI is skewed upward in areas with high-paying industries, like
the tech sector, making it an unreliable benchmark for understanding the economic reality of those with
incomes at the lower end of the spectrum. According to a government official:
"The AMI is an issue in our county where our income gaps continue to grow and our trends show spiking poverty yet
a 12% increase in income, which implies that there are people moving to the area with very high incomes. These few
individuals negatively influence our housing market yet are guiding it, continuing to bolster a market for very
expensive houses and shifting our entire market upwards."
A developer claimed that AMI could be a misleading metric due to people who live in lower-income counties
but work in a higher-income neighboring county. Hence, relying solely on AMI to assess the financial
conditions of an area may ignore important nuances of cross-county economic dynamics, potentially leading
to another source of disconnect between AMI and the local economic reality. According to government
31 Referring to King County Housing Authority benefits.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 61
officials, this issue is further exacerbated by the fact that the AMI calculation encompasses all socioeconomic
groups, including homeowners, who typically have higher incomes than renters. This often results in income
limits that are too high for low- and moderate-income households, making them ineligible for housing
assistance programs. Conversely, because AMI levels for homeownership programs are skewed lower by the
inclusion of renter incomes, it becomes challenging to identify potential homebuyers with low enough incomes
to qualify yet still earn enough to secure a primary mortgage.
To tackle affordability constraints, a few affordable housing developers, operators, and service providers
highlighted efforts to charge below the rent limit set by AMI or to use the current AMI when developing pro
formas,32 rather than relying on the AMI projected at the time of project completion. They argued that providers
should not be penalized for addressing the needs of lower-income households (who may have income
somewhat below the HUD income limit) but instead should receive increased subsidies for meeting that
demand.
Housing cost burden
The cost burden among those who qualify for affordable housing programs was an issue of concern for all
groups. According to a service provider, income limits don’t adequately support lower-income households in
high-cost areas like King County. The AMI used in the area often leads to housing costs that take up 40-60% of
applicants' income, causing unnecessary housing instability and higher eviction rates. Reflecting on the high
likelihood of rent burden among tenants in affordable housing programs using the current AMI method, a
government official mentioned that:
"It is really problematic that we use a maximum AMI to calculate eligibility, but then we use that AMI to charge rents.
That means that literally every household in an affordable unit will still be rent-burdened (unless a buffer is used in
eligibility during lease renewal, as some jurisdictions allow)."
Household size adjustments
Another challenge highlighted by community members and people who have lived in affordable housing,
government officials, and affordable housing operators and service providers stems from the idiosyncrasies
in how AMI is adjusted based on household size. HUD’s published AMIs by household size can differ
significantly from actual income patterns within a community. The stair-stepping formulas HUD uses to adjust
AMI for various household sizes can be problematic, particularly for large and single-parent households. For
instance, in many communities, larger families often have lower incomes than smaller households. Similarly,
even among households of the same size, single-parent households tend to earn less than two-parent
households. According to a government official:
"Maximum rents in income-restricted units of different unit sizes are commonly based on the AMI for household
sizes assumed by formula to occupy the specific sized units, with larger units naturally assumed to be needed for
larger families. However, the assumption inherent in the HUD AMIs that incomes continue to increase with each
additional household member beyond 4 has the perverse effect of increasing maximum allowable rents for the larger
housing unit sizes best suited to larger families even though families with more than four people often have lower
incomes."
Perspectives on geographic areas used for MAI calculation
With respect to the geographic boundaries used in AMI calculations, respondents from all groups also
emphasized that the current geographic areas used for HUD's AMI fail to reflect the differences in income and
market conditions, including those between urban and rural areas. A developer highlighted, "The numbers can
32 In construction, a pro forma is a financial model that projects a project's potential profitability and/or cash flow over time.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 62
be inflated, especially for others in the rural areas, as the metrics used are based on urban area statistics."
Many examples were provided. A government official said that:
"A major challenge of using income limits based on HUD MFI is that HUD uses the same income limits throughout
the Seattle-Bellevue, WA HUD Metro Fair Market Area, which is quite large. Although housing is regional, different
areas of this region have different concentrations of income levels and the region's housing market does have sub-
markets based on various characteristics of the community."
One respondent highlighted that Clark County, when combined with Multnomah County, results in a local AMI
that is substantially different from what it would be if the county were considered independently. It was also
mentioned that Bremerton has the lowest median income in Kitsap County, so HUD's AMI results in relatively
high rents for the area. In contrast, Sequim has a higher AMI due to the influx of retirees, skewing the
affordability calculations for that region. Government officials and affordable housing developers, operators,
and service providers mentioned using smaller geographies as a potential strategy for more accurately
aligning. According to them, this shift could lead to a better alignment with local income distributions and
housing market conditions, especially in high-cost or economically diverse regions.
Other respondents argued that the current geographic scales are appropriate, considering that housing search
may have a regional scale. A government official, for example, mentioned that:
"folks looking for affordable housing often have to look in a wide area, so it is convenient to have the MFI calculation
match that wide area as well so that they can do the calculation once."
Others noted that eligibility and affordability should reflect the needs of those who work in the area. If income
limits are based on city boundaries or smaller geographic areas, they may be set too high or too low to benefit
the local workforce (who may live across the region), and instead only serve people who reside in the area.
Perspectives on alternative AMI calculation methods and eligibility assessments
Regarding the adoption of a new AMI calculation method, affordable housing developers, operators, and
service providers emphasized the importance of clearly defining the purpose of the change, as each
benchmark used to calculate AMI will inevitably include or exclude specific individuals. If the goal is to
increase the number of qualifying individuals, it could exacerbate the rent burden if the underlying affordability
issue is not properly addressed. On the other hand, if the goal is to make housing more affordable, achieving
this may require additional subsidies, which could reduce the overall number of available units (due to limited
funding), rather than simply expanding access.
As an alternative, affordable housing developers, operators, and service providers emphasized that the
current AMI calculation method may not require a complete overhaul. Instead, adjusting the targeting for
different programs could more accurately reflect the realities that those needing assistance face. For instance,
they argued that relying on the default use of 60% or 80% AMI as the benchmark for rental housing affordability
is problematic, as it fails to account for the wide variation in economic profiles across different localities.
Introducing a new AMI method may not be necessary if government staff and elected officials better
understand how to align income limits with the most pressing housing needs and avoid rent burden.
Others have proposed potential adjustments to a household’s income assessment when determining
eligibility. Respondents of all groups recommend incorporating cost-of-living factors, such as childcare
expenses, into eligibility requirements to create a more equitable system and ensure that those most in need
are properly served. These additional costs disproportionately affect lower-income families, with many
households in affordable housing programs continuing to struggle with rent burden. Others suggested
including exemptions for specific groups, such as individuals with intellectual and developmental disabilities.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 63
Appendix B. Literature review
Overview of AMI calculation methodology
Area Median Income (AMI) is a term that refers to the calculation of the midpoint of the income distribution in
a specific geographic area. This means that half of the family households in the area have an income greater
than AMI, and half have an income less than AMI. Within the affordable housing industry, the term AMI is
synonymous with the U.S. Department of Housing and Urban Development (HUD) Median Family Income
(MFI). HUD calculates MFI annually for individual counties and multi-county metropolitan areas.
This section details the calculation of HUD MFI. It is organized into three parts. First, we describe the
geographic areas that HUD uses to estimate MFI. Next, we describe the source data. Finally, we describe
adjustments to account for inflation.
Geographic areas used for calculating HUD MFI
While HUD publishes estimates of MFI for all individual counties in Washington, the geographic area used to
calculate those MFI values varies. HUD uses three different area types for calculating MFI, which are defined
below. Exhibit 47 shows the geographic boundaries used for all HUD MFI calculations in Washington.
Metropolitan statistical area (MSA)
These are areas defined by the Census. They include a core city or population center and adjacent
communities that have a high degree of economic and social integration with the core. MSA boundaries are
based on county boundaries. An MSA (shown in orange in Exhibit 47) can be composed of a single county or
multiple counties combined. In some cases, MSAs cross state boundaries, as is the case for the Portland-
Vancouver-Hillsboro, OR-WA MSA.
HUD Metropolitan Fair Market Rent Areas (HMFA)
HUD divides some MSAs into smaller areas called HMFA. The Seattle-Tacoma-Bellevue, WA MSA is an
example of this. HUD divides it into two HMFAs: Seattle-Bellevue, WA HMFA and Tacoma, WA HMFA. These
areas are shown in purple in Exhibit 47.
Non-metropolitan counties
These are counties that are not included in an MSA. Typically, these are mostly rural counties without a large
city. Washington has 20 non-metropolitan counties, shown in grey in Exhibit 47.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 64
Exhibit 47. MSAs, HMFAs, and non-metropolitan counties used for HUD MFI
calculations
Area Na me Type
Adams Cou nty, WA Non-Me tropoli tan Coun ty
Bellingham, WA MSA Metropolitan Statistical Area
Bremerton -Sil verdale, WA MSA Metropolitan Statistical Area
Clallam Cou nty, WA Non-Me tropoli tan Coun ty
Columbia County, WA Non-Me tropoli tan Coun ty
Ferry County, WA Non-Me tropoli tan Coun ty
Garfield Coun ty, WA
Non-Me tropoli tan Coun ty
Grant Coun ty, WA Non-Me tropoli tan Coun ty
Grays Harbor County, WA Non-Me tropoli tan Coun ty
Island County, WA Non-Me tropoli tan Coun ty
Jefferson Coun ty, WA Non-Me tropoli tan Coun ty
Kennewick -Richla nd, WA MSA Metropolitan Statistical Area
Kittitas County, WA Non-Me tropoli tan Coun ty
Klickitat Coun ty, WA Non-Me tropoli tan Coun ty
Lewis County, WA Non-Me tropoli tan Coun ty
Lewiston, ID-W A MSA Metropolitan Statistical Area
Lincoln County, WA Non-Me tropoli tan Coun ty
Longview, WA MSA Metropolitan Statistical Area
Mason County, WA Non-Me tropoli tan Coun ty
Mount Vernon -Anacortes, WA MSA Metropolitan Statistical Area
Okanogan Coun ty, WA Non-Me tropoli tan Coun ty
Olympia-Tu mwa ter, WA MSA Metropolitan Statistical Area
Pacific Coun ty, WA Non-Me tropoli tan Coun ty
Pend Oreille Coun ty, WA Non-Me tropoli tan Coun ty
Portland -Va ncouver -Hillsboro, OR-W A MSA Metropolitan Statistical Area
San Juan Co unty, WA Non-Me tropoli tan Coun ty
Seattle -Bellevue , WA HUD Metro FMR Area HUD Metropoli tan Fair Market Rent Area
Spokane, WA HUD Metro FMR Area HUD Metropoli tan Fair Market Rent Area
Steve ns County, WA HUD Metro FMR Area HUD Metropoli tan Fair Market Rent Area
Tacoma, WA HUD Metro FMR Area HUD Metropoli tan Fair Market Rent Area
Wahkiakum County, WA Non-Me tropoli tan Coun ty
Walla Walla, WA MSA Metropolitan Statistical Area
Wenatchee, WA MSA Metropolitan Statistical Area
Whitman Cou nty, WA Non-Me tropoli tan Coun ty
Yakima, WA MSA Metropolitan Statistical Area
Source: HUD, 2024.
Source data
The calculation of HUD MFI by geographic area is based on median family income estimates published by the
U.S. Census American Community Survey (ACS). To understand what these estimates represent, it is
important to remember three key definitions:
1. Median: Median is a statistical term for the midpoint of a series of numbers, such as household
incomes. It is different from the average. While a few extremely high-income households can skew the
average income in an area, the median household income would not be skewed. Half of all households
have an income higher than the median, and half of all households have an income lower than the
median.
2. Family household: The Census defines a family household as a group of people living together who are
related by birth, marriage, or adoption.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 65
3. Family income: According to the Census, family income includes “money income received on a regular
basis […] before payments for personal income taxes, Social Security, union dues, Medicare deductions,
etc.,” received in the past 12 months.33
Census American Community Survey (ACS)
The ACS is an ongoing survey of households. It collects demographic and socioeconomic information,
including information about household characteristics and family income. More than 3.5 million households
are surveyed each year. The Census Bureau uses the information collected in the ACS to estimate median
family income for various geographies.
HUD uses the most recent ACS survey results available to calculate MFI. Although HUD receives a custom
data set from the Census Bureau, its data is based on the publicly available ACS data set, “B19113 Median
Family Income in the Past 12 Months.” The Census publishes ACS data in two different varieties. The one-year
ACS estimates are based on 12 months of survey responses, whereas the five-year ACS estimates are based
on five years of responses. Compared to one-year estimates, five-year estimates have a greater sample size
and therefore have a smaller margin of error. However, the survey responses for five-year estimates are
collected over a longer period of time and, therefore, may not reflect recent changes in conditions. HUD selects
either the one-year or five-year ACS estimate for MFI calculation, depending on the reliability of the one-year
estimates. For larger counties, MSAs, and HMFAs, the one-year ACS estimates are reliable enough due to the
larger sample used by the Census to create their estimate. For smaller counties, HUD instead uses five-year
ACS estimates.34 See Exhibit 48 below for a listing of areas by ACS estimate used. The reliability thresholds
are described in HUD's Methodology for Calculating FY 2024 Medians.
Exhibit 48. ACS estimate used for calculating HUD MFI, by calculation area35
Counties where the 1-year ACS estimate is used:
Asotin County36
Bellingham, WA MSA
Clallam County
Garfield County
Grant County
Grays Harbor County
Island County
Kennewick-Richland, WA MSA
Lewis County
Lewiston, ID-WA MSA
Longview, WA MSA
Mason County
33 Family income does not include irregular income, such as gifts or capital gains, and noncash benefits, such as food stamps, health
benefits, subsidized housing, and goods produced and consumed on a farm (US Census Bureau, 2021).
34 For the FY 2024 MFI calculations, HUD requires that the margin of error for the ACS estimate be less than half of the value and that
the estimate be based on at least 100 responses. For details, see HUD's Methodology for Calculating FY 2024 Medians. For FY 2024
and 2023, HUD used an alternative methodology for Garfield County as neither the one-year nor five-year ACS estimate met the
reliability threshold.
35 For HUD FY2024 and 2023, HUD used an alternative methodology for Garfield County as neither the one-year nor the five-year ACS
estimate met the reliability threshold. Source: Methodology for Calculating FY 2024 Medians (HUD, 2024).
36 2024 was the first year that Asotin County used a one-year ACS. Previously, the one-year ACS estimate was not available, and a five-
year ACS estimate was used.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 66
Mount Vernon-Anacortes, WA MSA
Olympia-Tumwater, WA MSA
Portland-Vancouver-Hillsboro, OR-WA MSA
Seattle-Bellevue, WA HMFA
Spokane, WA HMFA
Tacoma, WA HMFA
Wenatchee, WA MSA
Yakima, WA MSA
Counties where the five-year estimate is used:
Adams County
Columbia County
Ferry County
Jefferson County
Kittitas County
Klickitat County
Lincoln County
Okanogan County
Pacific County
Pend Oreille County
San Juan County
Stevens County, WA HMFA
Wahkiakum County
Walla Walla, WA MSA
Whitman County
Consumer Price Index (CPI)
To project the historical ACS estimate of MFI forward to the current year, HUD assumes that incomes rise at
the same rate as inflation, as measured by the CPI-U.37 More specifically, HUD uses the change in CPI-U from
the year the ACS survey was completed to the year the income limits are released. For example, the income
limits for 2024 use the 2022 ACS data. The 2022 ACS data is trended forward to 2024 using the change in CPI-
U from 2022 to 2024. However, because the 2024 CPI is not known when HUD publishes the income limits for
2024, HUD used the Congressional Budget Office's (CBO) estimate of CPI as the CPI for 2024. See Exhibit 49
for an example.
Exhibit 49. HUD MFI calculation for Spokane, WA HMFA
𝟐𝟎𝟐𝟐 𝟏 𝐘𝐞𝐚𝐫 𝐀𝐂𝐒 𝐌𝐅𝐈 × 𝟐𝟎𝟐𝟒 𝐂𝐏𝐈 − 𝐔
= 𝟐𝟎𝟐𝟒 𝐇𝐔𝐃 𝐌𝐅𝐈
𝟐𝟎𝟐𝟐 𝐂𝐏𝐈 − 𝐔
$𝟗𝟒, 𝟑𝟏𝟗 × 𝟑𝟏𝟎. 𝟔𝟖𝟑
= $𝟏𝟎𝟎, 𝟏𝟒𝟑
𝟐𝟗𝟐. 𝟔𝟏𝟑
Note: The calculation is rounded to the nearest $100 for a HUD MFI of $100,100.
Source: Methodology for Calculating FY 2024 Medians (HUD, 2024).
37 CPI-U refers to the Consumer Price Index for All Urban Consumers. It is published by the US Bureau of Labor Statistics.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 67
Historical changes to HUD AMI calculation
HUD has made several refinements to its AMI methodology over the years. Before the introduction of the ACS,
HUD relied on the decennial (10-year) census data to receive survey information about the incomes of
households in each area in the country. However, that data was updated only once every ten years. To account
for this infrequency, HUD would adjust the decennial census data using a combination of Bureau of Labor
Statistics and employment data. HUD's statistics and data over the years changed, but the methodology
remained the same. The methodology used each year can be found in the HUD Briefing Material on
HUDuser.gov. Below is a summary of this information.
When the 2000 decennial census was released, it became apparent that using large-scale survey data through
the census, which was only updated once every 10 years, was causing gross overestimations in income limits
for the interim years. In an attempt to calculate more accurate limits, HUD began trying to incorporate ACS
data in 2005 when it first became available.
Because the ACS data was new, HUD applied a cautious approach and implemented the change to ACS data
from the decennial census over time. HUD stated the following in its 2007 briefing material:
“The ACS MFI estimates have significantly larger margins of error than decennial Census estimates of MFIs and
often produce lower estimates, so HUD will implement ACS results with some caution. HUD’s objective is to
minimize the possibility of publishing income estimates with annual changes driven more by survey error than
changes in underlying economic conditions.”
In 2007, HUD began using ACS data for areas with populations greater than 65,000 to calculate the increase in
median family income from the 2000 census to the applicable ACS year. For example, in 2007, HUD utilized the
2005 ACS data. To account for the time between the 2005 ACS data and 2007, HUD applied an annual 3.5%
trend factor to account for inflation. The 3.5% trending factor was used for all areas. For areas with
populations of less than 65,000, HUD continued to use the 2000 Census updated to the income year using
Bureau of Labor Statistics (BLS) statistics, state-level ACS information, and a 3.5% trend factor. At this point in
time, ACS was only publishing one-year data; therefore, all calculations used one-year ACS data, regardless of
statistical reliability.
In 2009, HUD updated its methodology to use ACS data for areas with populations of 20,000 or more and
updated its trend factor to 3.0%. HUD was also able to use three-year ACS estimates, as three years of ACS
data were now available. In the FY 2010 HUD Income Limits Briefing Material, HUD provided more context on
why they used the three-year ACS estimate:
“HUD uses three-year estimates to dampen the impact of year-to-year fluctuations in ACS measured MFI on
programs relying on these parameters. These fluctuations are primarily, but not exclusively, observed in areas where
the margin of error estimates for the ACS data are large. In these areas, fluctuations in measured median income are
far more likely to be caused by sampling errors. The three-year ACS data have much smaller margins of error
because the number of observations in three-year estimates is three times the number of observations in one year
estimates.”
Beginning in 2009, HUD also discontinued using BLS statistics as part of its trending factor. Instead, it relied on
state-level ACS information and a 3.0% trend factor to update the 2000 Census Data.
In 2011, HUD began using five-year ACS data, which was first published in 2010. Because the five-year ACS
data were available for most geographic areas, HUD discontinued using the 2000 Census Data. HUD continued
to use a 3% trend factor. If an area had a reliable one-year ACS estimate, HUD would incorporate the one-year
ACS estimate.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 68
In 2012, HUD used the same ACS data as in 2011 but added a two-step trend factor. First, the 2009 ACS data
were trended forward from 2009 to 2010 using the change in CPI from 2009 to 2010 and then trended to 2012
using a 3.0% trend factor.
The methodology for 2013 remained largely unchanged, except that the trend factor was updated to 1.0166,
which “was calculated as the annualized change in national median family income as measured by the 2005
One-Year ACS and the 2010 One-Year ACS.” (HUD, 2013) HUD would use similar methodologies to update the
trend factor for 2014 (0.98%).
In the 2015 methodology, HUD again revisited the trend factor:
“In calculating the FY 2015 MFI estimates, HUD decided to replace the trend factor based on the annualized change
in national median family income over the last five years because the Department determined this was no longer a
reasonable expectation of upcoming income growth. Consequently, the Department incorporated a CPI forecast
from CBO into the process in order to account for anticipated income growth over the next year. For FY 2015, MFI
estimates based on the 2012 ACS data (the middle of 2012) are inflated to the mid-point of FY 2015. The CBO
projection of CPI, published in August 2014, is used to inflate the 2012 data.”
This started a long period with no changes to the HUD MFI methodology. Between 2015 and 2022, HUD MFI
was calculated by taking three-year-old ACS data and trending data forward to the income limit year. It used a
trend factor of the CBO estimate of CPI for the income limit year, divided by the CPI for the ACS year.
In 2020, due to COVID, the US Census Bureau could not produce reliable one-year ACS data. The 2020 ACS
would have typically been used for the 2023 HUD MFI estimates. In response to the lack of ACS data, HUD
updated its methodology to use the 2021 ACS data, a two-year lag as opposed to the typical three-year lag.
The CPI update factor methodology remained the same (CBO estimate of CPI for the income limit year/CPI for
the ACS year); however, because the ACS data was only two years old, the CPI factor only covered two years.
HUD used the same methodology for 2024 and has informally indicated it does not anticipate changing
methodologies for 2025.
Limitations of HUD MFI
HUD’s MFI is not a perfectly accurate estimate of median family income. HUD’s methodological choices can
significantly impact MFI calculations for areas across Washington. Here, we focus on two methodological
choices and discuss their implications. The first choice is estimating the selection of geographic boundaries.
The second choice is the rate of income inflation.
Geographic boundaries
One issue impacting HUD MFI is the geographic boundaries selected by HUD for its calculations. Incomes vary
significantly across the state, as well as within individual counties. Because HUD calculates MFI on a county,
MSA, or HMFA basis, the income limits cover large areas that may have communities with different incomes
than the rest of the county or area. This is particularly notable in larger metropolitan regions with wide
household income disparities. It can also impact non-MSA counties, where incomes in some cities may be very
different than those in rural areas of the county.
Exhibit 50 provides an example of these disparities in the Seattle-Bellevue, WA HUD Metro FMR Area, where
the HUD MFI was $147,400 in 2024. When applying the same calculation methodology at the city level, we see
considerable variance from HUD's MFI. MFIs by city range from an MFI nearly $43,000 lower than the HUD MFI
(see Kent) to an MFI $41,400 higher than the HUD MFI (see Seattle).
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 69
Exhibit 50. Comparison of city-level MFI to Seattle-Bellevue, WA HMFA MFI
($147,400)
City 2024 MFI Variance from Seattle-Bellevue, WA HMFA MFI
Bellevue 188,100 40,700
Burien* 105,900 -41,500
Carnation* 159,100 11,700
Edmonds* 151,000 3,600
Kent 104,600 -42,800
Renton 128,700 -18,700
Seattle 188,800 41,400
Another issue related to geography is variation in market rents. In counties with widely varying market
conditions, affordable housing rents based on income limits derived from AMI may be far below market rents
in one city while close to or even higher than market rents in another city.
One potential solution to these issues would be calculating income limits for smaller areas based on
alternative geographic breakdowns. While this may result in an income limit that is more reflective of the
income of households that live in smaller areas, data limitations with the ACS may result in income limits with
a larger margin of error and are more variable from year to year.
In the Assessment of Small Area Median Family Income Estimates published in 2018, HUD evaluated the
feasibility of calculating income limits at a smaller geographical footprint. HUD focused on three more
granular geographic area types: County, ZIP Code Tabulation Area (ZCTAs), and Census Tract. If HUD used the
same threshold for determining the reliability of ACS estimates (defined as having a margin of error less than
50% of the estimate and receiving at least 100 survey responses), 100% of metropolitan counties, 67% percent
of metropolitan ZCTAs, and only 29% of metropolitan census tracts had statistically reliable estimates. This
analysis was only conducted in MSAs. In non-metro areas, it is likely that an even lower percentage of ZCTAs
or Census Tracts would be deemed to have statistically reliable estimates.
In their report, HUD discussed a few additional issues with using smaller geographies:
An increased administrative burden on Public Housing Authorities (PHA) and other users of published
MFI and income limits: HUD points out that using any other geography smaller than the Department
currently uses would increase the number of PHAs required to use multiple sets of income limits. Also,
there would be cases where a PHA would face “multiple sets of income limits for multiple public
housing projects or a multifamily property owner faced different sets of income limits for multiple
projects, despite those projects operating in the same jurisdiction or substantially similar areas.”
Potential tenant harm and program inequities: HUD argues that using multiple sets of income limits
within one PHA jurisdiction may lead to inconsistencies in program eligibility for families earning the
same income but living in different parts of the jurisdiction, and it would be difficult to justify to tenants
and other interested parties. Similarly, different applicable income limits leading to an eligible voucher
recipient not being able to use the voucher in all neighborhoods would be “contrary to HUD’s mission of
promoting housing choice and the general purposes of the voucher program”.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 70
In concluding their report, HUD stated, “HUD strongly believes that calculating MFI estimates and income limits
should remain at the metropolitan area level to limit administrative complexity and burden on PHAs and other
interested parties and to ensure the use of the most current, robust data possible.”
Inflation trend factor
Due to the lag between the most recent year of ACS income data available and the fiscal year for which AMI
and income limits are in effect, HUD trends the ACS MFI estimate to the current year using the national CPI-U
index. This approach has two notable limitations:
1. The first issue is that incomes do not rise at the same rate in all areas of the country, or even all areas
of Washington. Using the same national trend factor for all areas can result in HUD’s calculation of MFI
being either too high or too low compared to an area's median family income. For example, Seattle-
Bellevue, WA HMFA uses the same trend factor as Pend Oreille County, even though each area's
underlying economics may differ. For an area where incomes are increasing faster than the national
CPI, this can result in an estimate of HUD MFI that is too low. On the other hand, in areas with income
growth slower than the national CPI, this can result in an estimate of MFI that is too high.
2. The second issue with this approach is that when HUD trends the ACS MFI estimate to the current year,
it assumes that median family income increases at the same rate as inflation. If the inflation rate, as
measured by the change in consumer prices, and the rate at which median incomes are changing
diverge, then HUD’s AMI estimates become less accurate. One way to measure the accuracy of HUD’s
inflation adjustments is by comparing the HUD estimate of MFI to the ACS estimate of MFI for the
same year. For example, HUD used 2019 ACS data and applied the inflation trend factor to calculate the
2022 HUD MFI. Now that the 2022 ACS estimates are available for comparison, we can directly
compare HUD’s 2022 MFI to the ACS 2022 MFI. We can assume the ACS estimate is more accurate
than HUD’s estimate, as the ACS estimate is based on surveys of households in 2022 and not subject
to an inflation factor. So, this comparison can show whether HUD’s estimate was too high or too low.
Exhibit 51 describes the percent variance between HUD MFI and ACS MFI by county in Washington, MSA, and
HMFA for 2022. This variance ranges from negative 21% in Mason County to positive 8% in Grays Harbor
County. Smaller rural counties in Washington typically have the highest variance; in most cases, HUD
underestimated MFI compared to ACS. This indicates that median family income increased faster than
inflation (as measured by CPI) in most parts of Washington between 2019 and 2022.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 71
Exhibit 51. Variance Between HUD MFI and ACS MFI, 2022
County Varianc e Betwe en HUD MFI an d AC S MF I, 2 022
Adams Cou nty -9%
Asotin Coun ty 2%
Benton Coun ty -8%
Chelan Coun ty -20%
Clallam Cou nty -19%
Clark County -3%
Columbia County -1%
Cowlitz Coun ty -8%
Douglas County -20%
Ferry County -12%
Franklin County -8%
Garfield Coun ty 1%
Grant Coun ty -13%
Grays Harbor County 8%
Island County -8%
Jefferson Coun ty -13%
King County -3%
Kitsap Coun ty -10%
Kittitas County -10%
Klickitat Coun ty -7%
Lewis County -6%
Lincoln County -14%
Mason County -21%
Okanogan Coun ty -13%
Pacific Coun ty -14%
Pend Oreille Coun ty -13%
Pierce County -4%
San Juan Co unty -10%
Skagit County -12%
Skamania Coun ty -3%
Snoho mish County -3%
Spokane Coun ty -12%
Steve ns County -9%
Thurston County -6%
Wahkiakum County 7%
Walla Walla County -5%
Whatcom Co unty -3%
Whitman Cou nty -10%
Yakima County -2%
Sources: HUD, 2024; BERK, 2024.
Two previous studies examined the impacts of HUD's methodology for estimating inflation in MFI calculations.
In a 2023 report, the Urban Institute found that HUD's inflation factor results in overestimating MFI in some
metropolitan regions, such as Nashville, while underestimating it in other metros, such as Seattle. These errors
result from disparities in the income growth rate compared to CPI in different metropolitan regions. Another
study by HUD came to similar conclusions. It recommends that HUD consider using an alternative data source
to calculate the inflation factor for MFI. Rather than using the CPI, HUD might consider using a source more
closely approximating income growth, such as CBO's projections for the Employment Cost Index.
Income limits derived from HUD MFI
AMI is rarely used directly in housing assistance programs. Instead, it is used by HUD or other agencies to
derive income limit standards that are calculated based on HUD MFI and, in many cases, additional
adjustments. Annually, HUD publishes two sets of income limits for every county in Washington, one for HUD
Programs and another for LIHTC and tax-exempt bond programs that HUD calls the Multifamily Tax Subsidy
Program (MTSP) limits. Combined, these two sets of income limit tables include four different income
standards in addition to HUD MFI:
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 72
1. Extremely Low Income
2. Very Low Income
3. Low Income
4. HERA Special
Each income limit has a different calculation methodology and is designed to be used for specific HUD
programs.38 A summary of the calculation methodology for each of these four income limit standards is
shown in Exhibit 52.
Exhibit 52. Common income limits derived from HUD MFI
Very Low (50%) Income (VLI): VLI is the most commonly used income limit standard. It is used for low-
income housing tax credit (LIHTC), tax-exempt bonds, and most HUD programs. This income limit uses
50% of HUD MFI as the starting point, but it may include additional adjustments to account for areas
where housing costs are exceptionally high, apply caps and floors for year-over-year changes, and
adjust areas to a floor of the state non-metro median income. As shown in Exhibit 10, in 2024,
Washington had six counties (15% of the total) in which VLI equaled 50% of HUD MFI. The other 33
areas were subject to one of HUD’s adjustments. A more detailed discussion of the calculation
methodology and adjustments applied to individual counties is provided in Appendix C. Alternative AMI
and impact analysis methodologies.
Extremely Low (30%) Income (ELI): This income limit is equal to the greater of 60% of VLI (equivalent
to 30% of HUD MFI if VLI has no adjustments) or the federal poverty levels as determined by the
Department of Health and Human Services (HHS). However, in no case can ELI be greater than VLI. The
HHS poverty standard is adjusted at each housing size. In 2024, 31 of the 39 areas in Washington had
their ELI adjusted up to the four-person poverty standard of $31,200
Low (80%) Income: Low income equals 160% of VLI (equivalent to 80% of HUD MFI if VLI has no
adjustments). However, the four-person low-income limit may not exceed the U.S. median family
income, except when justified by high housing costs. In addition, this income limit is subject to the
same caps and floors as VLI.
HERA Special: HERA Special income limits are only available to MTSP projects placed in service before
January 1, 2009. The limit is calculated for eligible counties by taking the 2009 VLI for a project and
adding the change in HUD MFI. This limit is only published for eligible areas where the HERA Special is
greater than VLI. Washington had the HERA Special published for 10 areas for 2024.
Source: HUD, 2024; Novogradac, 2024.
As VLI is the most commonly used income limit, the following section discusses its calculation in more detail.
Very Low Income (VLI) calculation method
The first step of calculating VLI is multiplying HUD MFI by 50%. However, HUD also applies several
adjustments, summarized in Exhibit 53. These adjustments limit how much VLI can change from year to year,
the floor below which VLI cannot dip, and adjustments to account for areas with high housing costs. It shows
that in 2024, VLI equaled 50% HUD MFI in only six counties in Washington. For the remainder of the counties,
another adjustment determined VLI. Exhibit 54 presents a map of which adjustment determined VLI in each
area of Washington in 2024
38 Attachment 1 of HUD’s Methodology for Determining FY 2024 Section 8 Income Limits delineates the federal program that uses each
of the income limit standards.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 73
Exhibit 53. HUD Very Low Income (VLI) limit adjustments and Washington counties
affected, 2024
# of WA counties where VLI is
Adjustment Description
determined by this adjustment
By default, VLI is calculated as 50% of HUD MFI. However, additional
50% of HUD MFI 6
adjustments may subsequently change this calculation.
This adjustment places a floor that no VLI can fall beneath. It impacts
State non-metro
areas where VLI is less than 50% of the median family income of all non- 16
median
metropolitan counties in the state. In 2024, this was $45,000 for WA.
In areas with high housing costs relative to area incomes, HUD increases
High housing cost VLI upward so that a higher percentage of the population can qualify for 3
Section 8 assistance.
Annual decrease This adjustment places a floor to prevent VLI from decreasing to less
0
floor than 95% of the previous year’s limit.
HUD caps VLI so it cannot rise more than 10% from the previous year's
Annual increase cap 14
limit.
Exhibit 54. Calculation adjustment that determined VLI by HUD area in 2024
Area Na me Calcul ation adj ustment that determin ed VLI by HUD area in 2024
Adams Cou nty, WA State N on-Me tro Median
Bellingham, WA MSA 10% Ceiling
Bremerton -Sil verdale, WA MSA Equal to 50% AM I
Clallam Cou nty, WA 10% Ceiling
Columbia County, WA 10% Ceiling
Ferry County, WA State N on-Me tro Median
Garfield Coun ty, WA State N on-Me tro Median
Grant Coun ty, WA State N on-Me tro Median
Grays Harbor County, WA State N on-Me tro Median
Island County, WA Equal to 50% AM I
Jefferson Coun ty, WA State N on-Me tro Median
Kennewick -Richla nd, WA MSA Equal to 50% AM I
Kittitas County, WA 10% Ceiling
Klickitat Coun ty, WA State N on-Me tro Median
Lewis County, WA State N on-Me tro Median
Lewiston, ID-W A MSA Equal to 50% AM I
Lincoln County, WA State N on-Me tro Median
Longview, WA MSA State N on-Me tro Median
Mason County, WA 10% Ceiling
Mount Vernon -Anacortes, WA MSA 10% Ceiling
Okanogan Coun ty, WA State N on-Me tro Median
Olympia-Tu mwa ter, WA MSA 10% Ceiling
Pacific Coun ty, WA State N on-Me tro Median
Pend Oreille Coun ty, WA State N on-Me tro Median
Portland -Va ncouver -Hillsboro, OR-W A MSA High Housing Cost
San Juan Co unty, WA 10% Ceiling
Seattle -Bellevue , WA HUD Metro FMR Area 10% Ceiling
Spokane, WA HUD Metro FMR Area 10% Ceiling
Steve ns County, WA HUD Metro FMR Area State N on-Me tro Median
Tacoma, WA HUD Metro FMR Area High Housing Cost
Wahkiakum County, WA State N on-Me tro Median
Walla Walla, WA MSA Equal to 50% AM I
Wenatchee, WA MSA 10% Ceiling
Whitman Cou nty, WA 10% Ceiling
Yakima, WA MSA State N on-Me tro Median
Sources: HUD, 2024; Novogradac, 2024; BERK, 2025.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 74
Description of VLI adjustment methods
Limits equal to 50 percent of HUD MFI
These are the areas that have no adjustments. Roughly 34% of the areas in the country and 15% in Washington
had no adjustment in the last two years.
State Non-Metro Median Income Adjustment
AMI income is adjusted up so that no area in a state has a VLI that is less than the non-metropolitan median
income of that state. This adjustment affects more than 43% of the areas nationwide and 41% in Washington.
The state non-metro floor for Washington for 2024 was $45,000.
High Housing Cost Adjustment
High housing cost areas are areas where housing costs are high compared to income limits. HUD adjusts the
VLI upwards in these areas so that a higher percentage of the population can qualify for Section 8 assistance.
The adjustment is based on the area's 2-bedroom HUD-published fair market rents (FMR) using the following
calculation: FMR*0.85/0.35*12. Although the high housing cost adjustment only affected 23 areas nationwide
(approximately 1% of all areas), it impacted around 10% of the population. Three counties in Washington were
subject to the high housing cost adjustment.
Low Housing Cost Adjustment
Low housing cost areas are the opposite of high housing cost areas, where housing costs are low compared to
income limits. HUD adjusts the VLI upwards in these areas so that a lower percentage of the population can
qualify for Section 8 assistance. Only one area nationwide (Los Alamos, NM) was subject to the low housing
cost adjustment in 2024.
Income Limit Floors
To help avoid large swings in VLI from year to year, HUD does not allow income limits to decrease by more
than 5 percent from one year to the next. 2024 was a strong year for income limits, so only 1% of areas were
subject to the floor; none of the areas were within Washington.
Income Limit Caps
HUD limits on how much VLI can increase from year to year. This is calculated as the greater of 5% or two
times the change in national median income, with a ceiling of 10%. The cap for 2024 was 10%. The cap was
applied to VLI in 21% of areas nationwide and 36% of areas in Washington.
Household size adjustment
HUD uses the above methodology to calculate the income limits for a four-person household. As shown in
Exhibit 55, the Area Median Income (AMI) is adjusted based on household size. For each person fewer than
four, the AMI is reduced by 10%, down to 70% of the four-person household base for a single-person
household. For each person beyond four, the AMI increases by 8%. For example, a five-person household is
108% of the four-person base, and a six-person household is 116%.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 75
Exhibit 55. Household size adjustment factors for HUD income limit
Note: For each additional person over eight, the four-person income limit is multiplied by an additional 8 percent.
Source: HUD, 2024.
Impacts of HUD income limits
General impacts of HUD income limits
There are many reasons why HUD's income limits may be relatively high or low compared to local area
incomes. Some of these are related to the method used to calculate HUD MFI, described above. Others relate
to the adjustments that HUD uses when calculating VLI and other income limits. Most adjustment factors are
designed to ensure the income limits are not set too low, which could result in fewer households being eligible
for housing assistance compared to the level of need. However, there are tradeoffs involved in these
adjustments. Exhibit 56 summarizes when income limits are not well aligned with local incomes.39
Exhibit 56. Impacts when HUD income limits are not aligned with local incomes
If HUD income limits are high compared to local incomes:
More households are eligible for housing assistance.
More competition for available affordable housing units, potentially crowding out households with the
greatest needs.
Rent limits are higher. This can contribute to a higher cost burden for some households.
Higher rent limits make new projects more financially feasible and help existing projects cover
operating costs and required debt payments.
If HUD income limits are low compared to local incomes:
Fewer households are eligible for housing assistance.
Households that need assistance may not qualify.
Rent limits are lower, which can reduce the cost burden for some households.
Lower rent limits make new projects less financially feasible and may make it difficult for existing
projects to cover operating costs, especially during inflation.
Sources: Novogradac, 2025; BERK, 2025.
A recent analysis of AMI in New York City found that the high housing cost adjustment significantly impacts
the alignment of income limits with the incomes of local residents. In 2022, this adjustment resulted in a VLI of
$66,700, nearly $20,000 higher than 50% of HUD MFI ($47,250). While this boost in the income limit is helpful
to make more households eligible for assistance, it can also result in less affordable housing supply targeted
for lower-income households in the greatest need of support. The authors point out: "54.6% of New York City's
rent-burdened households make less than 30% AMI, and another 23.5% make below 50%. Yet only 15.4% of
39 There are also impacts when income limits (and therefore rents) do not increase commensurate with affordable housing operating
expenses. When this happens, properties will have a hard time paying operating expenses and required debt payments. This may result
in deferring needed maintenance or not being able to make required payments.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 76
affordable housing produced under the de Blasio administration's Housing New York plan targeted households
under 30% AMI.”
Impacts on allowable rents in subsidized affordable housing
The impact of HUD income limits on allowable rents depends on the type of subsidy received. In most
development subsidies, rents for the project are based on the income limits, whereas in many rental subsidy
programs, rents are based on a different factor. A project may have both rental and operating subsidies.
Rental subsidies programs
The most common federal rental assistance programs are the Housing Choice (formerly Section 8) Voucher
and Public Housing programs funded by HUD and administered by local public housing agencies. In addition,
the US Department of Agriculture’s (USDA) Rural Development division oversees a rental subsidy program that
can be used in rural areas. These programs typically use income limits derived from AMI to determine
eligibility, but the rents paid are not tied to AMI.
In properties with rental assistance, the rent limit is usually not based on or tied to the income limits used to
qualify a tenant. When a household receives a rental subsidy, the rent is divided into two parts: the tenant-paid
portion and the rental subsidy amount. The tenant paid portion is generally a percentage of the household’s
actual income. In federal and most state and local programs, that percentage is typically 30%, meaning a
household would pay 30% of its income towards rent. The subsidy amount is calculated by taking the
difference between the allowable rent, commonly referred to as the contract rent, on the unit and the tenant-
paid portion. If the contract rent is $1,200 and the tenant-paid portion is $800, the subsidy payment would be
$400.
The method of setting the contract rent will vary from program to program. The contract rent for the Housing
Choice programs is based on a comparable unit's fair market rent rate. For the USDA program, the contract
rent is based on the project's budgeted expenses.
Development subsidies
Development subsidies come in many forms, including grants, low-interest rate loans, soft loans,40 and waived
fees. In return for the financial benefit of the development subsidy, owners will agree to provide units only to
qualified tenants based on income and charge lower rents based on published rent limits. The development
subsidies are given to the project during construction or upon conversion to permanent financing. The
subsidies allow the project to have lower mandatory debt payments and, therefore, charge lower rents to the
residents while still meeting all the property’s financial obligations.
In properties that receive development subsidies, the rent limit is usually set at 30% of the applicable income
limit. As the income limit increases, so does the rent limit. For instance, if the income limit were to increase by
5%, the rent limit would also increase by 5%. When determining the applicable rent limit, users need to
understand which HUD income standard is being used (e.g., MFI, ELI, VLI, etc.) and the bedroom size
adjustment.
40 Soft loans include debt that is only paid if the project has sufficient cash flow.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 77
Most housing programs determine rent limits based on an assumed number of people per bedroom, holding
the rent for a unit size constant regardless of the actual number of occupants.41 In this way, adjustments to
affordable rent limits based on unit size mirror adjustments to income limits based on household size. The
most common federal development subsidy is the low-income housing tax credit. The Washington State
Housing Finance Commission publishes HUD’s income and rent limits for tax credit and bond-financed
affordable housing properties.
Commerce administers the National Housing Trust Fund. It bases rents on 30% of the applicable income limit
using a 1.5 people per bedroom standard. Commerce also administers the HOME funds. Under the HOME
Program, there are two types of units, Low HOME and High HOME Units. The rent for Low HOME units equals
30% of VLI adjusted for bedroom size. The rent for High HOME Units is equal to the lesser of 30% of 65% AMI
adjusted for bedroom size or the Fair Market Rent for the unit size. In the case where the fair market rent is
less than the Low HOME rent, the Low HOME rent is also set at the Fair Market Rent, and the Low HOME and
High HOME rents would equal each other.
Examples of alternative AMI or income limit calculations
Very few housing programs in the country use income or rent limits that are not based on one of the HUD
standards discussed in this report. Here we review three examples from Washington State, San Francisco, and
Philadelphia.
Income limits for MFTE cities
Washington's Multifamily Tax Exemption (MFTE) program allows cities and counties to provide property tax
waivers to incentivize multifamily housing. The waiver can apply to new construction, conversion, and
rehabilitation of multi-family residential units. Two program options available to cities require that properties
set aside at least 20% of housing units for low and moderate-income households. Under the statute, household
income is based on AMI; households with incomes at 80% AMI or lower are considered low income, and
households with incomes at 80-115% AMI are considered moderate income.
Most cities reference HUD income limits when designing an MFTE program. However, they are allowed to use
alternative income limits that are lower than those published by HUD. One option is to use Income Limits for
MFTE Cities published by the University of Washington Center for Real Estate Research (UWCRER). These
alternative income limits are adjusted downward from HUD's income limits in cities with a lower median family
income than the surrounding HUD area (MSA, HMFA, or county). Among the 57 cities in their analysis, 37 have
city income limits that are less than the HUD income limits.
San Francisco
Beginning in 2016, the Mayor’s Office of Housing and Community Development (MOHCD) began publishing
customized income and rent limit increases for properties that MOHCD assisted through loans, grants, density
bonuses or fee waivers.42 These MOHCD income limits were based on HUD income limits but reflected
adjustments to cap the annual percentage increase. As stated on MOHCD’s website:
41 Rent based on the actual number of people in the unit is seldom used, due to the unpredictable nature of how many people will
occupy a unit and the additional complexity that would add to the underwriting of the project. Programs that set rent limits based on
assumed people per bedroom most commonly calculate occupancy as either 1.5 people per bedroom or one person per bedroom plus
one additional person. Studios are typically treated as housing a one-person household.
42 Affordable properties in San Francisco that are not receiving assistance from MOHCD are not required to use MOHCD income limits.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 78
“Annual increases to MOHCD AMI shall be limited to the lesser of: (1) the percentage amount necessary to adjust
MOHCD AMI to match the then-current year’s HUD SF AMI, or (2) four percent (4%). This Policy limits year-over-year
increases to MOHCD AMI to 4% in periods of high HUD SF AMI escalation, while allowing MOHCD AMI to “catch up”
to HUD SF AMI during periods when HUD SF AMI grows slowly, is static, or decreases.”
MOHCD outlined their reasoning for the policy as follows:
“As the City addresses the challenges created by the increasing volatility of the housing market, we are working
closely with community developers and property managers to support residents and maintain the integrity of existing
affordable housing programs. The priorities of the Mayor's Office of Housing and Community Development continue
to be ensuring that the City’s affordable housing is well maintained and well managed and minimizing the
displacement of residents living in affordable housing.”
However, the alternative income limits used by MOHCD add complexity and administrative burden to a project.
Property owners using both MOHCD funds and low-income housing tax credits (LIHTC) will need to monitor
both income and rent limits and use the most restrictive income limits. Exhibit 57 shows the difference
between the 60% MOHCD rents and 60% HUD Multifamily Tax Subsidy Projects (MTSP) Income Limit rents
used for LIHTC projects for San Francisco.
Exhibit 57. Comparison of 60% rent limits as published by San Francisco's MOHCD
and HUD's MTSP, 2024
1 Bedroom unit:
MOHCD: $1,799
HUD MSTP: $2,203
Difference: -$404
2 Bedroom unit:
MOHCD: $2,023
HUD MSTP: $2,644
Difference: -$621
3 Bedroom unit:
MOHCD: $2,248
HUD MSTIP: $3,054
Difference: -$806
4 Bedroom unit:
MOHCD: $2,428
HUD MSTIP: $3,408
Difference: -$980
Sources: City of San Francisco, 2024; HUD, 2024.
The reduction in rent required by MOHCD-assisted projects impacts a property's ability to cover its debt service
and operating expenses. A property with 100 two-bedroom units that used the MOHCD rent instead of the
LIHTC rent would be able to cover approximately $10 million less in debt using a 6% interest rate and a 30-year
term. The project will typically need additional resources to cover the decrease in supportable financing.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 79
Philadelphia
As of late 2024, Philadelphia was exploring using alternative geographic boundaries to calculate its AMI and
income limits. Philadelphia is part of the Philadelphia-Camden-Wilmington, PA-NJ-DE-MD MSA, which spans
five states and contains 11 counties. A brief titled Why Many Philadelphians Cannot Afford Affordable
Housing: Estimating an Alternative Area Median Income for the City/County of Philadelphia examines the issue
faced by Philadelphia’s continued use of the Philadelphia-Camden-Wilmington, PA-NJ-DE-MD MSA income
limit as opposed to an income limit that is based solely on Philadelphia. The report summarizes the issue as
follows:
“Philadelphia, like the central city of many metropolitan areas, has residents who are lower income than those in the
suburban counties. Establishing an AMI based on those higher-income surrounding counties creates a situation in
which fractions of AMI (e.g., 80% of AMI) will exceed the actual average of residents within the central city.”
Per the brief, if Philadelphia were to calculate a city income using the same methodology used by HUD, the MFI
would be $86,982 for Philadelphia as opposed to $114,400 calculated for the entire MSA. One important note
is that for this comparison, the brief used five-year ACS data instead of one-year ACS data and, therefore, is not
a direct comparison.
The brief found that people of color are more impacted by using an MSA-based MFI than white non-Hispanic
families:
“For many reasons that are beyond the scope of this Brief, there are substantial differences in family incomes in
Philadelphia between White not Hispanic families and those that are Black or Hispanic. Those differences are to the
disadvantage of Black and Hispanic residents of Philadelphia. In much the same way that an AMI based on multiple
areas amongst which Philadelphia has the lowest income, the city’s median is comprised of multiple groups of
families of which Black and Hispanic families are far below the average of all families (and even more below that of
White not Hispanic families). The implication of this is that while the HUD AMI leaves all Philadelphians at a
disadvantage, it leaves Philadelphians who are Black or Hispanic at a unique disadvantage.”
Philadelphia has not yet adopted alternative income limits. The proposals were under discussion, with
hearings expected to occur in 2024 and beyond.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 80
Appendix C. Alternative AMI and impact analysis
methodologies
Proposed alternatives
This study evaluates four alternative AMI methodologies:
1. Legislative District Median Family Income (MFI)
2. County MFI
3. City MFI
4. County Median Renter AMI
Exhibit 22 of this report includes more information about each of these alternatives. This section summarizes
the steps taken to calculate AMI for each alternative and conduct the impact analysis.
AMI methodology
The methodology for estimating AMI for each of the four alternatives mostly follows HUD's approach for
calculating AMI. The specific steps BERK took for estimating AMI for each of the four alternatives were as
follows:
Select a statistically reliable ACS estimate of MFI or median renter household income (for the County
Median Renter AMI alternative). When verifying the statistical reliability of the ACS estimate for MFI,
HUD follows the approach illustrated in Exhibit 58. BERK applied a similar approach with one exception.
HUD uses two standards when assessing statistical reliability: 1) the margin of error for the ACS
estimate is less than 50% of the estimate itself; and 2) the ACS estimate is based on at least 100
survey cases. We were only able to apply the first standard when selecting an appropriate ACS
estimate of MFI because data on sample size from the ACS is not publicly available.
After selecting the appropriate ACS estimate, calculate the CPI Inflation Factor.
Multiply the selected ACS estimate by the CPI Inflation Factor and round to the nearest $100.
For the Renter AMI Alternative only: The median renter household income from ACS is across all
household sizes. HUD's methodology treats the ACS MFI as applicable to a 4-person household,
although the average family household size in Washington is 3.0443. The average renter household size
in Washington is 2.22.44 To be consistent with HUD's approach, we assumed the median renter
household income from ACS applies to a 3-person household. To arrive at a 4-person estimate of AMI,
the estimated AMI is adjusted by family size using HUD’s methodology for family size adjustment (i.e.,
the 3-person median renter family income is 90% of the 4-person income).
Data
American Community Survey (ACS) data
BERK used the following data from the U.S. Census Bureau ACS to estimate AMI:
Median family income: B19113 Median Family Income in the Past 12 Months data set
43 U.S. Census Bureau American Community Survey 2023 1-Year Estimate (Table S1101: Households and Families).
44 U.S. Census Bureau American Community Survey 2023 1-Year Estimate (Table B25010: Average Household Size of Occupied
Housing Units by Tenure).
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 81
Median renter household income: S2503 Financial Characteristics data set
Inflation
The annual CPI estimate is sourced from the Bureau of Labor Statistics, archived at ALFRED, and the CPI
projection is from the CBO's February 2024 release of its 10-Year Economic Projections. For 2024 MFI, we
calculated the CPI Inflation Factor, which is the ratio between the 2024 CPI and the 2022 CPI, which equals
1.0618.
Exhibit 58. HUD's methodology for assessing the statistical reliability of ACS
estimates of MFI
Is there a statistically reliable
1-year ACS estimate of
median family income
available for the area?
(MOE<50% of estimate and
sample size > 100 cases)
Yes No
Is there a statistically reliable
5-year ACS estimate of
Use the 1-year median family income
estimate available for the area?
(MOE<50% of estimate and
sample size>100 cases)
Yes No
Does the area have a
minimally reliable
Use the 5-year estimate in at least two of
estimate the past three years?
(MOE <50% of estimate)
Yes No
Use the estimate from
Use the average of
the next larger
these two or three
encompassing
ACS estimates
geography
Source: HUD, 2025; BERK, 2025.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 82
VLI methodology
Once BERK estimated AMI for each alternative, we calculated the Very Low Income (VLI) limits following the
steps outlined below for each alternative except the County Median Renter AMI alternative, for which we
calculated the 60% AMI limit directly from MFI.
HUD MFI
Here, we review HUD's methodology for calculating VLI by HUD area:
Calculate preliminary 4-person VLI: The 4-person preliminary VLI is 50% of the estimated MFI for an
area.
High Housing Cost Adjustment: The 4-Person VLI is increased if it is less than the amount at which
35% of the preliminary VLI estimate equals 85% of the annualized two-bedroom 40th percentile Fair
Market Rent (FMR) (this adjusts income limits upward for areas where rental housing costs are
unusually high in relation to median income).
Low Housing Cost Adjustment: If the 4-Person VLI exceeds 80% of the U.S. median family income, and
the two bedroom 40th percentile fair market rent is affordable (less than or equal to 30% of the
preliminary VLI), the VLI will be reduced to the greater of 80% of U.S. median family income or the
amount at which 30% of it equals the two-bedroom 40th percentile FMR (this adjusts income limits
downward for areas of unusually high median family incomes).
State Non-Metro Median Family Income Adjustment: The 4-Person VLI is also adjusted if it is lower
than 50% of the State Non-Metro Median Family Income.
Ceilings and Floors: VLI is adjusted if it is lower than 5% or higher than 10% of the prior year VLI.
Family Size Adjustment: Once the final 4-person income limit has been established, income limits for
other family sizes are calculated by applying a percentage adjustment to the final 4-person VLI. The 1-
person family income limit is 70% of the 4-person income limit. The 2-person family income limit is 80%
of the 4-person income limit, the 3-person family income limit is 90% of the 4-person income limit, the
5-person income limit is 108% of the 4-person income limit, the 6-person family income limit is 116% of
the 4-person income limit, the 7-person family income limit is 124% of the 4-person income limit, and
the 8-person family income limit is 132% of the 4-person income limit. The income limit can be
calculated for families larger than eight people by adding an additional eight (8) percent per person to
the next lower limit. For example, a 9-person family income limit is 140% (132% + 8%), and so on. The
resulting low-income limit amounts for other family sizes are then rounded up to the nearest $50 to
produce the Final VLI.
These steps are illustrated in Exhibit 59.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 83
Exhibit 59. HUD's VLI methodology
Source: HUD, 2025; BERK, 2025.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 84
County and city MFI
To calculate VLI for the City MFI and County MFI alternatives, BERK implemented two methodologies.
Option A: No ceilings and floors adjustment
Calculate preliminary 4-Person VLI: The 4-person preliminary VLI is 50% of the estimated MFI for the
county or city.
Estimate Fair Market Rent (FMR): the HUD area FMR is adjusted by the ratio between the 5-Year 2017-
2021 ACS estimate of 2-bedroom unit gross rent for the county or city to the 5-Year 2017-2021 ACS
estimate of 2-bedroom gross rent for the larger HUD area to get a more localized FMR estimate.
High Housing Cost Adjustment: The 4-Person VLI is increased if it is less than the amount at which
35% of it equals 85% of the annualized localized two-bedroom FMR for the county or city (this adjusts
income limits upward for areas where rental housing costs are unusually high in relation to median
income).
Low Housing Cost Adjustment: If the 4-Person VLI exceeds 80% of the U.S. median family income, and
the two bedroom localized fair market rent is affordable (less than or equal to 30% of the preliminary
VLI), the VLI will be reduced to the greater of 80% of U.S. median family income or the amount at which
30% of it equals the two-bedroom localized FMR (this adjusts income limits downward for areas of
unusually high median family incomes).
State Non-Metro Median Family Income Adjustment: The 4-Person VLI is adjusted if it is lower than
50% of the State Non-Metro Median Family Income.
Family Size Adjustment: Once the final 4-person income limit has been established, income limits for
other family sizes are calculated by applying the same percentage adjustments to the final 4-person
VLI that HUD applies.
Option B: Washington Center for Real Estate Research methodology
Option B is a similar methodology to the one that the Washington Center for Real Estate Research (WCRER)
uses to estimate income limits for MFTE cities. It involves the following:
Calculate the ratio between the 2022 ACS MFI estimate for the county or city and the 2022 ACS MFI
estimate for the overlapping HUD area. The WCRER caps the ratio at 100% (i.e., the city or county AMIs
are the minimum of the HUD area AMI or the county- or city-specific AMI), but this is not implemented
in the BERK methodology.
Multiply the ratio by the HUD 2024 VLI to yield the county or city VLI.
Unlike the income limits published by WCRER, BERK's County and City MFI option B does not limit the
results to be no higher than HUD's income limits.
Legislative district MFI
To calculate VLI for the Legislative District MFI alternative, BERK implemented the following methodology:
Calculate preliminary 4-Person VLI: The 4-person preliminary VLI is 50% of the estimated MFI for the
legislative district.
State Non-Metro Median Family Income Adjustment: The 4-Person VLI is adjusted if it is lower than
50% of the State Non-Metro Median Family Income.
Family Size Adjustment: Once the final 4-person income limit has been established, income limits for
other family sizes are calculated by applying the same percentage adjustments to the final 4-person
VLI that HUD applies.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 85
60% AMI income limit methodology
Once VLI has been calculated for each alternative, we calculate the 60% AMI income limit by multiplying VLI by
120%. For the County Median Renter AMI alternative, the 60% AMI income limit is 60% of the estimated MFI for
the county.
Impact analysis
The impact analysis included the following:
Data availability and reliability assessment
Estimating households eligible for housing assistance at 60% AMI
Comparison of 60% AMI income limit by alternative to example household incomes
Comparison of 60% AMI rent by alternative to fair market rent
Data availability and reliability assessment
When estimating AMI for each of the four alternatives, BERK estimated the percentage of areas (legislative
district, county, city) that cannot be calculated because of a lack of statistically reliable data. BERK was able to
implement only one of the reliability standards that HUD uses to assess statistical reliability (i.e., the margin of
error for the ACS estimate is less than 50% of the estimate itself) due to data availability limitations
Comparison of the 60% AMI income limit by alternative to example
household incomes
In the Impact and feasibility evaluation section of this report, BERK compared the income of example
households earning minimum wage to the 60% AMI income limits by alternative for different cities in
Washington. The example households include one full-time minimum wage job household and two full-time
minimum wage job households. The annual income for these households was estimated using the
Washington state minimum wage of $16.28 per hour in 2024 and a total of 2,080 hours per year for a full-time
job.
Comparison of 60% AMI rent by alternative to fair market rent
BERK estimated the monthly rent that a household earning 60% AMI would be able to afford for each of the
four alternatives and compared it to the fair market rent for different cities in Washington. The 60% AMI
monthly rent is calculated by applying the 30% of income housing affordability standard (housing costs should
not exceed 30% of household income) to the 60% AMI annual income limit by alternative and then dividing by
12. The fair market rent by city is calculated as the corresponding HUD area FMR by relevant unit size,
multiplied by the ratio of city gross rent to HUD area gross rent, to arrive at a localized market rent estimate.
This report's Impact and feasibility evaluation section shows the percentage difference between the 60% AMI
rent by alternative and the fair market rent for different cities in Washington.
Estimating households eligible for housing assistance at 60% AMI
BERK estimated the number of total households that would be eligible for housing assistance at 60% AMI by
alternative for all cities in Washington. This analysis required data on the number of existing households in
each jurisdiction by AMI band, which is available from HUD through their Comprehensive Housing Affordability
Strategy (CHAS) data. The CHAS data combine ACS microdata with HUD-adjusted median family incomes
(HAMFI) to create estimates of the number of households that would qualify for HUD assistance at different
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 86
levels of AMI. Because the latest CHAS data released by HUD is for 2021 (based on 2017-2021 ACS 5-year
estimates), BERK analyzed eligible households for 2021. The approach involved the following:
Estimating AMI, VLI, and the 60% AMI income limit for each of the four AMI alternatives for 2021 using
the methodology outlined in this appendix.
Estimating the number of households by city eligible for housing assistance at 60% AMI using HUD's 4-
person 60% AMI income limit for the corresponding HUD area.
Estimating the number of households by city eligible for housing assistance at 60% AMI using the 4-
person 60% AMI income limit we estimated for each of the four AMI alternatives. Because the CHAS
data for households by AMI level is only available summarized in set brackets (i.e., <20% AMI, 20 to
30% AMI, 30% to 40% AMI, etc.), we assumed that the distribution of households by income in each
bracket is uniform to calculate the number of households eligible.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 87
Appendix D. HUD MFI and income limits by area, 2025
2025 HUD income limits for Washington counties
The various income standards for each county are summarized in Exhibit 60. For more details about these
limits, see Income limits derived from HUD MFI in Appendix B. Literature review.
Exhibit 60. HUD MFI and income limits for 4-person households, 2025
Very Low Income Extremely Low
HUD MFI Low Income
County (VLI) Income (ELI) 60% AMI
(AMI) (80% AMI)
(50% AMI) (30% AMI)
Adams $76,400 $47,400 $32,150 $56,880 $75,850
Asotin $87,100 $43,550 $32,150 $52,260 $69,700
Benton $105,600 $52,800 $32,150 $63,360 $84,500
Chelan $96,500 $48,250 $32,150 $57,900 $77,200
Clallam $90,400 $47,400 $32,150 $56,880 $75,850
Clark $124,100 $62,050 $37,250 $74,460 $99,300
Columbia $109,800 $50,100 $32,150 $60,120 $80,150
Cowlitz $85,500 $47,400 $32,150 $56,880 $75,850
Douglas $96,500 $48,250 $32,150 $57,900 $77,200
Ferry $80,700 $47,400 $32,150 $56,880 $75,850
Franklin $105,600 $52,800 $32,150 $63,360 $84,500
Garfield $86,500 $47,400 $32,150 $56,880 $75,850
Grant $91,700 $47,400 $32,150 $56,880 $75,850
Grays Harbor $89,000 $47,400 $32,150 $56,880 $75,850
Island $112,300 $55,700 $33,400 $66,840 $89,100
Jefferson $106,200 $49,150 $32,150 $58,980 $78,600
King $157,100 $78,550 $47,150 $94,260 $121,150
Kitsap $124,300 $62,150 $37,300 $74,580 $99,450
Kittitas $107,700 $53,850 $32,300 $64,620 $86,150
Klickitat $93,500 $47,400 $32,150 $56,880 $75,850
Lewis $92,100 $47,400 $32,150 $56,880 $75,850
Lincoln $91,000 $47,400 $32,150 $56,880 $75,850
Mason $104,300 $50,100 $32,150 $60,120 $80,150
Okanogan $78,200 $47,400 $32,150 $56,880 $75,850
Pacific $89,900 $47,400 $32,150 $56,880 $75,850
Pend Oreille $83,400 $47,400 $32,150 $56,880 $75,850
Pierce $120,800 $60,400 $36,250 $72,480 $96,650
San Juan $113,200 $55,400 $33,250 $66,480 $88,650
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 88
Very Low Income Extremely Low
HUD MFI Low Income
County (VLI) Income (ELI) 60% AMI
(AMI) (80% AMI)
(50% AMI) (30% AMI)
Skagit $111,600 $54,700 $32,800 $65,640 $87,500
Skamania $124,100 $62,050 $37,250 $74,460 $99,300
Snohomish $157,100 $78,550 $47,150 $94,260 $121,150
Spokane $100,800 $50,400 $32,150 $60,480 $80,650
Stevens $88,400 $47,400 $32,150 $56,880 $75,850
Thurston $116,700 $58,350 $35,000 $70,020 $93,350
Wahkiakum $71,300 $47,400 $32,150 $56,880 $75,850
Walla Walla $97,900 $48,950 $32,150 $58,740 $78,300
Whatcom $108,400 $54,200 $32,500 $65,040 $86,700
Whitman $98,300 $49,150 $32,150 $58,980 $78,650
Yakima $82,300 $47,400 $32,150 $56,880 $75,850
Source: HUD Section 8 Income Limits, 2024; HUD MTSP Income Limits, 2024.
EVALUATION OF ALTERNATIVE METHODS FOR CALCULATING AMI IN WASHINGTON 89
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