Geographic Cost of Living Differences: In Brief

March 2, 2022 R47037

Geographic Cost of Living Differences: In
Brief
March 2, 2022
Congressional Research Service
https://crsreports.congress.gov
R47037

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Geographic Cost of Living Differences: In Brief

Cost of Living: When (Inflation) Versus Where
(Geographic Differences)
The cost of living (COL) is an economic term referring to the amount of money people need to
achieve a certain standard of living. It is largely determined by the prices of goods and services
consumers must buy to reach that standard, including housing, food, energy (e.g., electricity and
gas), medical care, and leisure, among many others. The federal government produces several
measures of prices in the economy. For example, the Consumer Price Index and the Personal
Consumption Expenditures Price Index track prices paid for goods and services by households.1
Policymakers and the public closely watch the rate of change of prices over time, called inflation.
During periods of relatively high inflation, consumers need more money to achieve the same
standard of living, or they will have a reduced standard of living if their earnings are stagnant or
increase by less than inflation.2 However, these headline numbers do not provide any information
on differences in the COL in different parts of the country at any one time.3 Put another way,
inflation measures give no information about which areas are relatively more or less expensive
places in which to live or how much more expensive it is to live in a metropolitan or a rural area,
for example.
While the rate of inflation and changes to it have a number of quality-of-life and policy
implications, so too do regional price disparities. As will be discussed later in this report, policies
that do not account for COL differences across places may inadvertently benefit some more than
others. Additionally, policies that rely on data unadjusted for place in order to determine who
qualifies for certain benefits, for example, may also inadvertently benefit some more than others.
However, measures of price disparity are less well known and less closely tracked than inflation
measures. This report examines regional price disparity measures and selected economic and
policy considerations.
Measures of Geographic COL Differences
The main source of public data4 on geographic COL differences is the regional price parity (RPP)
series produced by the Bureau of Economic Analysis (BEA). BEA has been publishing official
estimates of RPP by state and metropolitan statistical area since 2008. RPPs are weighted

1 Other measures of prices include the gross domestic product price deflator, which measures a broader array of prices,
and the producer price index, which measures prices domestic producers receive for their products. These measures
include the prices of many goods and services that are not purchased by consumers and are not generally considered as
useful a gauge of cost of living as consumer prices.
2 For a more detailed discussion of inflation, see CRS In Focus IF10477, Introduction to U.S. Economy: Inflation, by
Lida R. Weinstock.
3 The Bureau of Labor Statistics (BLS) publishes a Consumer Price Index (CPI) for each state and a number of
metropolitan areas, but those figures only allow a comparison of inflation rates over time within the same metropolitan
area. A high number for an area indicates that area has experienced relatively more inflation over time, not that it is a
relatively more expensive place to live right now. BLS, Consumer Price Index: Overview, Handbook of Methods,
November 24, 2020, https://www.bls.gov/opub/hom/cpi/.
4 There are private sources of data for geographic COL differences that this report does not cover. For example, a major
private source of information on the comparative COL in different areas of the country is the Council for Community
and Economic Research Cost of Living Index (COLI), which compares costs and creates an index for COL up to the
city level. COLI data are available for purchase. See Council for Community and Economic Research, “Cost of Living
Index,” https://www.coli.org/.
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averages of price levels in one geographic region compared to all other regions in the United
States. The RPPs are expressed as a percentage of the overall national level, with the national
level set to 100. For example, if a state had an RPP value of 110, this would indicate that state
was 10% more expensive on average than the rest of the country.5
Table 1 below shows state-level RPPs for 2020 (the most recent data available), 2008 (the first
official year of the series), and the change from 2008 to 2020, organized from highest to lowest
2020 RPP. In 2020, Hawaii, the District of Columbia, and New Jersey had the three highest RPPs,
and Mississippi, West Virginia, and Arkansas had the three lowest RPPs. Generally, RPPs have
not changed by large degrees over the past 12 years, with a few exceptions. For example,
Connecticut, the most changed state, became about 5.7 percentage points less expensive during
this time period. Arizona, Delaware, Nevada, and Vermont went from more expensive to less
expensive than the national average between 2008 and 2020. Over the same period, Oregon went
from less to more expensive than the national average.6
Table 1. Bureau of Economic Analysis Regional Price Parities
United States Average = 100
State
2020 RPP
2008 RPP
Difference
Hawaii
111.985
109.726
2.259
District of Columbia
111.459
111.876
-0.417
New Jersey
111.163
106.864
4.299
California
110.38
109.949
0.431
New York
110.212
111.057
-0.845
Massachusetts
107.442
105.707
1.735
Washington
107.359
103.975
3.384
Maryland
106.472
108.452
-1.98
New Hampshire
103.713
105.908
-2.195
Connecticut
103.439
109.205
-5.766
Alaska
103.239
106.228
-2.989
Colorado
102.866
102.979
-0.113

5 BEA, Real Personal Consumption Expenditures and Personal Income by State, 2020, December 14, 2021,
https://www.bea.gov/news/2021/real-personal-consumption-expenditures-and-personal-income-state-2020.
Historically, BEA estimated RPPs using rolling averages of annual averages over five years for CPI price levels across
different locations (excluding rents) merged with American Community Survey (ACS) data on rents from the most
recent year. For example, the 2015 RPP series is an average of 2011-2015 CPI prices plus 2015 ACS rent indexes. See
BEA, Real Personal Income and Regional Price Parities, February 2021, https://www.bea.gov/system/files/
methodologies/RPP2020-methodology_1.pdf. In 2020, BEA changed its methodology. First, BEA replaced CPI
weights with Personal Consumption Expenditure Index weights. Second, BEA introduced new housing and utilities
data from the ACS public use microdata sample. Third, BEA removed seven highly variable CPI categories—hospital
services, physicians services, prescription drugs, college tuition and fees, elementary and high school tuition and fees,
childcare and nursery school, and club membership for shopping clubs, fraternal or other organizations—from the
calculation. Fourth, BEA switched from multiyear moving averages to only annual CPI and ACS data. See BEA,
Regional Price Parity Methodology Revisions, December 14, 2021, https://www.bea.gov/sites/default/files/2021-12/
rpp1221-methods.pdf.
6 Annual, state-level regional price parity data are included in the BEA’s “Real Personal Consumption Expenditures
and Personal Income by State” release. For the most current version, see BEA, Real Personal Consumption
Expenditures and Personal Income by State, 2020.
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Geographic Cost of Living Differences: In Brief

State
2020 RPP
2008 RPP
Difference
Oregon
102.622
97.6
5.022
Rhode Island
101.845
102.04
-0.195
Virginia
100.978
103.274
-2.296
Florida
100.711
101.779
-1.068
Illinois
100.476
100.318
0.158
Texas
99.542
97.512
2.03
Vermont
99.347
101.024
-1.677
Arizona
99.071
102.793
-3.722
Minnesota
98.625
96.351
2.274
Delaware
97.872
100.792
-2.92
Pennsylvania
97.564
99.061
-1.497
Nevada
97.056
101.56
-4.504
Maine
96.776
97.834
-1.058
Utah
95.322
97.4
-2.078
Georgia
94.541
94.78
-0.239
Michigan
94.045
95.54
-1.495
Wisconsin
93.188
93.336
-0.148
Nebraska
92.89
90.842
2.048
Louisiana
92.716
92.83
-0.114
Indiana
92.501
92.538
-0.037
Missouri
92.494
89.35
3.144
Montana
92.443
95.825
-3.382
Kansas
92.364
90.729
1.635
Wyoming
92.257
95.966
-3.709
Tennessee
92.15
92.05
0.1
North Dakota
92.041
86.837
5.204
North Carolina
91.84
92.97
-1.13
Ohio
91.69
92.513
-0.823
South Carolina
91.647
92.693
-1.046
New Mexico
91.567
94.928
-3.361
South Dakota
91.518
85.981
5.537
Oklahoma
91.322
90.868
0.454
Idaho
91.196
95.13
-3.934
Iowa
91.047
88.22
2.827
Kentucky
89.778
90.135
-0.357
Alabama
89.252
89.757
-0.505
Arkansas
89.181
88.996
0.185
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Geographic Cost of Living Differences: In Brief

State
2020 RPP
2008 RPP
Difference
West Virginia
87.959
88.145
-0.186
Mississippi
87.775
89.157
-1.382
Source: Bureau of Economic Analysis, State Area Regional Price Parities.
Notes: BEA changed its methodology for estimating RPPs in 2021 (for 2020 data). Comparing two series that have
been estimated using different methodologies may not be as accurate as comparing series estimated using the same
methodology. Additionally, in 2020, due to COVID-19, response rates for the ACS, which BEA uses in the calculation
of RPPs, were low enough that the Census Bureau considers many series coming from the 2020 ACS to be
experimental.
BEA additionally provides RPPs for metropolitan statistical areas7 (MSAs) as well as the
metropolitan and nonmetropolitan portions8 of each state. Within states, metropolitan areas
typically have higher RPPs than their nonmetropolitan counterparts. However, across the United
States, many MSAs have below-national-average RPPs, and some even have RPPs lower than the
national nonmetropolitan average.9 For example, in 2020, the Albany, GA, MSA had an RPP of
84.6, below both the national average and the U.S. nonmetropolitan average (89.0), while for the
state of Georgia, the metropolitan areas still had a higher average RPP (96.1) than the
nonmetropolitan areas (85.4) within the state.
Economic Considerations
Why Disparities Persist
From a theoretical standpoint, those goods that can be easily transported across locations might
be expected to exhibit little geographic variation in price, and for many goods and services, there
is likely to be a tendency for prices to equalize across the country.10 Where there is a premium for
a particular good in one area of the country, it would serve as a signal to (and an incentive for)
producers to make more of that good available in that area, either through increases in total
production or redistribution of current production, thus tending to bring the price more in line
with that prevailing elsewhere. However, as previously illustrated by data, geographic COL
differences persist. This variability can be explained by barriers to the trade of goods and services
across places, notably transportation costs and the inability to transport some goods and services.
Differences in transportation costs and transportability are reflected in prices. For example,
Hawaii tends to be relatively expensive compared to the national average, in part due to the high
transportation costs of having to fly or ship in most goods and services.

7 BEA uses the U.S. Office of Management and Budget definition of MSAs as “standardized county or equivalent-
based areas having at least one urbanized area of 50,000 or more population, plus adjacent territory that has a high
degree of social and economic integration with the core, as measured by commuting ties.”
8 Within a given state, anything that falls within an MSA is considered metropolitan, and everywhere else is considered
nonmetropolitan.
9 BEA, Real Personal Consumption Expenditures and Personal Income by State, 2020.
10 The idea that tradable goods and services should cause prices to equalize over locations is known as the law of one
price. While this is a well-known economic theory, economists debate the extent to which this theory holds in reality.
For example, see Kenneth Rogoff, Kenneth A. Froot, and Michael Kim, “The Law of One Price Over 700 Years,”
International Monetary Fund Working Papers, vol. 01, no. 174 (November 2001), https://www.imf.org/external/pubs/
ft/wp/2001/wp01174.pdf.
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Proxies for COL
Given that it was in 2008 that the federal government began publishing data on geographic COL
differences, this may raise the question: Do any previously existing policies account for these
differences? The short answer is yes, some do to varying extents. While COL data are relatively
new, certain policies take into account regional price and compensation differences that may
proxy geographic COL differences fairly well. This section discusses two such proxies—home
prices and income—and examples of how they have been used in policy.
Home Prices
As was stated earlier, some goods and services are not transportable—land and corresponding
rents, for example. In addition, local zoning laws can have a significant impact on how much and
what kind of housing can be built. For these reasons, housing markets tend to show variability,
and any one local housing market may not be priced similarly to the national average. Costs for
shelter tend to be a major category of spending in the United States, and therefore differences in
housing costs may proxy differences in COL.
Certain federal programs account for home value differences across regions. For example, the
Federal Housing Finance Agency sets both a national baseline and high cost area limits for
mortgages that Fannie Mae and Freddie Mac can purchase.11
Income
Just as there appear to be some significant differences in living costs in different regions of the
country, there are also regional differences in incomes. Figure 1 below plots national, state, and
District of Columbia RPPs against their corresponding median household incomes. As RPPs
increase, median household income tends to increase as well, and vice versa. The two variables
appear to be correlated, as most points are close to the trend line, with a few exceptions—such as
Utah, which has a relatively high median income ($77,827) given its RPP (95.3), or New York,
which has a relatively low median income ($73,398) given its RPP (110.2).

11 Federal Housing Finance Agency, “FHFA Announces Conforming Loan Limits for 2022,” press release, November
30, 2021, https://www.fhfa.gov/Media/PublicAffairs/Pages/FHFA-Announces-Conforming-Loan-Limits-for-
2022.aspx.
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Geographic Cost of Living Differences: In Brief

Figure 1. Correlation Between Median Income and Relative Price Parity by State,
2020

Sources: BEA State Area Regional Price Parities and Census Bureau American Community Survey.
Notes: Chart includes all 50 states, the United States (in light blue), and the District of Columbia. Due to the
impact of the COVID-19 pandemic, response rates for the American Community Survey were low and margins
of error therefore higher. As such, the income data presented in this chart are considered experimental by the
Census Bureau and do not meet the statistical standards of other Census data.
Just as transportability and transportation costs of goods and services contribute to differences in
the prices of those goods and services across locations, barriers to migration may cause
differences in income across locations. In a world with no barriers to migration, individuals
seeking to maximize their incomes would be able to choose employment in the location that did
so, incentivizing employers to compensate workers similarly for similar work across locations. At
the same time, there are significant barriers to migration, not least of which is that it can be costly
to move.12
Given that disparities across locations persist for both COL and income, it could be useful to
analyze whether there might be a correlation between the two. People with higher incomes can
afford to spend more on goods and services, and employers in areas with a low COL can offer
lower wages and still attract workers. Given the apparent correlation between measures of COL
and income, measures of compensation for comparable work could arguably be used to
reasonably proxy COL in a specific region. This gets reflected in public discussions of federal
employee pay. Federal locality pay—place-based differences in compensation of federal
government employees—is determined using the Bureau of Labor Statistics’ National
Compensation Survey,13 which is given to establishments (as opposed to households) and
estimates employer costs for employee compensation and trends in compensation, among other

12 For a more in-depth discussion of factors related to low migration rates within the United States, see William H.
Frey, U.S. Migration Still at Historically Low Levels, Census Shows, Brookings Institution, November 20, 2017,
https://www.brookings.edu/blog/the-avenue/2017/11/20/u-s-migration-still-at-historically-low-levels-census-shows/
#:~:text=The%20decline%20in%20annual%20mobility,owners%20move%20less%20than%20renters.
13 BLS, National Compensation Survey Frequently Asked Questions, August 31, 2016, https://www.bls.gov/ncs/
faq.htm#faqd.
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Geographic Cost of Living Differences: In Brief

topics.14 Colloquially, locality pay adjustments15 are often equated to COL adjustments, although
technically they are not the same.
If work in certain sectors of the economy is increasingly done remotely (perhaps because of
structural changes occurring in the aftermath of the pandemic), disparities could have significant
implications for wages and migration, as relative disparities themselves may change. Fully remote
work may remove some barriers to migration—workers would no longer be physically tied to
their place of work—which could, in turn, affect local labor markets.
Policy Considerations
Some government programs and policies are indexed to inflation but not place. Programs that are
not indexed for geographical price variation may provide more benefits to some than to others.
For example, tax credits, such as the child tax credit, provide a flat credit per qualifying child
across locations.16 For those receiving such tax credits, recipients in low-COL areas are receiving
more benefit than those in high-COL areas. Another example is Social Security payments. To the
extent that beneficiaries are mobile, they have an incentive to move to relatively less expensive
areas, increasing the purchasing power of their benefits without an increase in overall outlays.
However, the extent to which this actually occurs is likely not high. Using a simplistic scenario
for Social Security as an example, for the 2020-2021 period, 0.8% of people who moved did so
for a reason related to retirement. Additionally, about 8.4% of the total population moved in that
time, which is relatively low compared to earlier time periods and indicates that there was
relatively little migration even in an absolute sense.17 Given this, some may argue it is appropriate
to adjust selected transfer payments to reflect national variations in the COL.
In other cases, thresholds that qualify people or entities for programs are at issue. For example,
U.S. poverty thresholds are meant to reflect need based on level of money income, but they do
not vary geographically (they are indexed for inflation),18 despite large differences in the COL
within and across states.19 The standard of living for an individual at the poverty income
threshold may be very different in a metropolitan versus nonmetropolitan area or in a state with
an above-average RPP versus one with a below-average RPP.

14 BLS, National Compensation Measures: Overview, Handbook of Methods, December 15, 2017,
https://www.bls.gov/opub/hom/ncs/home.htm.
15 For more information about locality pay adjustments, see CRS Report R47033, Federal Pay: General Schedule (GS)
Pay Adjustment Process, Amounts Provided Since 2010, and Issues for Congress, by Barbara L. Schwemle.
16 Benefits.gov, Child Tax Credit, https://www.benefits.gov/benefit/938.
17 Census Bureau, Table A-1. Annual Geographic Mobility Rates, By Type of Movement: 1948-2021, CPS Historical
Migration/Geographic Mobility Tables, November 2021, https://www.census.gov/data/tables/time-series/demo/
geographic-mobility/historic.html; and Census Bureau, Table A-5. Reasons for Move (Specific Categories): 1999-2021,
CPS Historical Migration/Geographic Mobility Tables, November 2021, https://www.census.gov/data/tables/time-
series/demo/geographic-mobility/historic.html.
18 Census Bureau, How the Census Bureau Measures Poverty, November 22, 2021, https://www.census.gov/topics/
income-poverty/poverty/guidance/poverty-measures.html.
19 The Department of Health and Human Services additionally provides poverty guidelines, which are a simplification
of poverty thresholds used for administrative purposes. These guidelines include separate poverty levels for Alaska and
Hawaii. See Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation,
2021 Poverty Guidelines, https://aspe.hhs.gov/topics/poverty-economic-mobility/poverty-guidelines/prior-hhs-poverty-
guidelines-federal-register-references/2021-poverty-guidelines.
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Geographic Cost of Living Differences: In Brief

Author Information

Lida R. Weinstock

Analyst in Macroeconomic Policy

Acknowledgments
This report uses material from a report by former CRS specialist in quantitative economics, Brain Cashell.
The author thanks Brian Cashell for use of this material. Any errors or omissions are the author’s own.

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