A first look at experimental personal consumption expenditures by state.
Awuku-Budu, Christian ; Guci, Ledia ; Lucas, Christopher A. 等
THE VARYING economic experiences across the states during the
downturn that began in December 2007 and ended in June 2009 emphasized
the importance of regional statistics. Gross domestic product (GDP)
statistics by state, and personal income statistics by state have long
provided important information on the value of final goods and services produced by industries and on the incomes earned by households. However,
corresponding information on household sector consumption at the state
level has not traditionally been available.
Such information would be useful, as it would provide a clearer
indication of how households in various regions fare in recessions and
recoveries. Such statistics would yield insights on many questions, such
as what categories of consumption decline the most in specific states
and how the growth rates of consumer spending compare with the growth
rates of disposal personal income.
The Bureau of Economic Analysis (BEA) has been exploring the
possibility of producing statistics on personal consumption expenditures
(PCE) at the state level to address this data gap for several years, and
it is now in position to begin producing these statistics on an annual
basis. BEA plans to release its first set of prototype statistics in
2014.
These experimental PCE-by-state statistics are designed to be used
in conjunction with other macroeconomic and regional data produced by
BEA. Given the limited availability of source data at the regional
level, the new PCE-by-state statistics will not provide the same level
of category detail that BEA currently makes available at the national
level. The 16 categories prepared for these statistics correspond to the
categories in table 2.3.5 in the national income and product accounts.
In addition, the new statistics will not initially account for the
differences in prices of goods and services across regions or over time.
Nevertheless, these statistics will provide several benefits. They can
be used by state governments to analyze the potential revenue impact
generated from various sales tax proposals. They can be used for
cross-state comparison of the impact of fiscal policy choices on
household spending. They can be used to improve the regional
input-output models developed by regional economists in state
governments and academia. They can be used to assess purchasing power potential for marketing. Finally, the new statistics can be used to
provide an indication of the general well-being of households in a state
economy.
This "BEA Briefing" provides a first look at the most
recent experimental PCE-by-state statistics, providing an overview of
the methodology and discussing the initial results. It also discusses
BEA's long-term plans to continue to develop and improve these
statistics.
The methodology is relatively simple, utilizing either state-level
expenditure and receipt data or price and quantity data whenever these
state-level data are available. For years when these data are not
available, wage and salary data for the industries that provide the
goods and services are used for interpolation and extrapolation. The
experimental statistics are evaluated for consistency with state-level
disposable personal income, population, and out-of-pocket household
spending. Evaluation of the extrapolated results suggests that the
methodology produces estimates that are close to the benchmark values
for years when the primary source data are not yet available.
A BEA working paper that provides a more complete description of
the methodology used to create these statistics was released earlier
this year. (1) BEA plans to continue to update potential users on the
development of these statistics. The aim of these efforts is to solicit
feedback on how the current methodology might be improved before the new
statistics become an official product of the Bureau.
Methodology
Consistency with BEA statistics
PCE by state measures spending on goods and services by, and on
behalf of, resident households in each of the 50 states and the District
of Columbia. Like PCE in the national income and product accounts
(NIPAs), PCE by state excludes residential fixed investment but includes
the net expenditures by resident nonprofit institutions serving
households (see the box "How Do Personal Consumption Expenditures
Differ From Out-of-Pocket Spending?").
The experimental PCE-by-state statistics are constructed to be
consistent with BEA's national PCE statistics with respect to
category definitions and to be consistent with BEA's regional
income statistics with respect to residency. Consistency with the
residency concepts of BEA's state personal income statistics allows
household income and consumption to be accurately compared within the
same geographic boundaries.
The same data sources that are used for the national statistics are
also used for the state statistics whenever possible. However, some of
the data sources do not provide complete coverage at the state level, so
the estimates are scaled to sum to the category totals presented in the
NIPAs. This practice of rescaling to match a national statistic is
consistent with what is done for many other BEA regional statistics,
such as the statistics on GDP by state and GDP by metropolitan area,
which are released by BEA each year.
The experimental PCE-by-state statistics use the same category
definitions as those in the NIPAs, but the differences in residency lead
to some differences between state statistics and national statistics. At
the national level, PCE covers activities that are attributable to U.S.
residents even when that activity takes place outside of the United
States. (2) National PCE includes expenditures of U.S. government
civilian and military personnel stationed abroad, regardless of the
length of their assignment.
In contrast, because the PCE-by-state statistics are designed to
correspond to the same population used to measure state disposable
personal income, PCE by state excludes the spending of U.S. personnel
stationed abroad. (3) Thus, the sum of all consumer spending in the
states and the District of Columbia is smaller than the national total
spending by the amount of net expenditures of U.S. residents abroad,
which is reported in the NIPAs in other nondurable goods. PCE by state
does include travel expenditures abroad by U.S. residents, which are
presented as part of services.
Source data and main steps
The experimental PCE-by-state statistics are created with a
relatively simple methodology and evaluation procedure that is based on
detailed state-level source data. The methodology has three main steps:
* Use state-level data to create an initial set of annual nominal
expenditure estimates for detailed categories.
* Scale the initial estimates for each detailed category across
states to match the national PCE categories and aggregate the
expenditures to the 16 categories presented in the experimental
PCE-by-state statistics.
* Adjust estimated expenditures with household survey-based data
when evaluation indicates out-of-state spending is present.
The data and methods used for the annual estimates and the
residency adjustment are described below. A more detailed explanation is
available in a working paper on BEA's Web site.
Annual estimates
Three methods are used to prepare the initial set of annual
estimates; the method used depends on the data that are available for
each spending category. For example, expenditures on housing and
utilities--the largest expenditure category of state PCE (18.0 percent
in 2011)--use price and quantity data for the tenant occupied housing
and utilities components and use state personal income for the
owner-occupied housing component. Expenditures on health care
services--the second largest category of state PCE (16.3 percent in
2011)--use annual expenditure data. Expenditures on goods and some of
the services use economic census receipts. The three methods, price
times quantity, personal income, and expenditures or receipts, are
described in greater detail below.
Price times quantity. This method is used for expenditures on
tenant-occupied housing, utilities, and higher education. For
tenant-occupied housing, housing stock and rent data available from the
Decennial Census for the years 1990 and 2000 are used for quantity and
price. For 2005-2007, data from the American Community Survey (ACS) are
used. For other years, state population growth is used to interpolate
and extrapolate expenditures to complete the series.
For utilities, three main annual data sources are used: state-level
household water usage data from the U.S. Geological Survey, regional
water price data from the National Association of Clean Water Agencies,
and state-level household usage and price data on electricity and
natural gas from the Energy Information Agency. For higher education,
enrollment and average state tuition data from the National Center for
Education Statistics are used.
Personal income. This method is used for owner-occupied housing and
for financial services and insurance. Owner-occupied housing, which is
one of the largest spending subcategories, is the expenditure that a
homeowner would make if they rented the home instead of owning it. The
source data for this subcategory are the BEA's Regional Income
Division measure of the net rental income that a homeowner would receive
if they rented the home instead of owning it. The data source for this
net rental income estimate is state-level Decennial Census and ACS data
on the value of owner-occupied housing. (4) For the financial services
and insurance category of PCE, disposable personal income by state is
used as an indicator to allocate the corresponding national expenditures
to states.
Receipts and expenditures. This method is used for most categories
of goods and for many services. For health care services, many
categories of spending correspond directly to the categories of spending
tabulated by state of residence by the Center for Medicare and Medicaid Services. Data on expenditures of religious institutions are drawn from
the National Center for Charitable Statistics. While these sources
provide annual data, wage and salary data are used to extrapolate recent
years when the source data are not yet available.
For many categories of goods and services, state-level economic
census data are used to provide benchmark estimates for 1997, 2002, and
2007. For goods, the methodology uses receipts from the Census of Retail
Trade that are based on the state in which the retailer is located.
Industry receipts from the Census of Services are used for many services
categories. For both goods and services, class-of-customer data are used
to exclude the purchases made by businesses and government.
The use of these data to create state-level PCE statistics presents
two limitations. First, they do not provide a complete time series for
the PCE-by-state statistics, because the data are only available every 5
years. This limitation is overcome by using the growth rate of wages for
the industries that sell the goods and services in each PCE category to
extrapolate and interpolate estimates for the missing years. These wage
data come from BEA's regional wage and salary series and from the
Bureau of Labor Statistics (BLS) Quarterly Census of Employment and
Wages. A test extrapolation of expenditures based on 2002 economic
census data shows that this procedure provides generally accurate
results.
Chart 1 shows a comparison of 2007 benchmarked and extrapolated
expenditures for food services and accommodations for California. The
extrapolated value for 2007 is 1.0 percent below the benchmarked
estimate. Although larger extrapolation errors can be expected for small
states, the results suggest that the extrapolated estimates provide a
reasonable approach to the missing data challenge.
A second limitation of the economic census data is that the data
reflect the state where the business that provides the goods or services
is located, not necessarily the state of the household where the goods
or services are consumed; by definition, PCE statistics should reflect
the residence of the consuming household. This limitation is overcome by
the residency adjustment, which uses household-survey-based data.
Residency adjustment
Residency adjustments are based on an analysis that compares the
census-based estimates with data related to state-level household
spending. For each category, the analysis is done with three ratios: a
state PCE to state population ratio, a state PCE to state disposable
personal income ratio, and a ratio that compares the census-based
measure to a survey-based measure derived from consumer
expenditure-based data from BLS. (5)
[GRAPHIC 1 OMITTED]
In a few cases, the analysis provides evidence that the
census-based measures assign a relatively large amount of consumer
spending to the state of the businesses that provide the goods or
services rather than to the state of residency of consumers. In these
cases, household-survey-based data are used to make a consumer residency
adjustment for out-of-state spending. (6) The main categories affected
are food services and accommodations, recreation services,
transportation services, other durable goods, and gasoline and other
energy goods. These residency adjustments make up less than 2 percent of
total PCE.
A First Look at State-Level PCE
If the PCE-by-state statistics were produced as a regular time
series, they would provide a wealth of information for analysis. Three
examples drawn from the experimental statistics show the kind of
information and comparisons that could be made.
Total spending across states
The experimental PCE-by-state statistics show the geographic
variation in total spending across states. The variation in annual
nominal total PCE expenditures largely follows the geographic
distribution of population. As table 1 shows for 2011, the highest
estimated expenditures are for California and the lowest are for
Wyoming.
The experimental PCE-by-state statistics also show substantial
variation in annual percent changes. From 1997 to 2011, the states'
total PCE expenditures grew at an average annual rate of 4.8 percent
(table 2). However, the growth in total PCE expenditures in the
Southeast, Southwest, Rocky Mountain, and Far West regions exceeded this
annual rate; the Southwest region grew at the highest annual rate of 5.5
percent. High rates of PCE growth at the state level tend to correspond
to states with high rates of disposable personal income growth. From
1997 to 2011, Utah, Wyoming, Arizona, and Texas were in the top 10
states with the highest growth in both PCE and disposable personal
income.
More pronounced cross-state differences in spending are observed at
detailed spending categories, even across the most populous states
(table 3). This table can be used to calculate budget shares by
category. For example, spending on motor vehicles and parts for all
states was $374 billion out of a total of $10.7 trillion in 2011. Thus,
the average budget share of expenditures on motor vehicles and parts
across all states was 3.5 percent, but it ranged from a low 2.3 percent
in New York to a high of 5.1 percent in Texas. Similarly, the average
budget share on housing and utilities across all states was estimated at
18.0 percent of total expenditures. These shares were 13.4 percent for
Texas and 23.6 percent for California.
Per capita spending across states
The experimental PCE-by-state statistics also show substantial
variation in per capita expenditures. Compared with California, New
York, and Florida, Texas had the highest estimated per capita spending
on motor vehicles and parts and on gasoline and other energy goods, but
it had the lowest per capita spending on housing and utilities (table
4). New York had the highest estimated per capita expenditures on health
care.
Expenditures on housing and utilities make up the largest share of
PCE by state. In 2011, Hawaii, California, and the District of Columbia
were in the highest quintile for per capita spending on housing and
utilities (chart 2). Other areas with high per capita expenditures on
housing are located along the East coast and the West coast. Overall,
states with high per capita spending on housing and utilities tend to
correspond to those with high price levels for housing services. (7) Low
per capita expenditures on housing and utilities are estimated for the
rural states of the Midwest. Based on the experimental statistics, Texas
had the lowest per capita expenditures on housing and utilities of all
the other states plus the District of Columbia.
Per capita spending across time
In addition to these cross-state variations in per capita spending
by category, the experimental PCE-by-state statistics can also show
changes over time in regional consumption on a per capita basis. For
example, this information can be useful to show the impact of the recent
recession on household spending.
From 2008 to 2009, total per capita expenditures declined by 2.8
percent (table 5). Some regions, however, experienced relatively larger
declines. The regions with the largest declines in total per capita PCE
were the Southwest and the Rocky Mountain regions (chart 3). At the
state level, spending cuts in per capita total PCE ranged from 0.2
percent in North Dakota and 0.5 percent in West Virginia to 4.8 percent
in Nevada and 4.9 percent in Wyoming (table 5). According to BEA's
state personal income statistics, between 2008 and 2009, per capita
disposable personal income also declined by the largest percentage in
Wyoming (10.1 percent) and Nevada (9.0 percent).
Next Steps
As prototype estimates are developed for release in the fall of
2014, BEA is seeking comments on potential uses of the data, the
methodology, and enhancements of the data set that would be most
valuable to users. Comments can be addressed to
[email protected].
Over the next year, planned areas of focus include the following:
the incorporation of microdata for tenant-occupied housing and net
foreign travel estimates, the development of residency-based data
sources for the consumption of financial services, and the incorporation
of improved statistical methods for outlier detection and interpolation
into the experimental methodology.
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A longer term consideration is to increase the category detail when
the underlying source data are of sufficient quality and there is
sufficient interest. One area where this is feasible is in the category
of health services, which has the potential to complement the ongoing
work on health satellite accounts at BEA.
Another longer term consideration is the development of real
PCE-by-state measures that account for differences in prices both across
states and over time. This development would allow for comparisons in
real spending by category and provide a measure of well-being based on
consumption quantities. In the recent recession, real PCE-by-state
statistics could show the relationship between changes in state GDP
growth and changes in the real expenditures. For example, with detailed
real state-level statistics, the decline in the price of gasoline could
be separated from the impact on consumption quantities of gasoline.
The development of state price indexes for the PCE-by-state
statistics would draw heavily from much of the groundwork that has been
completed by the development of regional price parities (RPPs) and real
personal income. Real personal income statistics by state were released
for the first time as prototype estimates earlier this year. This work
has produced experimental RPPs for spending categories that are similar
to BEA's PCE categories. However, they differ by category
definition as well as by the weights assigned to the component
categories. The RPP spending categories are based on weights that
correspond to the out-of-pocket spending of BLS's consumer price
index and its consumer expenditure survey rather than PCE definitions.
In addition to creating PCE-category price indexes by state from the
RPP-based data, additional state-level price indexes will also need to
be developed for categories of spending that are distinct from the
consumer expenditure survey, such as financial services that are
provided without payment, net insurance premiums, and higher education.
Acknowledgments
The authors received valuable input from many BEA staff members on
the development of the experimental statistics. In particular, they wish
to thank Ana Aizcorbe, Michael Armah, Bettina Aten, Kyle Brown, Harvey Davis, Eric Figueroa, Ian Mead, Clinton McCully, Carol Moylan, Mauricio
Ortiz, and Joel Platt. Therese McGuire of BEA's Advisory Committee
also provided valuable comments.
RELATED ARTICLE: How do personal consumption expenditures differ
from out-of-pocket spending?
Personal consumption expenditures (PCE) measures spending by the
personal sector of the economy, which consists of households and
nonprofit institutions serving households (NPISHs). A large part of PCE
consists of out-of-pocket purchases of services and new goods from
businesses, governments and government enterprises, and NPISHs. However,
PCE is distinct from out-of-pocket household spending in a number of
important ways.
Because it aims to measure the spending of the personal sector of
the economy without duplication, only the net purchases of used goods
from governments and businesses are included in PCE. The net purchase is
the difference between receipts and expenses for the used goods.
Purchases between households, such as purchases from yard sales and
Craigslist, are excluded because they are transactions within the
personal sector.
Some household purchases are made from governments and NPISHs for
things like education and health care, where the price that households
pay is less than the cost of delivering those services. How is the
remainder of those costs accounted for in final demand? Again, only
their net expenditures are included in PCE to avoid duplication in the
measurement of spending. Thus the costs incurred by the NPISHs less
sales by NPISHs to households are accounted for as a separate component
of PCE, the net expenditures of NPISHs. When similar services are
provided by the government sector in exchange for a fee, the costs that
are not paid for by households are accounted for in the national
economic accounts as government expenditures.
In addition to these out-of-pocket expenditures, PCE also includes
spending on behalf of resident households and imputations for
consumption without direct market transactions. When governments and
employers provide the payments for the services that households
purchase, but not the services directly, these services are also part of
PCE. For example, PCE includes expenditures for health care that are
paid for by Medicare, Medicaid, and employer provided insurance. When
governments provide services directly, such as through elementary and
secondary schools or through veterans hospitals, these expenditures are
not treated as part of PCE but are treated as part of government output.
An important component of PCE is the value of housing services that
home-owners consume. Because home-owners consume these services whether
or not they owe a mortgage, PCE includes an imputed measure that
represents the rent that homeowners would pay if they rented the home
that they own. PCE also includes the financial services that households
receive without direct payment, such as no-additional-fee checking
accounts, use of automated teller machines, record keeping, and the
safekeeping of deposits.
Finally, PCE excludes purchases of illegal goods and services,
because these are not part of measured economic output. When combined
with investment, government expenditures, and net exports, PCE provides
a complete picture of the final uses of economic output. For more
information on the construction of PCE in the NIPAs, see "Chapter
5: Personal Consumption Expenditures" in Concepts and Methods of
the U.S. National Income and Product Accounts at www.bea.gov.
(1.) Christian Awuku-Budu, Ledia Guci, Christopher Lucas, and Carol
Robbins, "Experimental PCE-by-State Statistics," BEA working
paper WP2013-6 (Washington, DC: BEA, June 2013); www.bea.gov.
(2.) In the NIPAs, PCE includes expenditures by persons physically
located in the United States who have resided, or expect to reside, in
the country for 1 year or more. It also includes the purchases by U.S.
government personnel stationed abroad, and by U.S. residents who are
traveling or working abroad for 1 year or less (Bureau of Economic
Analysis, "Personal Consumption Expenditures," in Concepts and
Methods of the U.S. National Income and Product Accounts, October 2009,
page 5-2).
(3.) For state and county personal income statistics, BEA considers
a resident to be a participant in a U.S. regional economy regardless of
national allegiance or duration of residence. A residence adjustment
reallocates income earned in places of work other than the
recipient's place of residence. In practice, state and county
personal income excludes the income earned by U.S. residents living
abroad but includes the income earned by foreign nationals working in
the United States (Bureau of Economic Analysis, State Personal Income
and Employment Methodology, September 2011).
(4.) The difference between PCE and net income for owner-occupied
housing is that net income is the PCE expenditure less the costs of home
ownership. These costs are intermediate goods and services consumed,
consumption of fixed capital, property taxes, net interest paid, net
transfer payments, and subsidies. The use of net income as an indicator
for PCE assumes that these intermediate costs are the same share of
imputed gross rental income for owner-occupied housing across states.
(5.) These data are expenditure weights created as part of
BEA's regional price parities; for details, see Bettina H. Men,
Eric B. Figueroa, and Troy M. Martin, "Real Personal Income and
Regional Price Parities for States and Metropolitan Areas,
2007-2011" in this issue of the SURVEY.
(6.) Four factors have the potential to affect the geography of
consumption and influence receipts-based statistics. First, neighboring states with differing sales tax rates may lead consumers living near the
border to shop in a neighboring state. Second, sparse populations or
high urban rents lead consumers to travel to a neighboring state for
particular products that are not available in their local area. Third,
regional transportation hubs, such as regional airports, lead consumers
to travel to other states for transportation services. Fourth, travel
and tourism leads consumers to travel to locations with recreation or
other amenities outside of their home state.
(7.) Bettina H. Aten, Eric B. Figueroa, and Troy M. Martin,
"Research Spotlight: Regional Price Parities by Expenditure Class,
2005-2009," SURVEY OF CURRENT BUSINESS (May 2011): 73-87.
Table 1. State Total Personal Consumption Expenditures, 2011
[Millions of dollars]
2011
Sum of states (1) 10,720,970
New England 606,087
Connecticut 149,799
Maine 48,161
Massachusetts 295,906
New Hampshire 50,588
Rhode Island 38,294
Vermont 23,340
Mideast 1,846,930
Delaware 33,731
District of Columbia 32,322
Maryland 226,128
New Jersey 357,393
New York 759,284
Pennsylvania 438,073
Great Lakes 1,499,084
Illinois 445,298
Indiana 201,214
Michigan 308,266
Ohio 358,501
Wisconsin 185,805
Plains 683,270
Iowa 95,521
Kansas 88,322
Minnesota 193,460
Missouri 193,565
Nebraska 59,222
North Dakota 25,438
South Dakota 27,742
Southeast 2,560,805
Alabama 135,795
Arkansas 80,010
Florida 694,560
Georgia 304,882
Kentucky 127,466
Louisiana 147,588
Mississippi 83,549
North Carolina 295,952
South Carolina 143,253
Tennessee 197,824
Virginia 292,843
West Virginia 57,085
Southwest 1,188,176
Arizona 221,613
New Mexico 65,371
Oklahoma 115,960
Texas 785,232
Rocky Mountain 366,232
Colorado 178,017
Idaho 49,238
Montana 35,433
Utah 84,094
Wyoming 19,450
Far West 1,970,386
Alaska 25,438
California 1,404,891
Hawaii 50,620
Nevada 93,350
Oregon 135,232
Washington 260,854
(1.) The PCE for the sum of states equals national PCE less net
expenditures abroad by U.S. residents.
NOTE. The experimental statistics are based on the national PCE
statistics from the national income and product accounts before the
comprehensive revision that was released on July 31, 2013. Statistics
on expenditures may not sum to the regions' PCE totals because of
rounding.
Source. Authors' calculations.
Table 2. Percent Change from Preceding Period in State Total
Personal Consumption Expenditures
1998 1999 2000 2001 2002 2003
Sum of states (1) 6.2 7.2 7.7 4.7 4.1 4.9
New England 6.1 7.1 7.0 6.2 4.6 5.7
Connecticut 5.6 6.5 5.0 5.7 4.7 4.3
Maine 6.7 8.1 6.1 6.9 6.0 5.4
Massachusetts 6.4 7.1 7.7 6.4 3.5 5.7
New Hampshire 6.4 8.4 8.1 6.1 6.5 7.4
Rhode Island 5.2 7.1 9.4 5.7 6.9 8.3
Vermont 5.5 7.7 7.9 7.3 6.4 5.7
Mideast 5.6 6.7 7.2 4.8 4.5 5.1
Delaware 6.9 8.7 7.6 6.4 3.4 6.2
District of Columbia 1.0 4.5 10.1 4.2 6.9 2.5
Maryland 5.9 7.9 8.1 6.3 4.7 5.6
New Jersey 5.8 5.9 7.1 5.1 5.3 5.1
New York 5.6 7.0 7.2 4.3 4.3 5.4
Pennsylvania 5.5 6.5 6.7 4.5 3.9 4.7
Great Lakes 5.4 6.5 7.1 3.8 2.9 3.6
Illinois 5.3 5.7 8.1 3.8 2.5 3.5
Indiana 5.8 7.1 6.9 4.1 3.4 3.8
Michigan 4.4 6.4 5.6 3.6 2.6 2.7
Ohio 5.9 6.4 7.5 3.5 3.0 3.7
Wisconsin 5.8 8.1 7.0 4.7 3.9 5.2
Plains 6.1 7.2 7.2 5.0 3.6 4.7
Iowa 5.7 7.2 6.2 3.1 2.4 4.0
Kansas 6.9 6.2 5.3 4.4 3.5 4.3
Minnesota 6.2 8.8 9.7 5.3 3.4 4.8
Missouri 6.1 6.3 6.4 5.4 4.2 4.5
Nebraska 6.0 7.5 7.2 6.4 3.0 5.6
North Dakota 5.2 4.9 6.2 5.7 6.0 5.4
South Dakota 5.2 7.7 6.2 5.2 5.2 6.7
Southeast 6.2 7.1 7.8 4.9 4.2 5.3
Alabama 5.0 6.3 5.6 5.1 5.1 4.1
Arkansas 5.5 7.1 7.9 5.0 4.1 5.1
Florida 6.5 6.0 8.3 5.8 5.0 6.2
Georgia 6.9 8.0 8.7 5.1 3.6 5.3
Kentucky 6.0 7.3 7.9 3.4 4.3 4.4
Louisiana 5.3 4.8 5.6 3.3 3.6 6.8
Mississippi 6.9 7.6 6.4 5.0 4.2 5.6
North Carolina 6.6 8.5 8.8 4.4 3.2 4.1
South Carolina 6.7 8.4 7.2 4.5 4.1 4.4
Tennessee 5.7 7.0 7.1 3.8 3.2 4.4
Virginia 6.4 8.2 8.5 5.5 5.4 6.3
West Virginia 4.6 5.8 6.8 6.3 2.7 3.3
Southwest 7.4 7.7 8.5 4.0 3.7 4.9
Arizona 7.8 8.8 8.6 5.3 5.8 6.4
New Mexico 5.1 6.3 5.4 6.4 5.8 5.9
Oklahoma 5.6 6.3 7.0 5.3 2.4 5.3
Texas 7.7 7.8 8.9 3.3 3.2 4.3
Rocky Mountain 6.8 8.6 8.8 5.7 4.2 3.9
Colorado 7.2 9.6 9.8 5.8 3.0 3.1
Idaho 6.5 8.3 9.1 5.2 5.6 6.3
Montana 5.4 7.2 7.6 6.6 6.2 5.6
Utah 6.9 7.3 7.7 5.4 4.7 2.9
Wyoming 6.1 8.3 5.1 5.8 9.1 8.4
Far West 7.1 7.8 8.2 4.5 4.6 5.3
Alaska 5.4 7.6 6.6 6.7 7.4 6.0
California 6.7 7.7 8.6 4.6 4.7 5.3
Hawaii 2.6 5.3 6.6 3.5 2.6 5.6
Nevada 8.2 10.7 8.7 7.5 5.1 8.2
Oregon 6.5 8.6 6.3 4.2 4.8 3.7
Washington 10.1 7.1 7.6 3.3 3.4 5.1
2004 2005 2006 2007 2008
Sum of states (1) 6.0 6.4 5.7 5.1 2.7
New England 5.5 4.9 4.1 4.2 3.2
Connecticut 5.5 5.1 5.0 4.5 2.7
Maine 6.2 4.6 5.0 4.7 3.0
Massachusetts 5.6 5.1 3.8 4.5 3.8
New Hampshire 4.6 4.8 3.2 2.8 2.6
Rhode Island 4.2 4.5 2.4 3.0 1.8
Vermont 6.5 4.6 4.1 4.2 4.6
Mideast 5.7 5.5 4.7 4.9 2.9
Delaware 7.0 6.2 5.6 4.9 2.8
District of Columbia 9.1 3.7 7.8 3.9 4.9
Maryland 7.0 6.8 5.3 4.3 2.2
New Jersey 5.2 4.5 5.2 4.5 2.1
New York 5.9 6.0 4.6 5.3 3.5
Pennsylvania 4.7 5.1 4.0 5.2 2.9
Great Lakes 4.2 4.3 3.7 4.3 2.0
Illinois 4.7 5.8 5.0 6.2 2.0
Indiana 5.1 4.3 3.9 4.3 2.7
Michigan 3.6 2.5 2.3 2.6 2.2
Ohio 3.0 3.7 2.4 3.6 1.0
Wisconsin 5.3 5.2 5.3 4.0 3.1
Plains 4.9 4.5 4.6 4.8 3.5
Iowa 5.7 4.8 5.1 4.3 3.7
Kansas 4.5 4.2 5.4 4.8 3.6
Minnesota 5.4 3.8 4.0 4.6 3.4
Missouri 4.2 4.7 4.4 4.8 3.5
Nebraska 5.0 5.4 4.7 4.9 3.3
North Dakota 4.3 4.9 5.6 6.1 3.0
South Dakota 4.8 4.9 5.4 5.4 4.4
Southeast 6.8 7.6 6.4 5.1 2.2
Alabama 6.0 6.1 5.3 4.2 1.9
Arkansas 4.1 6.6 5.4 5.2 2.6
Florida 8.9 10.9 8.5 3.5 1.4
Georgia 5.4 7.0 6.2 6.1 1.3
Kentucky 5.5 4.9 4.2 4.1 2.6
Louisiana 5.4 4.1 5.0 8.4 4.1
Mississippi 5.0 6.8 6.7 6.6 2.3
North Carolina 6.5 6.5 5.9 7.3 3.2
South Carolina 6.5 6.6 6.3 7.3 3.1
Tennessee 5.7 6.0 5.7 5.6 1.4
Virginia 8.0 8.0 5.6 3.8 2.9
West Virginia 5.7 4.1 4.5 4.9 3.8
Southwest 6.6 8.4 7.9 6.0 3.4
Arizona 9.2 12.4 10.9 5.3 2.4
New Mexico 7.1 8.3 6.2 7.3 4.6
Oklahoma 5.4 7.4 7.7 7.1 4.3
Texas 6.0 7.5 7.2 5.9 3.5
Rocky Mountain 5.1 6.8 7.6 6.5 3.4
Colorado 4.1 4.6 5.2 5.4 3.4
Idaho 6.2 11.7 10.0 5.5 2.8
Montana 6.8 8.7 8.5 7.3 4.9
Utah 7.0 8.6 11.0 9.2 2.7
Wyoming 2.5 5.1 9.2 7.0 6.1
Far West 7.1 7.7 6.3 5.3 2.6
Alaska 5.2 4.1 3.6 5.1 4.7
California 7.0 7.5 5.9 4.6 2.3
Hawaii 8.6 9.1 6.6 5.6 3.5
Nevada 13.8 12.3 8.7 6.2 3.0
Oregon 6.4 7.5 8.0 7.0 1.6
Washington 6.1 6.7 7.4 7.8 4.3
2009 2010 2011 Average
1998-
2011
Sum of states (1) -1.9 3.8 5.0 4.8
New England -1.4 3.6 4.3 4.7
Connecticut -1.4 2.4 4.0 4.3
Maine -1.5 3.0 3.8 4.9
Massachusetts -1.2 4.5 4.8 4.8
New Hampshire -1.7 2.3 4.0 4.7
Rhode Island -1.8 3.3 3.4 4.5
Vermont -1.8 4.5 3.7 5.1
Mideast -1.6 3.7 4.7 4.6
Delaware -0.9 3.4 5.5 5.3
District of Columbia -0.7 5.8 5.7 5.0
Maryland -1.1 3.0 4.1 5.0
New Jersey -2.8 2.9 3.8 4.3
New York -1.4 4.5 5.6 4.8
Pennsylvania -1.5 3.4 4.3 4.3
Great Lakes -2.8 2.9 4.9 3.8
Illinois -3.0 2.7 4.6 4.1
Indiana -1.7 3.3 5.3 4.2
Michigan -3.4 2.8 5.2 3.1
Ohio -2.7 2.9 4.8 3.5
Wisconsin -2.4 2.8 4.3 4.5
Plains -1.9 3.2 5.3 4.5
Iowa -1.8 3.1 6.6 4.3
Kansas -1.5 2.6 5.1 4.2
Minnesota -2.9 3.0 5.1 4.6
Missouri -1.7 2.8 4.3 4.3
Nebraska -1.7 3.6 4.5 4.7
North Dakota 1.0 7.3 11.3 5.5
South Dakota -0.2 5.4 6.3 5.2
Southeast -1.9 3.9 5.1 5.1
Alabama -2.4 3.6 3.9 4.3
Arkansas -1.3 3.2 5.2 4.7
Florida -1.9 3.7 5.7 5.6
Georgia -2.2 3.7 5.2 5.0
Kentucky -1.0 3.8 4.9 4.5
Louisiana -0.3 4.4 5.4 4.7
Mississippi -2.2 3.2 4.6 4.9
North Carolina -2.1 4.2 4.7 5.1
South Carolina -2.6 5.0 4.8 5.2
Tennessee -2.7 4.6 5.7 4.5
Virginia -2.0 3.6 4.7 5.3
West Virginia -0.1 3.8 5.5 4.4
Southwest -1.6 4.3 6.1 5.5
Arizona -2.9 3.3 5.0 6.3
New Mexico -1.9 3.0 4.5 5.3
Oklahoma -1.2 4.6 6.1 5.2
Texas -1.3 4.6 6.6 5.4
Rocky Mountain -1.9 3.3 5.5 5.3
Colorado -2.2 2.9 5.1 4.8
Idaho -1.8 4.0 6.2 6.1
Montana -1.7 3.4 5.7 5.9
Utah -1.4 4.0 5.8 5.8
Wyoming -2.5 2.5 4.4 5.5
Far West -1.8 4.4 4.6 5.3
Alaska -0.2 4.0 5.5 5.1
California -2.1 4.7 4.1 5.1
Hawaii -0.2 3.4 4.6 4.8
Nevada -3.7 2.7 5.3 6.9
Oregon -2.2 2.9 5.1 5.0
Washington -0.1 4.0 7.0 5.7
(1.) The PCE for the sum of states equals national PCE less net
expenditures abroad by U.S. residents.
NOTE. The experimental statistics are based on the national PCE
statistics from the national income and product accounts before the
comprehensive revision that was released on July 31, 2013.
Source. Authors' calculations.
Table 3. State Personal Consumption Expenditures by Major Type
of Product for the Four Most Populous States, 2011
[Millions of dollars]
Line Sum of all California
states (1)
Personal consumption expenditures 1 10,720,970 1,404,891
Goods 2 3,616,748 401,474
Durable goods 3 1,146,422 135,101
Motor vehicles and parts 4 373,595 37,131
Furnishings and durable
household equipment 5 251,703 29,875
Recreational goods and
vehicles 6 340,117 43,298
Other durable goods 7 181,006 24,798
Nondurable goods 8 2,470,326 266,373
Food and beverages purchased
for off-premises consumption 9 810,188 95,639
Clothing and footwear 10 349,183 45,101
Gasoline and other energy
goods 11 428,303 39,204
Other nondurable goods 12 882,652 86,429
Services 13 7,104,222 1,003,417
Household consumption
expenditures (for
services) 14 6,812,279 962,698
Housing and utilities, 15 1,929,948 331,569
Health care 16 1,751,619 214,623
Transportation services 17 302,022 38,064
Recreation services 18 394,534 51,102
Food services and
accommodations 19 670,947 88,619
Financial services and insurance 20 807,053 105,272
Other services 21 956,156 133,449
Final consumption expenditures of
nonprofit institutions serving
households (NPISHs) (2) 22 291,943 40,719
Gross output of nonprofit
institutions (3) 23 1,164,469 132,891
Less: Receipts from sales of
goods and services by
nonprofit institutions (4) 24 872,526 92,172
New Texas Florida
York
Personal consumption expenditures 759,284 785,232 694,560
Goods 235,508 298,186 249,132
Durable goods 71,557 101,684 77,857
Motor vehicles and parts 17,771 39,828 23,716
Furnishings and durable
household equipment 16,980 19,842 18,207
Recreational goods and
vehicles 24,599 26,609 26,473
Other durable goods 12,207 15,405 9,462
Nondurable goods 163,952 196,501 171,275
Food and beverages purchased
for off-premises consumption 47,887 63,072 51,186
Clothing and footwear 30,078 29,901 18,135
Gasoline and other energy
goods 27,584 37,759 20,868
Other nondurable goods 58,403 65,769 81,087
Services 523,776 487,047 445,428
Household consumption
expenditures (for
services) 488,889 473,189 431,625
Housing and utilities, 126,765 105,284 137,980
Health care 131,371 122,667 108,148
Transportation services 21,421 25,827 17,616
Recreation services 26,444 29,883 20,986
Food services and
accommodations 50,599 54,979 44,013
Financial services and insurance 57,871 64,271 49,954
Other services 74,418 70,278 52,930
Final consumption expenditures of
nonprofit institutions serving
households (NPISHs) (2) 34,887 13,858 13,803
Gross output of nonprofit
institutions (3) 121,481 58,309 53,801
Less: Receipts from sales of
goods and services by
nonprofit institutions (4) 86,594 44,451 39,998
(1.) The PCE for the sum of states equals national PCE less net
expenditures abroad by U.S. residents, which is a component of
other nondurable goods.
(2.) Net expenses of NPISHs are defined as their gross operating
expenses less primary sales to households.
(3.) Gross output is net of unrelated sales, secondary sales, and
sales to business, to government, and to the rest of the world;
excludes own-account investment (construction and software).
(4.) Excludes unrelated sales, secondary sales, and sales to
business, to government, and to the rest of the world; includes
membership dues and fees.
NOTE. The experimental statistics are based on the national PCE
statistics from the national income and product accounts before the
comprehensive revision that was released on July 31, 2013. The
expenditures for each category may not sum to the PCE totals
because of rounding.
Source. Authors' calculations.
Table 4. Per Capita Spending on Selected Expenditure Categories for
the Four Most Populous States, 2011
[Dollars]
Motor Gasoline
vehicles Housing Health other
parts utilities care energy
goods
United States 1,199 6,194 5,622 1,375
California 985 8,797 5,694 1,040
Texas 1,551 4,101 4,778 1,471
New York 913 6,512 6,749 1,417
Florida 1,244 7,240 5,675 1,095
NOTE. The experimental statistics are based on the national PCE
statistics from the national income and product accounts before the
comprehensive revision that was released on July 31, 2013.
Source. Authors' calculations.
Table 5. Percent Change from Preceding Period in Per Capita State
Total Personal Consumption Expenditures, 2008-2009
2009
Sum of states (1) -2.8
New England -1.8
Connecticut -1.8
Maine -1.4
Massachusetts -1.9
New Hampshire -1.7
Rhode Island -1.7
Vermont -1.9
Mideast -2.2
Delaware -1.7
District of Columbia -2.7
Maryland -1.9
New Jersey -3.3
New York -1.9
Pennsylvania -1.9
Great Lakes -2.9
Illinois -3.3
Indiana -2.3
Michigan -2.9
Ohio -2.8
Wisconsin -2.9
Plains -2.6
Iowa -2.3
Kansas -2.3
Minnesota -3.5
Missouri -2.3
Nebraska -2.6
North Dakota -0.2
South Dakota -1.2
Southeast -2.9
Alabama -3.2
Arkansas -2.0
Florida -2.6
Georgia -3.4
Kentucky -1.6
Louisiana -1.5
Mississippi -2.6
North Carolina -3.6
South Carolina -3.9
Tennessee -3.6
Virginia -3.2
West Virginia -0.5
Southwest -3.3
Arizona -3.8
New Mexico -3.1
Oklahoma -2.5
Texas -3.2
Rocky Mountain -3.6
Colorado -3.8
Idaho -3.0
Montana -2.4
Utah -3.5
Wyoming -4.9
Far West -2.9
Alaska -1.8
California -3.0
Hawaii -1.3
Nevada -4.8
Oregon -3.3
Washington -1.7
(1.) The PCE for the sum of states equals national PCE less net
expenditures abroad by U.S. residents.
NOTE. The experimental statistics are based on the national PCE
statistics from the national income and product accounts before the
comprehensive revision that was released on July 31, 2013.
Source. Authors' calculations.