Local area personal income for 2014.
Lenze, David G.
PERSONAL INCOME grew substantially faster in the metropolitan
portion of the United States (4.6 percent) in 2014 than in the
nonmetropolitan portions (3.2 percent). (1) The percent change across
counties ranged widely, from -35.1 percent in Wallace County, Kansas, to
83.7 percent in McPherson County, Nebraska. (2) However, more than
three-fourths of the metropolitan counties and more than one-half of the
nonmetropolitan counties grew at rates between 1.1 percent and 6.0
percent (chart 1). (3) Inflation, as measured by the national price
index for personal consumption expenditures, was 1.4 percent in 2014.
The local area personal income estimates presented in this article
continue the successively more detailed series of data releases from the
Bureau of Economic Analysis (BEA) that depict the geographic
distribution of the nation's personal income for 2014. National
estimates of personal income for 2014 were released in January 2015,
followed by preliminary state personal income estimates in March. The
local area personal income estimates provide the first glimpse of
personal income for 2014 in counties and metropolitan statistical areas
(MSAs). The geographic picture will be completed with the release of
real personal income for states and metropolitan areas in July 2016.
The estimates discussed in this article incorporate the results of
the annual revisions of the national income and product accounts (NIPAs)
and state personal income accounts, which were released in July and
September 2015, respectively. In 2016, the estimates of gross domestic
product (GDP) by metropolitan area for 2014 and earlier years will be
revised to incorporate the results of these annual revisions of the
national, state and local area personal income accounts.
County Growth
With 14 percent of the U.S. population and 12 percent of the wage
and salary employment, the nonmetropolitan portion of the country
accounted for slightly less than 10 percent of the nation's
earnings in 2014. However, reflecting the rural affinity of much mining
and farming, the nonmetropolitan portion of the United States accounted
for more than 36 percent of national earnings in the natural resource
industries (table A). The nonmetropolitan area also accounted for 15.1
percent of manufacturing and utilities earnings, 11.9 percent of
government earnings, and 11.9 percent of transportation and warehousing
earnings. In contrast, relatively little--2.9 percent--of earnings in
the information industry was generated in nonmetropolitan counties.
Personal income growth in the metropolitan portion accelerated to
4.6 percent in 2014 from 1.1 percent in 2013 (table B). Much of the
acceleration was attributable to net earnings--which grew 4.8 percent in
2014, up from 1.3 percent--and to property income (dividends, interest,
and rent)--which grew 4.0 percent in 2014, after falling 1.1 percent.
Personal income growth in the nonmetropolitan portion of the United
States also accelerated, but not as much.
[GRAPHIC OMITTED]
Population in the metropolitan portion of the U.S. grew 0.9 percent
in 2014, the same as in 2013 (table C). Wage and salary employment
growth accelerated to 2.2 percent in 2014 up from 1.8 percent in 2013.
Employment growth in the nonmetropolitan portion of the United States
also accelerated in 2014 to 1.0 percent, but continued to grow at less
than half the pace than of the metropolitan portion. Nonmetropolitan
population declined slightly in 2014--about 0.1 percent--as it did in
2013.
Teton County, Wyoming, had the highest per capita personal income
in 2014, $194,485, more than four times the national average of $46,049
(chart 2). The next three counties with the highest per capita personal
incomes were New York, New York ($148,002); Wheeler, Nebraska
($135,907); and Williams, North Dakota ($121,538). The major sources of
personal income of these counties differ substantially (table D):
* Almost three-fourths of the personal income in Teton County was
in the form of dividends, interest, and rent. The sensitivity of Teton
County's income to financial conditions is evident by the 28
percent decline in per capita personal income in 2009 (chart 2).
* Wheeler County and Williams County, in contrast, had relatively
little property income--but net earnings in these counties exceeded
$100,000 per person. The high net earnings in these counties is
relatively recent. In 2007, both counties had per capita net earnings
below the national average.
* The recent surge in per capita personal income in Wheeler County
is attributable to farming, especially livestock production. Indeed,
farm proprietors' income per proprietor was $464,178 in 2014 in
Wheeler County.
* The recent surge in per capita income in Williams County is
related to the development of the Bakken shale formation, which
stimulated growth, especially in the mining, construction, and
transportation industries.
* Both property income and net earnings contributed to New York
County's high per capita personal income. The rather small
populations of Williams County (32,000 residents), Teton County
(23,000), and Wheeler County (766) stand in sharp contrast to New York
County's 1.6 million residents in 2014.
[GRAPHIC OMITTED]
Wheeler County, Georgia, had the lowest per capita personal income
of all counties in 2014 (chart 3). Its per capita personal income of
$15,787 was about a third of the national average of $46,049 (table E).
Part of the reason for the relatively low per capita personal income is
the large share of population living in group quarters--almost a third.
Many of these are prisoners with little income. Union County, Florida;
Telfair County, Georgia; and Elliott County, Kentucky, the next three
counties with the lowest per capita personal incomes, are similar in
having a relatively large number of prisoners with little income.
Updated Data Sources and Definitions
Along with the release of new estimates for 2014, BEA released
revised estimates of local area personal income for 1969-2013. BEA
typically revises the estimates for the preceding 2 years when it
updates the local area personal income statistics in order to
incorporate the results of the annual revisions of the national income
and product accounts (NIPAs) and the state personal income accounts and
to incorporate local area source data that are more complete and more
detailed than those previously available (such as the newly available
results of the 2012 Census of Agriculture).
In addition, this year's release of the local area personal
income accounts introduced the following ten improvements.
The new treatment of federal refundable income tax credits
introduced in the annual revision of the NIPAs. (4) Previously, the
portion of the refundable federal income tax credits that was not
directly paid to taxpayers as refunds (that is, the amount up to, but
not exceeding, their total income tax liability) was recorded as a
reduction in the income taxes paid by persons to the federal government,
and the portion that was paid to taxpayers as refunds (that is, any
excess of the credits over the liability) was recorded as personal
current transfer receipts. The total amount of the refundable tax
credits is now recognized as a transfer from the government sector to
the household sector. As a result, estimates of personal current
transfer receipts have been revised up to reflect the total amount of
the refundable tax credits. This affected estimates of personal current
transfer receipts, and personal income, starting with 1976 when the
earned income tax credit was introduced. (5)
[GRAPHIC OMITTED]
County-level data are available from the Internal Revenue Service
for the earned income tax credit and the additional child tax credit.
For the other tax credits, state estimates are allocated to counties
using a related series, such as the number of tax returns or household
population.
Property income. Previously, BEA allocated the state estimates of
personal dividend income and personal interest income (excluding imputed
receipts from pension plans) and monetary rental income of persons
(excluding farms owned by nonoperator landlords) to counties using
county tabulations of dividends, taxable and nontaxable interest, and
gross rent and royalties reported on individual income tax return Form
1040 (and associated schedules) from the Individual Master File (IMF) of
the Internal Revenue Service (IRS). These are tabulations of the returns
processed in the first 39 weeks of the year. Beginning with data for
2009, the IRS is providing BEA with tabulations of all returns filed
during the calendar year. The automatic 4-month extension of the due
date for filing income tax returns was increased to 6 months for tax
year 2005. This led to a substantial increase in the amount of income
reported on returns processed in the last 13 weeks of the year. The
returns processed at the end of the year tend to be the returns of
high-income taxpayers and tend to be more geographically concentrated
than the returns processed in the first 39 weeks. In order to avoid a
break in the time series estimates due to the switch from the 39-week
tabulations to the 52-week tabulations, BEA carried back, at a
decreasing rate, the income reported on end-of-year returns from 2009 to
1990 for dividends and interest and to 1998 for monetary rent.
Residence adjustment. Previously, the residence adjustment was
based on extrapolations of the journey-to-work data from the 2000 Census
of Population and on wages reported on IRS Form 1040. The
journey-to-work data are tabulations of the wages and salaries of the
employees in a given place-of-work county by their place of residence.
The data are cross tabulated by industry. BEA revised the residence
adjustment from 2002 to 2013 using a special tabulation of the
journey-to-work data from the 2006-2010 American Community Survey 5-year
estimates prepared by the Census Bureau for BEA. In addition, as
discussed above, the IRS is now providing BEA with tabulations of the
wages reported on all income tax returns filed during the calendar year.
Unemployment compensation for railroad employees. Previously, BEA
allocated the state estimates of unemployment compensation for railroad
employees, a component of personal current transfer receipts, using
county-level data from the Census Bureau's Federal Assistance Award
Data Systems (FAADS). Because FAADS was terminated, BEA now uses similar
data published on the Treasury Department's USAspending.gov Web
site. County estimates have been revised beginning with 2009.
Railroad retirement and disability benefits. Previously, BEA
allocated the state estimates of railroad retirement and disability
benefits, a component of personal current transfer receipts, using
county-level data from the Census Bureau's FAADS. BEA now uses
similar data published on the Treasury Department's USAspending.gov
Web site. County estimates have been revised beginning with 2009.
Veterans benefits. Veterans benefits are a component of personal
current transfer receipts. BEA allocates the national estimates of (1)
veterans pension and disability benefits, (2) veterans readjustment
benefits, and (3) veterans life insurance benefits to states on the
basis of the Geographic Distribution of VA Expenditures (GDX) Report
from the Department of Veterans Affairs. Previously, BEA allocated the
state estimates to counties on the basis of data from FAADS. Because the
GDX Report has data for counties as well as for states, starting with
the estimates for 2009, the GDX data are now used as the allocating
series for both counties and states.
Higher education student assistance. Previously, BEA allocated the
state estimates of higher education student assistance, a component of
personal current transfer receipts, to counties using county-level
payments data from the Census Bureau's Consolidated Federal Funds
Report. Because the federal financial statistics program was terminated,
BEA now uses Pell Grant data published on the Treasury Department's
USAspending.gov Web site. These fiscal year data are available by the
nine-digit ZIP codes associated with the Pell Grant recipients'
schools and the amount of the grants disbursed to their schools. BEA
converts the data to calendar years and sums the ZIP codes up to
counties. County estimates were revised beginning with 2009.
Indemnity payments from crop insurance. These payments are a
component of "imputed and miscellaneous income received"
(table CA45). Previously, BEA allocated the state estimates of indemnity
payments (benefits) from crop insurance to counties using data for
"crop and livestock insurance payments" from the Census of
Agriculture, which is conducted every 5 years. Starting with estimates
for 2008, annual crop indemnities data by county from the Risk
Management Agency of the U.S. Department of Agriculture (USDA) are now
used to allocate the state estimates. The losses covered by crop
insurance are highly location and time specific. The use of
administrative data rather than survey data and the use of annual data
rather than quinquennial data improves the accuracy and timeliness of
the county estimates.
Government payments. Previously, BEA allocated the state estimates
of government payments to farmers to counties using administrative data
from the Farm Services Agency. These county data represented about 80
percent of the state control totals on average. Beginning with estimates
for 2007, BEA now uses the Farm Services Agency data plus conservation
payments data from the Natural Resource Conservation Service of USDA to
distribute the state estimates of government payments to counties. The
combined data account for about 90 percent of the state controls.
Revised boundaries for three Alaska counties. On January 3, 2013,
Petersburg Borough was incorporated as Alaska's 19th organized
borough. The new borough retained the most populous portion of the
former Petersburg Census Area (with 3,202 residents) and gained a
portion of the Hoonah-Angoon Census Area (with one resident). The
remainder of the former Petersburg Census Area (with 613 residents) was
added to the Prince of Wales-Hyder Census Area (chart 4). (6) The new
Petersburg Borough retains the same federal information processing
standards (FIPS) code as the former Petersburg Census Area, but because
of the boundary change, there is now a break between 2012 and 2013 in
the time series estimates for this county. (7) Statistics for 2009-2012
continue to reflect the boundaries of the old census area; statistics
for 2013-2014 reflect the boundaries of the new borough. The source data
used to estimate wages and salaries and property income are currently
compiled on the basis of the new boundaries. BEA adjusted the other
source data to reflect those boundaries.
[GRAPHIC OMITTED]
Magnitude of revisions
For many counties, the picture of personal income shown by the
revised estimates is similar to the picture shown by the previous
estimates (table F). Sixty percent or more of the counties in every year
had personal income revisions of less than 5 percent in absolute value.
For example, in 2008, 15 percent of the revisions to county personal
income were less than 1 percent, and 50 percent were between 1 percent
and 5 percent. Only 10 percent of the 3,112 counties were revised 10
percent or more. For the most recent years, there were more large
revisions--15 percent of the counties were revised 10 percent or more in
2013--but this often reflected the replacement of preliminary estimates
of certain components of personal income based on simple extrapolations
with estimates based on recently released source data.
Source Data
The primary 2014 county-level data used by BEA to prepare the
estimates of local area personal income presented in this article were
wage and salary data from the Bureau of Labor Statistics, benefits paid
by the Social Security Administration, Medicare enrollment and
fee-for-service expenditure data from the Centers for Medicare and
Medicaid Services, and Medicaid payments from state departments of
social services. In addition, IRS tabulations of 2013 federal income tax
returns were used, primarily for dividends, interest, nonfarm
proprietors' income, and the residence adjustment. (8)
Other 2014 county-level data used by BEA to prepare estimates of
various components of local area personal income include the following
(table G):
* For local area farm income, farm cash receipts, government
payments, crop production, livestock stocks, and crop insurance
indemnity payments by county for 2014 from the USDA and state offices of
agricultural statistics were used.
* For military earnings, the number of full-time military and coast
guard personnel by county for 2014 from the Departments of Defense and
Homeland Security was used.
* For state unemployment insurance compensation, county-level data
for 2014 from state employment security agencies were used.
* For a few small components of personal income, population
(excluding population in group quarters) by county for 2014 from the
Census Bureau was used to allocate state estimates to the counties.
By David G. Lenze
(1.) Personal income, which is measured in current dollars, is the
sum of net earnings by place of residence, property income, and personal
current transfer receipts.
(2.) Both Wallace and McPherson counties are nonmetropolitan.
Personal income growth rates for metropolitan counties ranged from -26.5
percent in Lynn County, Texas (in the Lubbock MSA) to 23.4 percent in
Oldham County, Texas (in the Amarillo MSA).
(3.) BEA prepares estimates of personal income for 3,113 of the
counties in the United States. Some small counties (mostly in Virginia
but also in Hawaii) are combined with a larger, nearby county so that
geographic coverage is complete (for details see the appendix to the
Local Area Personal Income Methodology on BEA's Web site). For
statistical purposes, nonmetropolitan counties are those counties that
remain after metropolitan statistical areas (MSAs) have been delineated
by the Office of Management and Budget (OMB). According to the OMB, an
MSA has at least one urbanized area of 50,000 or more residents plus
adjacent territory that has a high degree of social and economic
integration with the core as measured by commuting ties. MSAs are
defined in terms of whole counties. Of the counties for which BEA
prepares personal income estimates, 1,146 are metropolitan and 1,967 are
nonmetropolitan.
(4.) See Stephanie H. McCulla and Shelly Smith, "Preview of
the 2015 Annual Revision of the National Income and Product
Accounts," SURVEY OF CURRENT BUSINESS 95 (June 2015).
(5.) Tax credits are recognized in the personal income accounts in
the year following the year of tax liability. For example, a tax credit
earned for 1996 will be recognized in the local area personal income
accounts for 1997, the year in which the tax returns are filed.
(6.) Population estimates are from the Census Bureau.
(7.) The Petersburg Census Area was created when the
Wrangell-Petersburg Census Area was split in the process of
incorporating the Wrangell City and Borough (see "Data for Newly
Organized Areas," in David G. Lenze, "Local Area Personal
Income for 2009," SURVEY OF CURRENT BUSINESS 91 (May 2011): 43-44).
(8.) For complete details about the estimation methodology and data
sources, see Local Area Personal Income Methodology on BEA's Web
site.
Data Availability
The complete set of annual personal income and employment
statistics for counties, metropolitan statistical areas, micropolitan
statistical areas, metropolitan divisions, consolidated statistical
areas, and the metropolitan and nonmetropolitan portions of states and
for all years are available interactively on BEA's Website.
The estimates were revised for 1969 forward.
The local area personal income and employment statistics are also
available through members of the BEA User Group, which consists of state
agencies and universities that help BEA disseminate the statistics in
their states. A list of the BEA user groups is available on BEA's
Website.
For more information about the statistics, contact the Regional
Income Division at 202-606-5360, fax 202-606-5322, or email
reis@bea.gov.
Alternative Measures of County Employment and Wages
Three widely used measures of county employment and wages by place
of work are (1) employment and payroll in the County Business Patterns
(CBP) series from the Census Bureau, (2) employment and wages from the
Quarterly Census of Employment and Wages (QCEW) program from the Bureau
of Labor Statistics (BLS), and (3) wage and salary disbursements and
employment from the Bureau of Economic Analysis (BEA). These measures
differ in source data and coverage.
The CBP data are derived from Census Bureau business establishment
surveys and federal administrative records. The QCEW data are
tabulations of monthly employment and quarterly wages of workers who are
covered by state unemployment insurance programs or by the unemployment
insurance program for federal employees.(1) The BEA estimates of
employment and wages are primarily derived from the BLS data; the
estimates for industries that are either not covered or not fully
covered in the QCEW are also based on supplemental data from other
agencies, such as the Department of Defense, the U.S. Department of
Agriculture, and the Railroad Retirement Board.
The coverage of the Census Bureau data differs from that of the BLS
data primarily because the Census Bureau data exclude most government
employees and because the BLS data cover civilian government
employees.(2) The CBP data also exclude several private industries that
are partly covered by the QCEW: crop and animal production; rail
transportation; insurance and employee benefit funds; trusts, estates,
and agency accounts; and private households. However, the CBP data cover
the employees of educational institutions, membership organizations, and
small nonprofit organizations in other industries more completely than
the BLS data.(3) In addition, the Census Bureau reports employment only
for the month of March; the BLS employment data are quarterly and annual
averages of monthly data.
In 2001, both BLS and BEA began to include employees of Indian
tribal councils in local government. These employees were previously
included in the relevant private industries.(4) In the Census Bureau
data, these employees are still classified in private industries.
BEA estimates of employment and wages differ from the BLS data
because BEA adjusts the estimates to account for employment and wages
that are not covered or that are not fully covered by the unemployment
insurance programs. BEA adds estimates of employment and wages to the
BLS data to bridge small gaps in coverage for nonprofit organizations
that do not participate in the unemployment insurance program (in
several industries), for students and their spouses employed by colleges
or universities, for elected officials and members of the judiciary, for
interns employed by hospitals and by social service agencies, and for
insurance agents classified as statutory employees. In addition, BEA
uses supplemental source data to estimate most, or all, of the
employment and wages for the following: farms, farm labor contractors
and crew leaders, private households, private elementary and secondary
schools, religious membership organizations, rail transportation, and
military. BEA also adjusts for employment and wages subject to
unemployment insurance, but not reported by employers. Other adjustments
to wages include estimates for unreported tips, judicial fees paid to
jurors and witnesses, compensation of prison inmates, and marriage and
license fees paid to justices of the peace. (5)
The Census Bureau released 2013 data for total employment and
payrolls for counties on its Web site on April 23, 2015. BLS released
county data on total employment and average weekly pay for 2014 on its
Web site on June 17, 2015. BEA released estimates for 2014 and revised
estimates for 2012-2013 of total wage employment and total wage and
salary disbursements for counties on its Web site on November 19, 2015.
1. The QCEW data account for 94 percent of BEA's wages and
salaries.
2. The Census Bureau data cover only those government employees who
work in government hospitals, federally chartered savings institutions
and credit unions, liquor stores, and wholesale liquor establishments,
and university publishers. The BLS data in most states exclude state and
local elected officials, members of the judiciary, state national and
air national guardsmen, temporary emergency employees, and employees in
policy and advisory positions.
3. The BLS data do not cover certain religious elementary and
secondary schools because a Supreme Court decision exempts some of these
schools from unemployment compensation taxes. The BLS data also exclude
college students (and their spouses) who are employed by the school in
which they are enrolled and student nurses and interns who are employed
by hospitals as part of their training. In half of the states, the BLS
data only include nonprofit organizations with four or more employees
during 20 weeks in a calendar year.
4. For example, employees of casinos owned by tribal councils were
included in "Amusement, Gambling, and Recreation Industries."
5. A detailed description of the sources and methods used to
prepare the estimates is available on BEA's Web site.
Table A. Industrial Structure of Metropolitan and
Nonmetropolitan Portions of the United States for 2014
Earnings by place of work
(billions of dollars)
Metropolitan Nonmetropolitan
Natural resources (1) 209.0 119.4
Construction 528.9 63.6
Manufacturing and utilities 935.1 165.9
Wholesale and retail trade 1,055.8 108.6
Transportation and warehousing 320.4 43.2
Information 349.4 10.3
Finance and insurance 710.6 28.4
Real estate and rental and leasing 219.1 12.5
Business services (2) 1,686.6 67.0
Education, health care, and social
assistance 1,215.9 110.9
Leisure, hospitality, and other (3) 765.3 83.1
Government and government
enterprises 1,563.7 211.2
Local 828.2 127.8
Total 9,559.9 1,024.1
Industry's share of area's total
earnings
(percent)
Metropolitan Nonmetropolitan
Natural resources (1) 2.2 11.7
Construction 5.5 6.2
Manufacturing and utilities 9.8 16.2
Wholesale and retail trade 11.0 10.6
Transportation and warehousing 3.4 4.2
Information 3.7 1.0
Finance and insurance 7.4 2.8
Real estate and rental and leasing 2.3 1.2
Business services (2) 17.6 6.5
Education, health care, and social
assistance 12.7 10.8
Leisure, hospitality, and other (3) 8.0 8.1
Government and government
enterprises 16.4 20.6
Local 8.7 12.5
Total 100.0 100.0
Nonmetropolitan share of national
earnings
(percent)
Natural resources (1) 36.4
Construction 10.7
Manufacturing and utilities 15.1
Wholesale and retail trade 9.3
Transportation and warehousing 11.9
Information 2.9
Finance and insurance 3.8
Real estate and rental and leasing 5.4
Business services (2) 3.8
Education, health care, and social
assistance 8.4
Leisure, hospitality, and other (3) 9.8
Government and government
enterprises 11.9
Local 13.4
Total 9.7
(1.) Consists of farm; forestry, fishing, and related activities; and
mining.
(2.) Consists of professional and technical services; management of
companies and enterprises; and administrative and waste management
services.
(3.) Consists of arts, entertainment and recreation; accommodation and
food services; and other services, except public administration.
Table B. Personal Income Change by Component
for U.S. Metropolitan and Nonmetropolitan Portions
Percent change
Dividends,
Personal Net interests Transfer
income earnings and rent receipts
2012-2013
United States 1.2 1.4 -1.0 2.5
Metropolitan portion 1.1 1.3 -1.1 2.6
Nonmetropolitan portion 1.9 2.3 0.1 2.1
2013-2014
United States 4.4 4.6 4 4.2
Metropolitan portion 4.6 4.8 4.0 4.3
Nonmetropolitan portion 3.2 2.7 3.9 3.9
Dollar change (billions of dollars)
Dividends,
Personal Net interests Transfer
income earnings and rent receipts
2012-2013
United States 160.0 125.1 -25.5 60.3
Metropolitan portion 129.6 103.4 -25.7 52.0
Nonmetropolitan portion 30.4 21.8 0.3 8.3
2013-2014
United States 618.7 411.9 104.2 102.5
Metropolitan portion 565.9 386.4 93.1 86.4
Nonmetropolitan portion 52.7 25.6 11.1 16.1
Table C. Population and Jobs for U.S. Metropolitan and Nonmetropolitan
Portions
Percent change Change
2013 2014 2013 2014
Metropolitan portion
Population 0.9 0.9 2,413,977 2,390,428
Wage and salary jobs 1.8 2.2 2,179,546 2,712,333
Nonmetropolitan portion
Population -0.1 -0.1 -28,524 -30,903
Wage and salary jobs 0.6 1.0 96,454 181,667
Table D. Personal Income and Its Major Components
[Dollars per person]
Teton, New York, Wheeler,
Wyoming New York Nebraska
Personal income 194,485 148,002 135,907
Net earnings by place of
residence 45,983 92,533 119,486
Dividends, interest, and rent 143,683 44,337 10,202
Personal current transfer
receipts 4,819 11,131 6,219
Williams,
North U.S.
Dakota average
Personal income 121,538 46,049
Net earnings by place of
residence 101,921 29,577
Dividends, interest, and rent 14,257 8,541
Personal current transfer
receipts 5,360 7,932
Table E. Personal Income and Its Major Components
[Dollars per person]
Wheeler, Union, Telfair,
Georgia Florida Georgia
Personal income 15,787 17,811 18,443
Net earnings by place of
residence 7,374 8,898 8,844
Dividends, interest, and rent 2,396 2,923 2,614
Personal current transfer
receipts 6,017 5,990 6,986
Elliott, U.S.
Kentucky average
Personal income 19,879 46,049
Net earnings by place of
residence 8,322 29,577
Dividends, interest, and rent 2,207 8,541
Personal current transfer
receipts 9,350 7,932
Time series Time lag
Personal Income Summary
Personal Income, Population, Per
Capita Personal Income (table CA1) 1969-2014 11 months
Personal Income and Employment by
Major Component (table CA4) 1969-2014 11 months
Personal Income by Major Component
and Earnings by NAICS Industry (table
CA5N) 2001-2014 11 months
Personal Income by Major Component
and Earnings by SIC Industry
(table CA5) 1969-2000 *
Compensation of Employees by NAICS
Industry (table CA6N) 2001-2014 11 months
Compensation of Employees by SIC
Industry (table CA6) 1969-2000 *
Total Full-Time and Part-Time
Employment by NAICS Industry
(table CA25N) 2001-2014 11 months
Total Full-Time and Part-Time
Employment by SIC Industry
(table CA25) 1969-2000 *
Economic Profile (table CA30) 1969-2014 11 months
Personal Current Transfer Receipts
(table CA35) 1969-2014 11 months
Farm Income and Expenses (table CA45) 1969-2014 11 months
Gross Flow of Earnings (table CA91) 1990-2014 11 months
BEA Regional Fact Sheets (BEARFACTS) 2014 11 months
Table F. Revisions to County Personal Income, 2001-2013
Revision (absolute value) Number of counties
2001 2002 (1) 2003 2004 2005 2006
0.0-0.9 percent 1,826 1,310 1,059 875 737 609
1.0-4.9 percent 1,265 1,730 1,852 1,897 1,854 1,781
5.0-9.9 percent 14 61 175 292 429 579
10.0 percent or more 5 10 25 47 91 142
Total 3,110 3,111 3,111 3,111 3,111 3,111
Revision (absolute value)
2007 2008 (2) 2009 (3) 2010 2011
0.0-0.9 percent 539 482 504 500 460
1.0-4.9 percent 1,685 1,544 1,571 1,585 1,547
5.0-9.9 percent 687 766 727 707 737
10.0 percent or more 200 320 311 321 369
Total 3,111 3,112 3,113 3,113 3,113
Revision (absolute value)
2012 2013
0.0-0.9 percent 434 398
1.0-4.9 percent 1,428 1,468
5.0-9.9 percent 822 794
10.0 percent or more 429 453
Total 3,113 3,113
(1.) For 2002 forward, the number of counties includes Broomfield
County, CO.
(2.) For 2008 forward, the number of counties reflects the division of
the Skagway-Hoonah-Angoon Census Area into the Skagway Borough and the
Hoonah-Angoon Census Area.
(3.) For 2009 forward, the number of counties reflects the division of
the Wrangell-Petersburg Census Area into the Petersburg Census Area and
the Wrangell City and Borough.
Table G. County Source Data Used to Estimate
Local Area Personal Income 1
Wages and salaries by industry
In general BLS Quarterly Census of Employment and
Wages data.
Farm USDA Census of Agriculture data.
Agriculture and forestry
support activities USDA Census of Agriculture data.
Rail transportation. RRB payroll and employment data; Census
Bureau Journey to Work (Census of
Population) data.
Educational services Census Bureau County Business Patterns
payroll data; State departments of
education employment data; DOE
Private School Universe Survey
employment data; Official Catholic
Directory number of teachers in
religious orders data.
Membership associations
and organizations Household population data (2)
Private households Household population data; (2) Census
Bureau Journey to Work (Census of
Population) data.
Military DOD personnel data; DHS Coast Guard
personnel and payroll data; Household
population data. (2)
State and local government Census Bureau American Community
Survey wage data; RRB payroll and
employment data.
Employer contributions for
employee pension and insurance
funds by industry
All industries BEA estimates of employment. (3)
Employer contributions
for government social
insurance by
industry
All industries BLS state unemployment insurance
programs employer contributions data.
Proprietors' income
Farm USDA Census of Agriculture data; USDA
National Agriculture and Statistic
Service crop production and livestock
stocks data; Cash receipts from state
offices of agricultural statistics;
USDA Farm Service Agency government
payments to farmers data; USDA Risk
Management Agency crop indemnity
payments data.
Nonfarm industries IRS data on net gross receipts of sole
proprietorships and partnerships;
Census Bureau Nonemployer Statistics.
Residence adjustment Census Bureau Journey to Work
(American Community Survey) employment
and wage data; IRS wage data.
Dividends, interest, and rent IRS income tax returns data on
dividends, taxable interest, and gross
rents and royalties; OPM federal
civilian retirement payments data; DOD
military retirement payments data;
Census Bureau Census of Housing data
on the aggregate gross rental value of
owner-occupied single family dwellings
and number of mobile homes;
USDA gross rental value of farm
dwellings data.
Personal current transfer SSA Social Security and Supplemental
receipts Security Income enrollees and benefits
data; CMS data on the number of
enrollees in the Medicare Hospital
Insurance, Supplementary Medical
Insurance, and Par t D programs; CMS
Medicare Advantage fee-for-services
expenditure data; data from the
Treasury Department's
USASpending.gov (higher education
student assistance and railroad
worker retirement and unemployment
benefits); Census Bureau Small Area
Income and Poverty Estimates (persons
and children age 0-17 in
poverty and number of Supplemental
Nutritional Assistance Program
recipients); Census Bureau American
Indian and Alaska Native Alone
population, and household population
data;2 DOD Tricare payments data; IRS
refundable income tax credit data;
Number of unemployed persons from
the BLS Local Area Unemployment
Statistics program; DVA veterans
pension, disability, life insurance,
and readjustment benefits data and
number
of pension and disability
beneficiaries; NSF federal fellowship
benefits data; Federal Reserve Bank
of New
York data on the number of mortgage
debtors, per debtor mortgage debt
balance and percent of mortgage
debt in delinquency; Medicaid payments,
Children's Health Insurance Program
enrollment, Supplemental
Nutritional Assistance Program
benefits, energy assistance payments,
general assistance benefits, and
family
assistance benefits data from the
state departments of social services;
State unemployment insurance
compensation data from the state
employment security agencies.
Employee and self-employed
contributions for government
social insurance CMS Medicare Parts B and D enrollment
data; Census Bureau American Community
Survey veteran population
data; Civilian population age 18 and
over data. (4)
(1.) BEA prepares some county estimates DHS Department of Homeland
by aggregating source data available by Security
ZIP code. DOD Department of Defense
(2.) Household population for counties DOE Department of Education
is calculated as the difference between DVA Department of Veterans
the Census Bureau population and the Affairs
Census Bureau population in group IRS Internal Revenue Service
quarters estimates. NSF National Science
(3.) See the Local Area Personal Income Foundation
Methodology for the data sources used OPM Office of Personnel
by BEA to estimate employment. Management
(4.) Civilian population for counties RRB Railroad Retirement
is based on Census Bureau population, Board
Coast Guard employment, and Department SSA Social Security
of Defense active duty military Administration
employment data, adjusted to a place USDA U.S. Department of
of residence basis. Agriculture
BEA Bureau of Economic Analysis
BLS Bureau of Labor Statistics
CMS Centers for Medicare and Medicaid
Services
National Totals of BEA County Estimates of Wages and Salaries and CBP
Payrolls and QCEW Wages
[Billions of dollars]
2012 2013 2014
Total CBP payrolls 5,414.3 5,621.7 n.a
Plus: Differences in coverage:
QCEW civilian government wages (1) 1,036.1 1,046.9 1,076.8
Other differences, net (2) 40.8 4.0 n.a
Equals: Total QCEW wages 6,491.2 6,672.6 7,017.0
Plus: BEA adjustments:
For unreported wages and
unreported tips on employment tax
returns. 76.9 77.3 86.7
For wages and salaries not covered
or not fully covered by
unemployment insurance:
Private 225.2 229.0 240.4
Government 132.1 130.5 129.7
Other BEA adjustments (3) -3.9 -3.6 -4.3
Equals: BEA estimates of wages
and salaries (4) 6,921.5 7,105.9 7,469.4