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.

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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.

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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)

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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.

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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 [email protected].

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