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To help mark the Monthly Labor Review’s centennial, the editors invited several producers and users of BLS data to take a look back at the last 100 years. This article highlights the important role of the Current Employment Statistics (CES) survey as a key source of economic information for data users seeking to obtain a timely and broad view of the U.S. labor market. The CES program publishes first estimates of employment, hours, and earnings each month, approximately 3 weeks after the week including the 12th of the month. CES estimates, widely used on their own, also serve as important inputs to other closely watched economic indicators. Among the users of CES data are government agencies, private businesses, and research organizations.
The Current Employment Statistics (CES) survey was first conducted in October 1915 for four manufacturing industries—boots and shoes, cotton goods, cotton finishing, and hosiery and underwear. The first CES data release, published in the January 1916 issue of the Monthly Review, indicated that it would be useful to employers in these industries, as well as to workers, the unemployed, and policymakers:
The amount of authoritative data concerning the ebb and flow of industrial employment in the United States is limited. The necessity for figures on this subject is apparent. Every successful employer must know his own business, and to continue successful [sic] he needs to know the condition of the industry of which his establishment is a part, for so closely are industrial affairs related that the prosperity of any establishment may be affected materially by the conditions of the industry as a whole. To the workingmen, the unemployed, and those seeking to relieve unemployment such figures are also of service.1
Over the past 100 years, the CES survey has evolved considerably. In 2015, CES published more than 900 national employment series for nonfarm and government industries. Two sets of estimates of hours and earnings for private sector employees also were produced—one for all employees and one for production employees in goods-producing industries and nonsupervisory employees in private service-providing industries. Further, numerous additional series were derived from basic estimates. CES also has expanded to produce estimates, by industry, for all 50 states, the District of Columbia, Puerto Rico, the U.S. Virgin Islands, and about 450 metropolitan areas and divisions.
CES data serve as one of the first available monthly economic indicators for evaluating the health of the U.S. economy. Each month, the U.S. Bureau of Labor Statistics (BLS) publishes estimates of employment, hours, and earnings from the CES survey. The Employment Situation, a news release combining national estimates from the CES survey and labor force data from the Current Population Survey (CPS), is published about 3 weeks after the week that includes the 12th of the month. The reference period for CES respondents is the pay period that includes the 12th of the month. BLS releases CES estimates for states and metropolitan areas about 2 weeks after the release of national estimates.
Because of their breadth of industry detail, geographic scope, and timeliness, CES data are followed closely by a wide array of economic data users—policymakers, government agencies and entities, major news media, financial market analysts in the United States and around the world, and other business and academic analysts, researchers, and forecasters. This article highlights the strengths of CES data and their important contributions as economic indicators.
The breadth and quality of CES data help one understand why data users choose to follow them. The CES survey, also known as the payroll or establishment survey, is a monthly survey of approximately 146,000 businesses and government agencies representing about 623,000 worksites throughout the United States. Using data from this sample, BLS produces and publishes estimates of employment, hours, and earnings for the nation, states, and metropolitan areas, by detailed industry. The CES survey produces over 27,000 data series for the nation and about 23,000 series for states and areas.2
CES employment series include all employees, production and nonsupervisory employees (referred to in this article as production employees),3 and women employees. Monthly employment estimates for major industry sectors and some detailed industries begin as early as 1939, but all employment series generally begin no later than 1990.
BLS also produces estimates of average hourly earnings, average weekly hours, and, for manufacturing industries, average weekly overtime hours. Hours and earnings estimates cover private sector workers in two employee sets—all employees and production employees. Since 1964, monthly estimates of hours and earnings for production employees have been produced for all private industry sectors. The hours and earnings estimates for all employees start in 2006.
BLS also derives other series, such as average weekly earnings and diffusion indexes, from the basic series of employment, hours, and earnings. Each month, CES publishes real earnings (a Principal Federal Economic Indicator) in conjunction with the release of the Consumer Price Index (CPI). Average hourly and average weekly earnings are deflated by the CPI to provide information on the real buying power of consumers.
Industry classification. All data on employment, hours, and earnings for the nation, states, and metropolitan areas are classified in accordance with the North American Industry Classification System, developed under the auspices of the Office of Management and Budget.4 The United States, Canada, and Mexico share this classification system, which allows a direct comparison of economic data across the three countries.5
Revisions. Because not all respondents report their payroll data by the initial release of employment, hours, and earnings, CES estimates are considered preliminary when first published each month. BLS continues to collect payroll data and revises estimates twice before the annual benchmark update (discussed below). For a given month, BLS publishes second preliminary estimates 1 month after the initial release and final sample-based estimates 2 months after the initial release. The estimates published with the second and third (final) releases incorporate additional data from respondents and corrected data. With each new monthly observation and the revisions to previous months’ estimates, BLS recalculates CES seasonal adjustment factors, which also can contribute to revisions in the seasonally adjusted estimates.6
Benchmarking. On an annual basis, BLS recalculates nearly 2 years of CES data in a process known as benchmarking. The process corrects for sampling and modeling error by reanchoring sample-based estimates for March of each year to nearly complete employment counts based primarily on unemployment insurance tax records.7 Historically, benchmark revisions of total nonfarm employment have been relatively small, averaging 0.3 percent (in absolute terms) from March 2005 through March 2015.8
Seasonality. CES data are available both seasonally adjusted and not seasonally adjusted. To reveal underlying economic trends, the seasonal adjustment process removes from the data the effects of normal employment variation, which results from recurring events within a year (such as holidays and weather changes). BLS uses a concurrent seasonal adjustment methodology for national CES estimates that incorporate estimates up through the current month’s data.
CES data as inputs to other important economic indicators. While CES estimates, on their own, serve as important economic indicators for analyzing the health of the U.S. economy, they also serve as inputs to other economy-wide indicators. Total nonfarm employment and aggregate weekly hours (the product of employment and average weekly hours) are considered coincident economic indicators. In other words, employment and aggregate hours are indicative of the current state of the economy and tend to move in sync with U.S. business cycles, reaching peaks and troughs at about the same time as the cycle. In fact, the Business Cycle Dating Committee of the National Bureau of Economic Research (NBER) uses CES employment data to determine turning points in the U.S. business cycle.
Table 1 shows the relationship between turning points in the U.S. business cycle, as determined by NBER, and turning points in CES employment. Eight out of 11 peak months in CES employment coincided within 3 months of the NBER peak months. Eight out of the 11 trough months coincided within 3 months of the NBER trough months. However, this coincident pattern for identifying business cycle troughs (i.e., ending points of recessions) broke down after the last two recessions. CES employment continued to decline for 21 months after the end of the 2001 recession and for 8 months after the June 2009 business cycle trough. For both recessions, NBER found that business cycle peak dates coincided with the peaks in CES employment, whereas the central indicators—real gross domestic product and real gross domestic income—gave mixed signals about the peak dates.9
NBER turning points | CES employment turning points | Months lead (lag) | |||
---|---|---|---|---|---|
Peak month | Trough month | Peak month | Trough month | Peak month | Trough month |
November 1948 | October 1949 | September 1948 | October 1949 | 2 | 0 |
July 1953 | May 1954 | July 1953 | August 1954 | 0 | (3) |
August 1957 | April 1958 | April 1957 | June 1958 | 4 | (2) |
April 1960 | February 1961 | April 1960 | February 1961 | 0 | 0 |
December 1969 | November 1970 | March 1970 | November 1970 | (3) | 0 |
November 1973 | March 1975 | July 1974 | April 1975 | (8) | (1) |
January 1980 | July 1980 | (1) | (1) | (1) | (1) |
July 1981 | November 1982 | July 1981 | December 1982 | 0 | (1) |
July 1990 | March 1991 | June 1990 | May 1991 | 1 | (2) |
March 2001 | November 2001 | February 2001 | August 2003 | 1 | (21) |
December 2007 | June 2009 | January 2008 | February 2010 | (1) | (8) |
Notes: (1) No peak or trough month declared for CES data because period of decline did not meet criteria. For information on how peaks and troughs are identified in CES data, see https://www.bls.gov/ces/tables/peak-trough.htm. Note: CES data are subject to annual benchmarking and reseasonal adjustment. Sources: U.S. Bureau of Labor Statistics and National Bureau of Economic Research. |
The Federal Reserve uses aggregate weekly hours in manufacturing, mining and logging, electric and gas utilities, and publishing industries to calculate industrial production indexes (IPIs), which measure real output in those industries.10 Investors use IPIs to analyze growth in these industries. Growth in month-over-month IPIs for a particular industry signals that companies within that industry are performing well.11
The Bureau of Economic Analysis uses aggregate weekly earnings (the product of average hourly earnings, average weekly hours, and employment ) for all private sector jobs to estimate wages and salaries for personal income, a coincident economic indicator.12
The Conference Board combines various statistics to produce its composite leading and coincident economic indexes. These indexes are designed to signal peaks and troughs in the U.S. business cycle and to summarize and reveal common turning-point patterns in economic data by smoothing out some of the volatility of individual economic series. The Coincident Economic Index provides information on the current state of the economy. CES employment is a direct input into the index, whereas aggregate weekly earnings for all private industries and aggregate weekly hours of production employees in selected industries are indirect inputs (through personal income and industrial production, respectively).
The Conference Board’s Leading Economic Index is used to predict the direction of the economy’s movements in months to come. The manufacturing workweek from the CES survey, also useful as a short-term predictor of changing economic trends, is a direct input into the index.13
Date | Employment (in thousands) | ETI (2010 = 100) |
---|---|---|
Jan 1974 | 78,104 | 64.42 |
Feb 1974 | 78,254 | 63.47 |
Mar 1974 | 78,296 | 64.27 |
Apr 1974 | 78,382 | 64.51 |
May 1974 | 78,547 | 64.54 |
Jun 1974 | 78,602 | 64.34 |
Jul 1974 | 78,635 | 64.36 |
Aug 1974 | 78,619 | 62.84 |
Sep 1974 | 78,611 | 61.46 |
Oct 1974 | 78,629 | 59.97 |
Nov 1974 | 78,261 | 57.28 |
Dec 1974 | 77,657 | 54.79 |
Jan 1975 | 77,297 | 53.42 |
Feb 1975 | 76,919 | 52.88 |
Mar 1975 | 76,649 | 51.94 |
Apr 1975 | 76,461 | 52.23 |
May 1975 | 76,623 | 52.48 |
Jun 1975 | 76,520 | 53.21 |
Jul 1975 | 76,769 | 54.10 |
Aug 1975 | 77,155 | 54.64 |
Sep 1975 | 77,230 | 55.16 |
Oct 1975 | 77,535 | 55.59 |
Nov 1975 | 77,680 | 55.96 |
Dec 1975 | 78,018 | 56.75 |
Jan 1976 | 78,506 | 57.43 |
Feb 1976 | 78,817 | 58.19 |
Mar 1976 | 79,049 | 58.25 |
Apr 1976 | 79,292 | 58.41 |
May 1976 | 79,311 | 58.43 |
Jun 1976 | 79,376 | 59.07 |
Jul 1976 | 79,547 | 59.12 |
Aug 1976 | 79,704 | 59.23 |
Sep 1976 | 79,892 | 58.91 |
Oct 1976 | 79,905 | 58.24 |
Nov 1976 | 80,237 | 59.20 |
Dec 1976 | 80,448 | 60.35 |
Jan 1977 | 80,692 | 59.88 |
Feb 1977 | 80,988 | 59.96 |
Mar 1977 | 81,391 | 61.76 |
Apr 1977 | 81,729 | 62.13 |
May 1977 | 82,089 | 62.18 |
Jun 1977 | 82,488 | 62.77 |
Jul 1977 | 82,836 | 62.60 |
Aug 1977 | 83,074 | 63.03 |
Sep 1977 | 83,532 | 63.31 |
Oct 1977 | 83,794 | 63.53 |
Nov 1977 | 84,173 | 63.76 |
Dec 1977 | 84,408 | 64.17 |
Jan 1978 | 84,595 | 63.57 |
Feb 1978 | 84,948 | 63.92 |
Mar 1978 | 85,461 | 65.21 |
Apr 1978 | 86,163 | 66.83 |
May 1978 | 86,509 | 67.06 |
Jun 1978 | 86,951 | 67.00 |
Jul 1978 | 87,205 | 66.77 |
Aug 1978 | 87,481 | 67.49 |
Sep 1978 | 87,618 | 67.82 |
Oct 1978 | 87,954 | 68.47 |
Nov 1978 | 88,391 | 68.52 |
Dec 1978 | 88,673 | 69.00 |
Jan 1979 | 88,810 | 67.95 |
Feb 1979 | 89,054 | 67.67 |
Mar 1979 | 89,480 | 68.61 |
Apr 1979 | 89,418 | 66.55 |
May 1979 | 89,791 | 68.36 |
Jun 1979 | 90,109 | 67.30 |
Jul 1979 | 90,215 | 67.10 |
Aug 1979 | 90,297 | 66.78 |
Sep 1979 | 90,325 | 67.27 |
Oct 1979 | 90,482 | 66.87 |
Nov 1979 | 90,576 | 66.22 |
Dec 1979 | 90,673 | 65.88 |
Jan 1980 | 90,802 | 65.97 |
Feb 1980 | 90,882 | 65.36 |
Mar 1980 | 90,994 | 64.13 |
Apr 1980 | 90,850 | 61.04 |
May 1980 | 90,419 | 58.44 |
Jun 1980 | 90,099 | 57.96 |
Jul 1980 | 89,837 | 58.29 |
Aug 1980 | 90,097 | 58.64 |
Sep 1980 | 90,210 | 60.00 |
Oct 1980 | 90,491 | 61.28 |
Nov 1980 | 90,748 | 62.12 |
Dec 1980 | 90,943 | 62.25 |
Jan 1981 | 91,037 | 62.01 |
Feb 1981 | 91,105 | 61.63 |
Mar 1981 | 91,210 | 62.05 |
Apr 1981 | 91,283 | 62.11 |
May 1981 | 91,293 | 61.74 |
Jun 1981 | 91,490 | 61.66 |
Jul 1981 | 91,602 | 61.40 |
Aug 1981 | 91,566 | 61.01 |
Sep 1981 | 91,479 | 59.98 |
Oct 1981 | 91,380 | 58.75 |
Nov 1981 | 91,171 | 58.06 |
Dec 1981 | 90,893 | 56.95 |
Jan 1982 | 90,567 | 56.56 |
Feb 1982 | 90,562 | 56.54 |
Mar 1982 | 90,432 | 55.97 |
Apr 1982 | 90,152 | 54.87 |
May 1982 | 90,107 | 54.66 |
Jun 1982 | 89,864 | 54.14 |
Jul 1982 | 89,522 | 53.72 |
Aug 1982 | 89,364 | 52.96 |
Sep 1982 | 89,183 | 52.45 |
Oct 1982 | 88,906 | 52.12 |
Nov 1982 | 88,783 | 52.41 |
Dec 1982 | 88,769 | 52.60 |
Jan 1983 | 88,993 | 53.90 |
Feb 1983 | 88,918 | 53.79 |
Mar 1983 | 89,090 | 54.86 |
Apr 1983 | 89,366 | 55.51 |
May 1983 | 89,643 | 56.38 |
Jun 1983 | 90,022 | 57.54 |
Jul 1983 | 90,440 | 58.74 |
Aug 1983 | 90,132 | 59.08 |
Sep 1983 | 91,247 | 60.33 |
Oct 1983 | 91,518 | 61.27 |
Nov 1983 | 91,871 | 61.94 |
Dec 1983 | 92,227 | 63.63 |
Jan 1984 | 92,673 | 64.40 |
Feb 1984 | 93,154 | 65.02 |
Mar 1984 | 93,429 | 65.43 |
Apr 1984 | 93,792 | 65.69 |
May 1984 | 94,100 | 66.62 |
Jun 1984 | 94,479 | 66.93 |
Jul 1984 | 94,792 | 67.04 |
Aug 1984 | 95,034 | 67.04 |
Sep 1984 | 95,344 | 66.93 |
Oct 1984 | 95,630 | 66.92 |
Nov 1984 | 95,979 | 67.47 |
Dec 1984 | 96,107 | 67.64 |
Jan 1985 | 96,373 | 68.03 |
Feb 1985 | 96,497 | 68.33 |
Mar 1985 | 96,843 | 68.23 |
Apr 1985 | 97,039 | 68.34 |
May 1985 | 97,313 | 68.40 |
Jun 1985 | 97,459 | 68.55 |
Jul 1985 | 97,649 | 68.94 |
Aug 1985 | 97,842 | 69.10 |
Sep 1985 | 98,045 | 69.26 |
Oct 1985 | 98,233 | 69.34 |
Nov 1985 | 98,442 | 69.90 |
Dec 1985 | 98,609 | 70.32 |
Jan 1986 | 98,734 | 70.96 |
Feb 1986 | 98,841 | 70.72 |
Mar 1986 | 98,935 | 70.73 |
Apr 1986 | 99,122 | 70.98 |
May 1986 | 99,249 | 70.60 |
Jun 1986 | 99,155 | 71.53 |
Jul 1986 | 99,473 | 71.92 |
Aug 1986 | 99,587 | 71.23 |
Sep 1986 | 99,934 | 72.05 |
Oct 1986 | 100,120 | 71.93 |
Nov 1986 | 100,306 | 72.62 |
Dec 1986 | 100,511 | 73.52 |
Jan 1987 | 100,683 | 73.24 |
Feb 1987 | 100,915 | 74.89 |
Mar 1987 | 101,164 | 75.31 |
Apr 1987 | 101,502 | 75.73 |
May 1987 | 101,728 | 76.70 |
Jun 1987 | 101,900 | 76.91 |
Jul 1987 | 102,247 | 77.54 |
Aug 1987 | 102,418 | 78.57 |
Sep 1987 | 102,646 | 78.70 |
Oct 1987 | 103,138 | 79.95 |
Nov 1987 | 103,370 | 79.75 |
Dec 1987 | 103,664 | 80.63 |
Jan 1988 | 103,758 | 80.49 |
Feb 1988 | 104,211 | 81.29 |
Mar 1988 | 104,487 | 81.51 |
Apr 1988 | 104,732 | 82.23 |
May 1988 | 104,961 | 82.59 |
Jun 1988 | 105,324 | 82.75 |
Jul 1988 | 105,546 | 82.51 |
Aug 1988 | 105,670 | 83.41 |
Sep 1988 | 106,009 | 83.68 |
Oct 1988 | 106,277 | 84.30 |
Nov 1988 | 106,616 | 84.50 |
Dec 1988 | 106,906 | 85.25 |
Jan 1989 | 107,168 | 85.77 |
Feb 1989 | 107,426 | 85.33 |
Mar 1989 | 107,619 | 85.33 |
Apr 1989 | 107,792 | 85.57 |
May 1989 | 107,910 | 84.72 |
Jun 1989 | 108,026 | 84.63 |
Jul 1989 | 108,066 | 84.40 |
Aug 1989 | 108,115 | 84.81 |
Sep 1989 | 108,365 | 85.05 |
Oct 1989 | 108,476 | 84.40 |
Nov 1989 | 108,753 | 85.23 |
Dec 1989 | 108,849 | 84.98 |
Jan 1990 | 109,184 | 84.81 |
Feb 1990 | 109,433 | 85.64 |
Mar 1990 | 109,647 | 85.64 |
Apr 1990 | 109,687 | 84.99 |
May 1990 | 109,838 | 85.29 |
Jun 1990 | 109,862 | 84.35 |
Jul 1990 | 109,830 | 84.50 |
Aug 1990 | 109,614 | 83.86 |
Sep 1990 | 109,525 | 83.47 |
Oct 1990 | 109,366 | 81.63 |
Nov 1990 | 109,216 | 80.46 |
Dec 1990 | 109,160 | 79.34 |
Jan 1991 | 109,040 | 79.26 |
Feb 1991 | 108,735 | 78.16 |
Mar 1991 | 108,577 | 77.56 |
Apr 1991 | 108,366 | 77.87 |
May 1991 | 108,241 | 78.20 |
Jun 1991 | 108,338 | 78.68 |
Jul 1991 | 108,298 | 79.03 |
Aug 1991 | 108,308 | 78.69 |
Sep 1991 | 108,340 | 78.91 |
Oct 1991 | 108,357 | 78.45 |
Nov 1991 | 108,299 | 77.36 |
Dec 1991 | 108,325 | 77.32 |
Jan 1992 | 108,377 | 77.74 |
Feb 1992 | 108,314 | 77.99 |
Mar 1992 | 108,368 | 78.76 |
Apr 1992 | 108,527 | 79.70 |
May 1992 | 108,653 | 80.40 |
Jun 1992 | 108,721 | 80.62 |
Jul 1992 | 108,792 | 80.79 |
Aug 1992 | 108,930 | 80.30 |
Sep 1992 | 108,966 | 80.72 |
Oct 1992 | 109,148 | 81.51 |
Nov 1992 | 109,284 | 81.93 |
Dec 1992 | 109,496 | 83.31 |
Jan 1993 | 109,805 | 84.12 |
Feb 1993 | 110,047 | 83.80 |
Mar 1993 | 109,998 | 84.00 |
Apr 1993 | 110,306 | 84.00 |
May 1993 | 110,572 | 84.63 |
Jun 1993 | 110,754 | 85.02 |
Jul 1993 | 111,055 | 84.95 |
Aug 1993 | 111,211 | 85.45 |
Sep 1993 | 111,451 | 86.10 |
Oct 1993 | 111,737 | 86.92 |
Nov 1993 | 112,000 | 87.68 |
Dec 1993 | 112,312 | 88.42 |
Jan 1994 | 112,583 | 90.19 |
Feb 1994 | 112,783 | 91.48 |
Mar 1994 | 113,248 | 92.95 |
Apr 1994 | 113,598 | 93.35 |
May 1994 | 113,931 | 92.90 |
Jun 1994 | 114,246 | 94.00 |
Jul 1994 | 114,619 | 95.06 |
Aug 1994 | 114,901 | 96.42 |
Sep 1994 | 115,254 | 96.57 |
Oct 1994 | 115,467 | 96.84 |
Nov 1994 | 115,887 | 97.71 |
Dec 1994 | 116,164 | 98.81 |
Jan 1995 | 116,488 | 99.03 |
Feb 1995 | 116,692 | 99.25 |
Mar 1995 | 116,913 | 98.82 |
Apr 1995 | 117,075 | 98.51 |
May 1995 | 117,060 | 98.37 |
Jun 1995 | 117,294 | 98.45 |
Jul 1995 | 117,390 | 98.47 |
Aug 1995 | 117,643 | 99.39 |
Sep 1995 | 117,887 | 99.53 |
Oct 1995 | 118,040 | 99.32 |
Nov 1995 | 118,189 | 99.29 |
Dec 1995 | 118,322 | 100.14 |
Jan 1996 | 118,303 | 99.46 |
Feb 1996 | 118,735 | 100.67 |
Mar 1996 | 119,002 | 99.78 |
Apr 1996 | 119,165 | 101.81 |
May 1996 | 119,487 | 102.57 |
Jun 1996 | 119,774 | 103.06 |
Jul 1996 | 120,023 | 103.38 |
Aug 1996 | 120,202 | 104.49 |
Sep 1996 | 120,427 | 104.45 |
Oct 1996 | 120,677 | 104.27 |
Nov 1996 | 120,976 | 105.85 |
Dec 1996 | 121,147 | 105.14 |
Jan 1997 | 121,381 | 107.42 |
Feb 1997 | 121,684 | 108.76 |
Mar 1997 | 122,000 | 109.33 |
Apr 1997 | 122,292 | 109.09 |
May 1997 | 122,552 | 110.53 |
Jun 1997 | 122,818 | 111.49 |
Jul 1997 | 123,124 | 112.61 |
Aug 1997 | 123,093 | 112.19 |
Sep 1997 | 123,605 | 113.48 |
Oct 1997 | 123,945 | 113.42 |
Nov 1997 | 124,251 | 114.66 |
Dec 1997 | 124,554 | 115.68 |
Jan 1998 | 124,830 | 115.52 |
Feb 1998 | 125,026 | 117.04 |
Mar 1998 | 125,177 | 117.34 |
Apr 1998 | 125,457 | 117.64 |
May 1998 | 125,861 | 118.27 |
Jun 1998 | 126,080 | 118.20 |
Jul 1998 | 126,209 | 117.53 |
Aug 1998 | 126,551 | 119.57 |
Sep 1998 | 126,774 | 119.65 |
Oct 1998 | 126,973 | 120.57 |
Nov 1998 | 127,255 | 120.98 |
Dec 1998 | 127,601 | 121.52 |
Jan 1999 | 127,727 | 122.06 |
Feb 1999 | 128,137 | 124.19 |
Mar 1999 | 128,244 | 124.03 |
Apr 1999 | 128,620 | 124.37 |
May 1999 | 128,831 | 124.90 |
Jun 1999 | 129,091 | 125.71 |
Jul 1999 | 129,417 | 126.37 |
Aug 1999 | 129,577 | 126.51 |
Sep 1999 | 129,791 | 126.13 |
Oct 1999 | 130,191 | 128.32 |
Nov 1999 | 130,484 | 129.10 |
Dec 1999 | 130,780 | 129.96 |
Jan 2000 | 131,010 | 130.61 |
Feb 2000 | 131,140 | 130.18 |
Mar 2000 | 131,608 | 131.73 |
Apr 2000 | 131,895 | 131.88 |
May 2000 | 132,122 | 131.46 |
Jun 2000 | 132,075 | 131.49 |
Jul 2000 | 132,251 | 131.91 |
Aug 2000 | 132,241 | 130.22 |
Sep 2000 | 132,377 | 131.16 |
Oct 2000 | 132,363 | 130.02 |
Nov 2000 | 132,589 | 129.07 |
Dec 2000 | 132,731 | 128.11 |
Jan 2001 | 132,705 | 127.23 |
Feb 2001 | 132,777 | 125.99 |
Mar 2001 | 132,752 | 123.90 |
Apr 2001 | 132,471 | 121.91 |
May 2001 | 132,433 | 120.93 |
Jun 2001 | 132,302 | 119.07 |
Jul 2001 | 132,190 | 119.13 |
Aug 2001 | 132,033 | 118.99 |
Sep 2001 | 131,793 | 113.99 |
Oct 2001 | 131,468 | 112.09 |
Nov 2001 | 131,175 | 110.69 |
Dec 2001 | 131,005 | 111.60 |
Jan 2002 | 130,867 | 111.75 |
Feb 2002 | 130,733 | 111.81 |
Mar 2002 | 130,713 | 112.69 |
Apr 2002 | 130,634 | 112.68 |
May 2002 | 130,627 | 113.53 |
Jun 2002 | 130,684 | 114.08 |
Jul 2002 | 130,599 | 113.52 |
Aug 2002 | 130,585 | 113.53 |
Sep 2002 | 130,526 | 111.72 |
Oct 2002 | 130,652 | 111.82 |
Nov 2002 | 130,662 | 112.70 |
Dec 2002 | 130,505 | 110.09 |
Jan 2003 | 130,597 | 112.14 |
Feb 2003 | 130,447 | 110.64 |
Mar 2003 | 130,238 | 109.88 |
Apr 2003 | 130,194 | 109.21 |
May 2003 | 130,186 | 109.67 |
Jun 2003 | 130,195 | 110.79 |
Jul 2003 | 130,219 | 111.05 |
Aug 2003 | 130,177 | 112.15 |
Sep 2003 | 130,281 | 111.20 |
Oct 2003 | 130,479 | 111.88 |
Nov 2003 | 130,496 | 113.23 |
Dec 2003 | 130,618 | 113.44 |
Jan 2004 | 130,780 | 113.53 |
Feb 2004 | 130,826 | 114.56 |
Mar 2004 | 131,158 | 115.29 |
Apr 2004 | 131,407 | 115.80 |
May 2004 | 131,715 | 116.68 |
Jun 2004 | 131,791 | 116.39 |
Jul 2004 | 131,835 | 118.10 |
Aug 2004 | 131,956 | 117.91 |
Sep 2004 | 132,120 | 117.60 |
Oct 2004 | 132,466 | 118.69 |
Nov 2004 | 132,530 | 118.33 |
Dec 2004 | 132,660 | 120.24 |
Jan 2005 | 132,794 | 120.06 |
Feb 2005 | 133,033 | 122.54 |
Mar 2005 | 133,169 | 121.47 |
Apr 2005 | 133,534 | 122.88 |
May 2005 | 133,708 | 121.95 |
Jun 2005 | 133,955 | 122.42 |
Jul 2005 | 134,331 | 122.77 |
Aug 2005 | 134,525 | 123.51 |
Sep 2005 | 134,593 | 120.74 |
Oct 2005 | 134,678 | 122.46 |
Nov 2005 | 135,015 | 124.79 |
Dec 2005 | 135,174 | 125.22 |
Jan 2006 | 135,452 | 126.72 |
Feb 2006 | 135,768 | 126.79 |
Mar 2006 | 136,049 | 126.98 |
Apr 2006 | 136,232 | 128.01 |
May 2006 | 136,255 | 126.73 |
Jun 2006 | 136,337 | 126.59 |
Jul 2006 | 136,544 | 125.86 |
Aug 2006 | 136,725 | 126.75 |
Sep 2006 | 136,883 | 126.69 |
Oct 2006 | 136,887 | 126.17 |
Nov 2006 | 137,095 | 125.80 |
Dec 2006 | 137,266 | 126.47 |
Jan 2007 | 137,506 | 127.51 |
Feb 2007 | 137,596 | 128.33 |
Mar 2007 | 137,785 | 128.70 |
Apr 2007 | 137,864 | 127.78 |
May 2007 | 138,007 | 127.68 |
Jun 2007 | 138,085 | 127.80 |
Jul 2007 | 138,052 | 127.25 |
Aug 2007 | 138,028 | 127.16 |
Sep 2007 | 138,116 | 126.60 |
Oct 2007 | 138,201 | 125.66 |
Nov 2007 | 138,316 | 125.18 |
Dec 2007 | 138,413 | 124.53 |
Jan 2008 | 138,432 | 125.00 |
Feb 2008 | 138,346 | 122.42 |
Mar 2008 | 138,268 | 120.80 |
Apr 2008 | 138,058 | 119.90 |
May 2008 | 137,873 | 118.22 |
Jun 2008 | 137,708 | 117.68 |
Jul 2008 | 137,499 | 115.12 |
Aug 2008 | 137,233 | 113.17 |
Sep 2008 | 136,781 | 109.69 |
Oct 2008 | 136,308 | 107.19 |
Nov 2008 | 135,539 | 103.54 |
Dec 2008 | 134,844 | 100.39 |
Jan 2009 | 134,053 | 97.10 |
Feb 2009 | 133,350 | 95.17 |
Mar 2009 | 132,527 | 92.51 |
Apr 2009 | 131,841 | 91.52 |
May 2009 | 131,490 | 91.24 |
Jun 2009 | 131,020 | 91.32 |
Jul 2009 | 130,691 | 91.22 |
Aug 2009 | 130,479 | 91.69 |
Sep 2009 | 130,260 | 92.37 |
Oct 2009 | 130,060 | 92.59 |
Nov 2009 | 130,053 | 93.62 |
Dec 2009 | 129,774 | 95.20 |
Jan 2010 | 129,802 | 96.67 |
Feb 2010 | 129,733 | 96.75 |
Mar 2010 | 129,896 | 97.30 |
Apr 2010 | 130,139 | 99.28 |
May 2010 | 130,661 | 99.51 |
Jun 2010 | 130,528 | 99.94 |
Jul 2010 | 130,458 | 100.78 |
Aug 2010 | 130,424 | 101.14 |
Sep 2010 | 130,372 | 101.15 |
Oct 2010 | 130,629 | 101.77 |
Nov 2010 | 130,752 | 101.97 |
Dec 2010 | 130,840 | 103.74 |
Jan 2011 | 130,882 | 103.88 |
Feb 2011 | 131,070 | 104.75 |
Mar 2011 | 131,295 | 105.76 |
Apr 2011 | 131,641 | 104.98 |
May 2011 | 131,714 | 104.44 |
Jun 2011 | 131,949 | 105.75 |
Jul 2011 | 132,019 | 105.64 |
Aug 2011 | 132,126 | 105.95 |
Sep 2011 | 132,372 | 106.15 |
Oct 2011 | 132,574 | 107.34 |
Nov 2011 | 132,720 | 107.98 |
Dec 2011 | 132,927 | 109.24 |
Jan 2012 | 133,265 | 110.39 |
Feb 2012 | 133,522 | 111.22 |
Mar 2012 | 133,761 | 110.98 |
Apr 2012 | 133,836 | 111.51 |
May 2012 | 133,951 | 112.16 |
Jun 2012 | 134,038 | 111.25 |
Jul 2012 | 134,181 | 111.45 |
Aug 2012 | 134,371 | 111.97 |
Sep 2012 | 134,552 | 111.07 |
Oct 2012 | 134,684 | 111.87 |
Nov 2012 | 134,833 | 112.35 |
Dec 2012 | 135,076 | 113.27 |
Jan 2013 | 135,266 | 113.68 |
Feb 2013 | 135,577 | 114.93 |
Mar 2013 | 135,712 | 114.65 |
Apr 2013 | 135,904 | 114.52 |
May 2013 | 136,122 | 115.09 |
Jun 2013 | 136,268 | 114.95 |
Jul 2013 | 136,408 | 115.23 |
Aug 2013 | 136,677 | 116.35 |
Sep 2013 | 136,862 | 116.97 |
Oct 2013 | 137,051 | 116.45 |
Nov 2013 | 137,342 | 117.97 |
Dec 2013 | 137,387 | 117.73 |
Jan 2014 | 137,574 | 117.94 |
Feb 2014 | 137,742 | 118.80 |
Mar 2014 | 138,014 | 119.83 |
Apr 2014 | 138,324 | 120.06 |
May 2014 | 138,537 | 121.22 |
Jun 2014 | 138,843 | 121.99 |
Jul 2014 | 139,075 | 122.54 |
Aug 2014 | 139,293 | 123.35 |
Sep 2014 | 139,579 | 123.12 |
Oct 2014 | 139,779 | 124.40 |
Nov 2014 | 140,110 | 125.14 |
Dec 2014 | 140,402 | 125.98 |
Jan 2015 | 140,623 | 126.49 |
Feb 2015 | 140,888 | 126.42 |
Mar 2015 | 140,972 | 126.18 |
Apr 2015 | 141,223 | 127.33 |
May 2015 | 141,496 | 127.03 |
Jun 2015 | 141,724 | 127.09 |
Jul 2015 | 142,001 | 127.76 |
Aug 2015 | 142,151 | 128.72 |
Sep 2015 | 142,300 | 129.07 |
Oct 2015 | 142,595 | 129.46 |
Nov 2015 | 142,875 | 128.31 |
Dec 2015 | 143,137 | 128.71 |
Sources: U.S. Bureau of Labor Statistics and The Conference Board. |
Changes in employment trends of the temporary help services industry typically lead employment changes for the overall U.S. economy. Therefore, The Conference Board uses temporary help employment from the CES survey as an input in calculating the Employment Trend Index. This index aggregates eight separate economic indicators and offers a short-term, forward look at potential changes in employment trends.14 (See figure 1.)
CES data used in other BLS programs. CES data are used as inputs to other BLS data, in programs such as the Local Area Unemployment Statistics (LAUS) program, which produces statistics on the labor force by state and metropolitan area. LAUS uses CES state and area employment estimates as primary inputs to its employment estimates for states and metropolitan areas. LAUS data are based on place of residence, whereas CES estimates are based on location of work. Therefore, LAUS adjusts its estimates with U.S. Census Bureau data, to “residency-adjust” the CES employment inputs.
The National Compensation Survey program, another user of CES data, produces statistics on employer cost levels (Employer Costs of Employee Compensation (ECEC) estimates), changes in employer labor costs (Employment Cost Index), and employee healthcare and retirement benefits. ECEC estimates are weighted by current employment derived from CES employment estimates and from the Quarterly Census of Employment and Wages program.
The Job Openings and Labor Turnover Survey (JOLTS) uses CES employment as a monthly benchmark. A gauge of labor shortages and churn, data collected by JOLTS include estimates of job openings, hires, and separations. JOLTS weighted employment is ratio adjusted to match CES employment each month, and the resulting ratio is then applied to these estimates. JOLTS also aligns estimates of hires and separations to closely track CES over-the-month employment changes.
The Office of Productivity and Technology produces measures of labor productivity (output per hour), unit labor costs, and multifactor productivity (output per unit of combined inputs) for major U.S. economic sectors and industries. The labor hours measure underlying the productivity series is based primarily on CES employment and average weekly hours data, supplemented with CPS hours data (adjusted to an hours-worked concept) for self-employed and unpaid family workers. Productivity and related cost measures may be used to analyze and forecast changes in prices, wages, production, and technology.
BLS also produces employment projections for 10 years into the future. CES estimates of employment by industry, supplemented with data from the CPS survey, serve as the base-year employment from which projections are made. Employment projections are widely used by policymakers and other officials to make decisions about education and training policy, funding, and program offerings. In addition, federal agencies, researchers, and academia use employment projections to understand potential future trends in the economy and the labor market.15
Uses of CES data in formulating monetary and fiscal policy. Policymakers closely follow CES data for their depth of coverage—geographic and industry detail—and for their timely release each month. The Federal Reserve uses CES data to gauge economic conditions in the U.S. labor market when formulating monetary policy. Federal, state, and local government officials use CES employment and aggregate earnings data to forecast tax revenues and plan budgets. Thus, CES data are useful in determining both monetary and fiscal policy.
Other uses of CES data. Each year, CES data are used by a broad spectrum of researchers, including BLS economists, to analyze the economy, labor markets, and industries. For example, Lawrence Mishel and colleagues used various CES statistics in analyzing the economic experience of workers and their families in the United States.16
CES data also are used in the private sector by firms, labor unions, universities, trade associations, and research organizations to study economic conditions and to develop plans for the future. Firms, for example, may use CES employment, hours, and earnings data for planning business activity. A manufacturer could choose to set up factories in an area with a strong manufacturing sector and a skilled workforce. Likewise, a retail chain may decide to open an upscale store or an economy store on the basis of average earnings in an area. Businesses use CES data for forecasting and economic analysis of the labor market and the overall U.S. economy. Every month, national and local news media report results from the CES news releases. Also, trade association journals, the labor press, and general reference works regularly republish CES data in summary form or for specific industries or areas.
The CES program produces employment, hours, and earnings estimates for approximately 900 industries for the nation, states, and areas. National CES estimates represent some of the earliest economic indicators of the U.S. economy. CES data, important not only on their own, serve as inputs into other key economic indicators. The data also provide an important source of information for businesses, major news media, researchers, and students.
Richa Ajmera, and Angie Clinton, "Current Employment Statistics data and their contributions as key economic indicators," Monthly Labor Review, U.S. Bureau of Labor Statistics, March 2016, https://doi.org/10.21916/mlr.2016.11
1 “Amount of employment in certain industries in October and November, 1915,” Monthly Review, vol. II, no. 1, January 1916, pp. 11–12.
2 See “Current Employment Statistics—CES (national)” (U.S. Bureau of Labor Statistics), https://www.bls.gov/ces/.
3 Production employees are defined differently depending on the industry. Production and nonsupervisory employees include production employees in mining and logging and manufacturing, construction employees in construction, and nonsupervisory employees in private service-providing industries.
4 For more information on the North American Industry Classification System, see “Introduction to NAICS” (U.S. Census Bureau), https://www.census.gov/eos/www/naics/.
5 For example, a recent article on bilateral trade directly compares CES estimates of U.S. industry employment with similar estimates for Mexico and Canada; see Christopher E. Wilson, “Working together: economic ties between the United States and Mexico” (Washington, DC: Mexico Institute, Woodrow Wilson International Center for Scholars, November 2011), https://www.wilsoncenter.org/sites/default/files/Working%20Together%20Full%20Document.pdf.
6 See “Revisions,” in Technical notes for the Current Employment Statistics survey (U.S. Bureau of Labor Statistics, February 5, 2016), https://www.bls.gov/web/empsit/cestn.pdf.
7 Unemployment insurance tax records are collected, reviewed, and edited through the BLS Quarterly Census of Employment and Wages program, https://www.bls.gov/cew/.
8 For more information on the benchmark process, see the latest CES national benchmark article at https://www.bls.gov/web/empsit/cesbmart.pdf.
9 “The NBER’s business cycle dating procedure: frequently asked questions” (Cambridge, MA: National Bureau of Economic Research), http://www.nber.org/cycles/recessions_faq.html.
10 “Industrial production and capacity utilization—G.17” (Board of Governors of the Federal Reserve System), http://www.federalreserve.gov/releases/g17/About.htm.
11 “Industrial Production Index—IPI,” Investopedia, http://www.investopedia.com/terms/i/ipi.asp.
12 The latest news release for personal income from the Bureau of Economic Analysis is available at https://www.bea.gov/newsreleases/national/pi/pinewsrelease.htm.
13 “Global business cycle indicators” (The Conference Board), https://www.conference-board.org/data/bcicountry.cfm?cid=1.
14 “The Conference Board Employment Trend Index (ETI)” (The Conference Board), https://www.conference-board.org/data/eti.cfm.
15 See “Employment projections” (U.S. Bureau of Labor Statistics), https://www.bls.gov/emp/.
16 Lawrence Mishel, Josh Bivens, Elise Gould, and Heidi Shierholz, The state of working America, 12th ed. (Ithaca, NY: Cornell University Press, 2012).