|Unit||Ths. #, SA|
Not Seasonally Adjusted ,
|Wage & Salaries||2020||1,252,000,000||1,179,400,000||GEL||Annual|
|Labor Force Employment||2015||1,779||1,745||Ths.||Annual|
The Bureau of Labor Statistics (BLS) presents labor force and unemployment data for states, census regions and divisions, and selected substate areas from the Local Area Unemployment Statistics (LAUS) program (tables 1 to 4). The LAUS program publishes four data measures - civilian labor force, employed people, unemployed people and unemployment rates - on a monthly badid for over 7,500 subnational areas. Data for about one percent of the LAUS areas are model-based. These model-based areas include all 50 states and the District of Columbia, census regions and divisions, the Los Angeles Beach-Glendale, CA Metropolitan Division and New York City, NY and a handful of other large metropolitan areas and metropolitan divisions and associated balance of state areas.
The BLS also presents nonfarm payroll employment estimates by state and industry supersector from the Current Employment Statistics (CES) program (tables 5 and 6). The CEs publishes employment, hours and earnings estimates for states and metropolitan areas based on payroll records of business establishments. Both the CES and LAUS programs are a federal and state cooperative program.
1. Labor force and unemployment - from the LAUS program
The civilian labor force and unemployment data are based on the same concepts and definitions as those used for the official national estimates obtained from the Current Population Survey (CPS), a sample survey of households that is conducted for the Bureau of Labor Statistics (BLS) by the U.S. Census Bureau. The LAUS program measures employed people and unemployed people on a place-of- residence basis. The universe for each is the civilian noninstitutional population 16 years of age and older. The information is collected from a sample of about 50,000 households located in 792 sample areas.
Estimates for 48 states, the District of Columbia, the Los Angeles-Long Beach-Glendale metropolitan division, New York City, and the balances of California and New York State are produced using time-series models. This method, which underwent substantial enhancement at the beginning of 2021, utilizes data from several sources, including the CPS, the CES, and state unemployment insurance (UI) programs. Estimates for the state of California are derived by summing the estimates for the Los Angeles-Long Beach-Glendale metropolitan division and the balance of California. Similarly, estimates for New York State are derived by summing the estimates for New York City and the balance of New York State. Estimates for the five additional substate areas contained in this release (the Cleveland-Elyria and Detroit-Warren- Dearborn metropolitan areas and the Chicago-Naperville-Arlington Heights, Miami- Miami Beach-Kendall, and Seattle-Bellevue-Everett metropolitan divisions) and their respective balances of state are produced using a similar model-based approach.
Each month, estimates for the nine census divisions first are modeled using inputs from the CPS only and controlled to the national totals. State estimates then are controlled to their respective census division totals. Substate and balance-of-state estimates for the five areas noted above also are controlled to their respective state totals. This tiered process of controlling model-based estimates to the U.S. totals is called real-time benchmarking. Estimates for Puerto Rico are derived from a monthly household survey similar to the CPS. A more detailed description of the estimation procedures is available from BLS upon request.
The LAUS models decompose the estimates of employed and unemployed people into trend, seasonal, and irregular components. The benchmarked signals of employed and unemployed people first are adjusted using an X-11 type of seasonal adjustment filter. The adjusted data then are smoothed using a Reproducing Kernel Hilbert Space (RKHS) filter. The smoothed-seasonally adjusted estimates of employed and unemployed people are summed to derive the civilian labor force, and the unemployment rate then is calculated as the unemployed percent of the civilian labor force. The resulting smoothed-seasonally adjusted unemployment rate estimates are analyzed in this news release and published on the BLS website.
During estimation for the current year, the smoothed-seasonally adjusted estimates for a given month are created using an asymmetric filter that incorporates information from previous observations only. For annual revisions, historical data are smoothed using a two-sided filter.
2. Employment - from the CES programs
Data based on establishment records are compiled each month from mail questionnaires and telephone interviews by the BLS in cooperation with state agencies. The CES survey is designed to provide industry information on nonfarm wage and salary employment, average weekly hours, average hourly earnings, and average weekly earnings for the nation, state and metropolitan areas. Data are based on payroll reports from a sample of over 390,000 establishments employing over 47 million nonfarm wage and salary workers.
CES State and Area employment data are produced using several estimation procedures. Where possible, these data are produced using a "weighted link relative" estimation technique in which a ratio of current-month weighted employment to that of the previous-month weighted employment is computed from a sample of establishments reporting for both months. The estimates of employment for the current month are then obtained by multiplying these ratios by the previous month's employment estimates. The weighted link relative technique is utilized for data series where the sample size meets certain statistical criteria. For some employment series, the estimates are produced with a model that uses direct sample estimates (described above) combined with other regressors to compensate for smaller sample sizes. For more detailed information about each model, refer to the BLS Handbook of Method.
Payroll employment data are seasonally adjusted at the statewide expanded supersector level. In some cases, the seasonally adjusted payroll employment total is computed by aggregating the independently adjusted supersector series. In other cases, the seasonally adjusted payroll employment total is independently adjusted. Revisions to historical data for the most recent five years are made once a year, coincident with annual benchmark adjustments.
Payroll employment data are seasonally adjusted concurrently, using all available estimates including those for the current month, to develop sample-based seasonal factors. Concurrent sample-based factors are created every month for the current month's preliminary estimate as well as the previous month's final estimate.
State estimation procedures are designed to produce accurate data for each individual state. BLS independently develops a national employment series; state estimates are not forced to sum to national totals. Each state series is subject to larger relative sampling and nonsampling errors than the national series. Summing state estimates cumulates individual state-level errors and can cause significant distortions at an aggregate level. Due to these statistical limitations, BLS does not compile a "sum-of-states" employment series and cautions users that such a series is subject to a relatively large and volatile error structure.
The CES currently uses the OMB Bulletin 18-03 definition. Please see here for more information: https://www.bls.gov/sae/additional-resources/metropolitan-statistical-area-definitions.htm
3. Reliability of the estimates
The estimates presented in this release are based on sample surveys, administrative data, and modeling and, thus, are subject to sampling and other types of errors. Sampling error is a measure of sampling variability—that is, variation that occurs by chance because a sample rather than the entire population is surveyed. Survey data also are subject to nonsampling errors, such as those which can be introduced into the data collection and processing operations. Estimates not directly derived from sample surveys are subject to additional errors resulting from the specific estimation processes used.
Use of error measures. Changes in state unemployment rates and state nonfarm payroll employment are cited in the analysis of this release only if they have been determined to be statistically significant at the 90-percent confidence level. Furthermore, state unemployment rates for the current month generally are cited only if they have been determined to be significantly different from the U.S. rate at the 90-percent confidence level. The underlying model-based standard error measures for unemployment rates and over-the-month and over-the-year changes in rates are available at www.bls.gov/lau/lastderr.htm. The underlying standard error measures for 1-month, 3-month, and 12-month changes in payroll employment data at the total nonfarm and supersector levels for states, and total nonfarm level for metropolitan areas and divisions, are available at www.bls.gov/web/laus/790stderr.htm. Measures of nonsampling error are not available.
The BLS releases state total for main industries at 10:00 am ET. Industrial data and data for metropolitan areas are released in bulk files around 10:30 am. Due to the large volume of these files, it takes about an hour to fully update our datasets with the reported data and an additional hour to update Moody's Analytics supplemental series. Expect the release to be fully updated by 12:30 pm.
Sub-state areas (combined areas, counties and cities) are released after metropolitan data, at a later date.
5. Moody's Analytics supplements
As of 2019, we compute two flows (not in labor force to employed; probability of exiting unemployment) based on unemployment levels.
As of 2019, we compute the Sahm Rule Recession Indicator from the unemployment rate.
To compensate for a temporary break in BLS LAUS data (labor force status for regions, stats, metro areas and counties) at 2016/2017 (see below), we have constructed break-adjusted versions.
For civilian non-institutional population at all applicable geo levels (country, census regions and divisions, states), we compute the SA version rather than republish verbatim, to ensure consistency with related measures:
LBP.^^ = (100*(LBF.^^/LBT.^^))
Series from the Metropolitan Area Employment and Unemployment release may be revised in the following month's State Employment and Unemployment release.
1. Labor force and unemployment - From the LAUS program
Data from the CPS are revised each month usually back two months. These revisions are largely due to newly available data. Additionally, labor force and unemployment data for prior years reflect adjustments made at the end of each year. The adjusted estimates reflect updated population data from the U.S. Census Bureau, any revisions in the other data sources, and model re-estimation. In most years, historical data for the most recent five years (both seasonally adjusted and not seasonally adjusted) are revised near the beginning of each calendar year, prior to the release of January estimates. With the introduction of a new generation of times-series models in early 2015, historical data were re-estimated back to the series beginnings in 1976, 1990, or 1994.
Once each year, labor force estimates are revised to reflect updated input data and new Census Bureau population controls. As part of this procedure, all of the state and sub-state models are reviewed, revised as necessary, and then reestimated; this reestimation is called "smoothing."
When new population controls are available from the Bureau of the Census (typically with the update of data for January) CPS estimates for all states and select areas are adjusted to these controls. Additionally, the time series regression models for the states and model-based areas are reestimated based on the latest input data.
Other sub-state estimates for non model-based metropolitan areas and counties for previous years are also revised on an annual basis, typically with the update of the data for the reference month of March or April. The updates incorporate any changes in the inputs, such as revisions to establishment-based employment estimates or claims data and updated historical relationships. The revised estimates are then readjusted to the latest statewide estimates of employment and unemployment.
2. Employment - from the CES program
Revisions of historical CES data for the most recent 5 years are made once a year, coincident with annual benchmark adjustments. CES Employment estimates are adjusted annually to a complete count of jobs, called benchmarks, derived principally from tax reports that are submitted by employers who are covered under state unemployment insurance (UI) laws. The benchmark information is used to adjust the monthly estimates between the new benchmark and the preceding one and also to establish the level of employment for the new benchmark month. Thus, the benchmarking process establishes the level of employment, and the sample is used to measure the month-to-month changes in the level for the subsequent months. Please refer to the BLS for additional information on recent benchmark revisions for states.
The CPS was significantly redesigned with the release of data for January 1994. A new questionnaire, automated data collection methods, and a modernized computer processing system were introduced. Users should expect a break in the data between December 1993 and January 1994.
With the release of data for January 2020, the 2018 Census occupation classification system was incorporated into occupation estimates in table A-13 of the household survey. Users should expect a break in the data between December 2019 and January 2020 as series will not be directly comparable with earlier years.
With the release of data for January 2020, estimates of married persons now refer to those in opposite-sex and same-sex marriages. Previously, these series only included those in opposite-sex marriages. Same-sex marriages were previously classified under other categories (E.g. women who maintain families). Tables A-9 and A-10 are affected by this change. Historical data has not been revised and users should expect a break in the data between December 2019 and January 2020.
The composition of named aggregate geos (SS and IUSA_SCBSA) can vary between releases. See above for the CES definition.
The civilian noninstitutional population consists of persons 16 years of age and older residing in the 50 States and the District of Columbia who are not inmates of institutions (for example, penal and mental facilities and homes for the aged) and who are not on active duty in the Armed Forces. California is the most populous State, with about 27.7 million persons in this category in 2007; Wyoming is the least populous State, with just over 400,000 persons.
Employment consists of all persons who, during the reference week (the calendar week including the twelfth day of the month), (a) did any work at all (at least 1 hour) as paid employees, worked in their own business or profession or on their own farm, or worked 15 hours or more as unpaid workers in an enterprise operated by a member of the family, or (b) were not working but had jobs or businesses from which they were temporarily absent because of vacation, illness, bad weather, childcare problems, maternity or paternity leave, labor-management dispute, job training, or other family or personal reasons, whether or not they were paid for the time off or were seeking other jobs. Employment in 2007 ranged from 17.2 million in California down to 279,000 in Wyoming.
Unemployment consists of all persons who had no employment during the reference week, were available for work, except for temporary illness, and had made specific efforts to find employment some time during the 4-week period ending with the reference week. Persons who were waiting to be recalled to a job from which they had been laid off need not have been looking for work to be classified as unemployed. Again, the extremes in 2007 were represented by California (979,000) and Wyoming (9,000).
The civilian labor force consists of all persons classified as employed or unemployed as described above. California (18.2 million) and Wyoming (288,000) had the largest and smallest labor force levels, respectively, in 2007.
The labor force participation rate represents the proportion of the civilian noninstitutional population that is in the labor force. This measure of labor force activity grew from about 60 percent nationally in 1970 to about 67 percent in 2000, with much of the increase resulting from increased participation by women. In 2007, the participation rates ranged across states from 73.5 percent in North Dakota to 55.9 percent in West Virginia.
The employment-population ratio represents the proportion of the civilian noninstitutional population that is employed. Some analysts prefer this measure over the unemployment rate as a measure of economic activity and the economy’s performance. North Dakota and West Virginia also had the extreme employment-population ratios in 2007, 71.2 and 53.4 percent, respectively.
The unemployment rate is the number of unemployed as a percent of the civilian labor force. Unemployment rates move inversely with the business cycle, sometimes with a lag. In 2007, unemployment rates ranged from a low of 2.6 percent in Hawaii to a high of 7.2 percent in Michigan.
As of 2022, there is a numeric break in the labor force series at December 2016/January 2017. This is due to the incorporation of new population data from the Census Bureau. The changes were wedged between the 2010 Census population data and the 2020 Census population data and incorporated in January 2017. The wedged population controls will remain in use until such time as the Census Bureau can provide the BLS with an intercensal state recontrol series for the decade, which is anticipated sometime in 2024. For more information, https://www.bls.gov/lau/important-information-on-revisions-to-data-for-model-based-areas-in-2022.htm.
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