Region, state, and area labor force data
FEDERAL-STATE COOPERATIVE PROGRAM
Labor force and unemployment estimates for States, labor market areas (LMAs), and other areas covered under Federal assistance programs are developed by State employment security agencies under a Federal-State cooperative program. The local unemployment estimates, which derive from standardized procedures developed by BLS, are the basis for determining eligibility of an area for benefits under Federal programs such as the Workforce Investment Act.
Annual average data for the States and 337 areas shown in table C-3 are published in Employment and Earnings (usually the May issue). For regions, States, selected metropolitan areas, and central cities, annual average data classified by selected demographic, social, and economic characteristics are published in the BLS bulletin, Geographic Profile of Employment and Unemployment.
Labor force estimates for counties, cities, and other small areas have been prepared for administration of various Federal economic assistance programs and are available on the Internet at http://www.bls.gov/lau or by subscription by calling 202-691-6392.
Monthly labor force, employment, and unemployment estimates are prepared for the 50 States, the District of Columbia, Puerto Rico, and over 7,000 areas, including nearly 2,400 LMAs, all counties, and cities with a population of 25,000 or more. Regional aggregations are derived by summing the State estimates. The estimation methods are described below for States (and the District of Columbia) and for sub-state areas. At the sub-LMA (county and city) level, estimates are prepared using disaggregation techniques based on decennial and annual population estimates and current unemployment insurance data. A more detailed description of the estimation procedure is contained in the BLS document, Manual for Developing Local Area Unemployment Statistics.
Estimates for States
Current monthly estimates. Effective January 1996, civilian labor force and unemployment estimates for all States and the District of Columbia are produced using models based on a “signal-plus-noise” approach. The model of the signal is a time series model of the true labor force which consists of three components: A variable coefficient regression, a flexible trend, and a flexible seasonal component. The regression techniques are based on historical and current relationships found within each State’s economy as reflected in the different sources of data that are available for each State–the Current Population Survey (CPS), the Current Employment Statistics (CES) survey, and the unemployment insurance (UI) system. The noise component of the models explicitly accounts for auto correlation in the CPS sampling error and changes in the average magnitude of the error. In addition, the models can identify and remove the effects of outliers in the historical CPS series. While all the State models have important components in common, they differ somewhat from one another to better reflect individual State characteristics.
Two models–one for the employment-to-population ratio and one for the unemployment rate–are used for each State. The employment-to-population ratio, rather than the employment level, and the unemployment rate, rather than the unemployment level, are estimated primarily because these ratios are usually more meaningful for economic analysis.
The employment-to-population ratio models use the relationship between the State’s monthly employment from the CES and the CPS. The models also include trend and seasonal components to account for movements in the CPS not captured by the CES series. The seasonal component accounts for the seasonality in the CPS not explained by the CES, while the trend component adjusts for long-run systematic differences between the two series.
The unemployment rate models use the relationship between the State’s monthly unemployment insurance (UI) claims data and the CPS unemployment rate, along with trend and seasonal components.
In both the employment-to-population ratio and unemployment rate models, an important feature is the use of a technique that allows the equations to adjust automatically to structural changes that occur. The regression portion of the model includes a built-in tuning mechanism, known as the Kalman Filter, which revises a model’s coefficients when the new data that become available each month indicate that changes in the data relationships have taken place. Once the estimates are developed from the models, levels are calculated for employment, unemployment, and labor force.
Benchmark correction procedures. Once each year, monthly estimates for all States and the District of Columbia are adjusted, or benchmarked, by BLS to the annual average CPS estimates. The benchmarking technique employs a procedure (called the Denton method) which adjusts the annual average of the models to equal the CPS annual average, while preserving, as much as possible, the original monthly seasonal pattern of the model estimates.
Estimates for substate areas
Monthly labor force, employment, and unemployment estimates for two large substate areas–New York City and the Los Angeles-Long Beach metropolitan area–are obtained using the same modeling approach as for states. Estimates for the nearly 2,400 remaining LMAs, are prepared through indirect estimation techniques, described below.
Preliminary estimate–employment. The total civilian employment estimates are based largely on CES data. These “place-of-work” estimates must be adjusted to refer to place of residence as used in the CPS. Factors for adjusting from place of work to place of residence have been developed on the basis of employment relationships at the time of the 1990 decennial census. These factors are applied to the CES estimates for the current period to obtain adjusted employment estimates, to which are added estimates for employment not represented in the CES–agricultural employees, nonagricultural self-employed and unpaid family workers, and private household workers.
Preliminary estimate–unemployment. In the current month, the estimate of unemployment is an aggregate of the estimates for each of two categories: (1) Persons who were previously employed in industries covered by State UI laws; and (2) those who were entering the civilian labor force for the first time or reentering after a period of separation.
Substate adjustment for additivity. Estimates of employment and unemployment are prepared for the State and all LMAs within the State. The LMA estimates geographically exhaust the entire State. Thus, a proportional adjustment is applied to all substate preliminary LMA estimates to ensure that they add to the independently estimated State totals for employment and unemployment. For California and New York, the proportional adjustment is applied to all LMAs other than the two modeled areas, to ensure that the LMA estimates sum to an independent model-based estimate for the balance of State.
Benchmark correction. At the end of each year, substate estimates are revised. The revisions incorporate any changes in the inputs, such as revisions in the CES-based employment figures, corrections in UI claims counts, and updated historical relationships. The updated estimates are then readjusted to add to the revised (benchmarked) State estimates of employment and unemployment.
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