BLS Handbook of Methods

Chapter 1.
Labor Force Data Derived from the Current Population Survey

Estimation Methods
Under the estimating methods used in the CPS, all of the results for a given month become available simultaneously and are based on returns from all respondents. The estimation procedure involves weighting the data from each sample person by the inverse of the probability of the person being in the sample. This gives a rough measure of the number of actual persons that the sample person represents. Since 1985, most sample persons within the same State have had the same probability of selection.

Some selection probabilities may differ within a State due to the sample design or for operational reasons. Field subsampling, for example, which is carried out when areas selected for the sample are found to contain many more households than expected, may cause probabilities of selection to differ for some sample areas within a State. Through a series of estimation steps (outlined below), the selection probabilities are adjusted for noninterviews and survey undercoverage; data from previous months are incorporated into the estimates through the composite estimation procedure.

1. Noninterview adjustment. The weights for all interviewed households are adjusted to account for occupied sample households for which no information was obtained because of the occupants’ absence, impassable roads, refusals, or unavailability of the respondents for other reasons. This noninterview adjustment is made separately for clusters of similar sample areas that are usually, but not necessarily, contained within a State. Similarity of sample areas is based on Metropolitan Statistical Area (MSA) status and size. Within each cluster, there is a further breakdown by residence. Each MSA cluster is split into “central city” and “balance of the MSA.” Each non-MSA cluster is split into “urban” and “rural” residence categories. The proportion of sample households not interviewed varies from 7 to 8 percent, depending on weather, vacation times, and so forth.
2. Ratio estimates. The distribution of the population selected for the sample differs by chance from that of the population as a whole in such characteristics as age, race, sex, ethnicity, and State of residence. Because these characteristics are closely correlated with labor force participation and other principal measurements made from the sample, the survey estimates can be substantially improved when weighted appropriately by the known distribution of these population characteristics. This is accomplished through two stages of ratio adjustment, as follows:
   1. First-stage ratio estimation. The purpose of the first-stage ratio adjustment is to reduce the contribution to variance of selecting a sample of PSUs rather than drawing sample households from every PSU in the Nation. This adjustment is made to the CPS weights in two race cells: black and nonblack; and two age cells: 0 to 15 years and 16 years and older; it is applied only to data from PSUs that are not self-representing and for those States that have a substantial number of black households. The procedure corrects for differences that existed in each State cell at the time of the 2000 census between 1) the race distribution of the population in sample PSUs and 2) the race distribution of all PSUs. (Both 1 and 2 exclude self-representing PSUs.)
   2. Second-stage ratio estimation. This procedure substantially reduces the variability of estimates and corrects, to some extent, for CPS undercoverage. The CPS sample weights are adjusted to ensure that sample-based estimates of population match independent population controls.

   Beginning in 2003, the second-stage weighting has new coverage steps “0A” and “0B” that are followed by an iterative raking process. California and New York are split into substate areas, and 53 states/areas are used in Step 0B and Step 1 (Los Angeles-Long Beach metropolitan area; balance of California; New York City; balance of New York; the other 48 states; and the District of Columbia.)

   The noniterated National Coverage Step 0A is added primarily to improve the efficiency of adjustment for subpopulations that are prone to undercoverage. Step 0A also provides some control for Asian race that could not be included in the iterated steps.

   The noniterated State Coverage Step 0B is designed to adjust for race/gender/age coverage differences between the states. Race is limited to black and nonblack, and there is no ethnicity component in the step.

   The three iterated steps adjust sample weights to the following control groups:

   
   
   1. State step—6 gender x age cells defined for 53 states/areas
   2. Ethnicity step—26 Hispanic and 26 non-Hispanic gender x age cells
   3. Race step—34 white-only, 26 black-only, and 26 Asian-only and residual gender x age cells

The independent population controls are prepared by projecting forward the resident population as enumerated on April 1, 2000. The projections are derived by updating demographic census data with information from a variety of other data sources that account for births, deaths, and net migration. Subtracting estimated numbers of resident Armed Forces personnel and institutionalized persons reduces the resident population to the civilian noninstitutional population.

Composite estimation results in a reduction in the sampling error beyond that which is achieved through the two stages of ratio estimation. For some items, the reduction is substantial. The resultant gains in reliability are greatest in estimates of month-to-month change, although gains also are usually obtained for estimates of level in a given month, change from year to year, and change over other intervals of time.

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