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August 2013

Wage estimates by job characteristic: NCS and OES program data

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NCS–OES estimation method

The method for calculating wage estimates by job characteristic follows essentially the procedures and formula that the OES program uses to calculate its estimates for the mean hourly wage, with a step added to incorporate the information about job characteristics from the NCS.7 The section titled “Occupational Employment Statistics,” of the BLS Handbook of methods, describes the OES procedures in detail. In the OES survey, wage rates of workers are typically reported as grouped data across 12 consecutive, nonoverlapping wage intervals. The survey then uses data from the NCS to calculate mean wage rates for these intervals and thereby produce estimates for the mean hourly wage. The extra step needed to produce the wage estimates for the job characteristics is to allocate the OES data by wage interval on the basis of proportions for the job characteristics from the NCS data.8

Consider the following illustration of OES data for a sampled establishment with 10 secretaries:9

An establishment employs 10 secretaries at the following wage rates:

                                         Rate            Number of secretaries

                                        $8/hour                        1
                                        $9/hour                        1
                                      $12/hour                        2
                                      $13/hour                        2
                                      $14/hour                        2
                                      $16/hour                        1
                                      $17/hour                        1

The establishment will report its secretaries’ wage rates to the OES survey as follows:

                   Wage interval                Description             Number of secretaries

                             A                     (under $ 7.50/hour)                     0
                             B                     ($ 7.50–$9.49/hour)                    2
                             C                    ($ 9.50–$11.99/hour)                   0

                             D                    ($12.00–$15.24/hour)                  6
                             E                     ($15.25–$19.24/hour)                  2

This illustration can be extended to demonstrate the calculation of wage estimates by characteristic. Consider the NCS observations for secretaries from the same area as the OES-sampled establishment, and divide those observations into appropriate wage intervals based on the preceding hourly wage rates. Suppose that, among those NCS observations for which the hourly wage rate falls within interval B ($7.50–$9.49/hour), half of the workers work part time and half work full time. Then the NCS–OES estimation method would allocate the two workers from the OES-sampled establishment who fall into wage interval B as one part-time worker and one full-time worker. Suppose further that, among those NCS observations for which the wage rate falls within interval D ($12.00–$15.24/hour), the proportion of workers who work part time equals one-third. Then the six workers from the OES-sampled establishment who fall into interval D are allocated as two part-time and four full-time workers. Finally, suppose that, among those NCS observations for which the wage rate falls within interval E ($15.25–$19.24/hour), all the workers work full time. Then the two workers from the OES-sampled establishment who fall into interval E would both be allocated as full-time workers.

Notes

7 For a detailed description of the OES procedures, see “Occupational Employment Statistics,” BLS handbook of methods (U.S. Bureau of Labor Statistics, December 10, 2009), http://www.bls.gov/opub/hom/homch3.htm.

8 See the appendix for a demonstration of the parallels between this procedure and a standard procedure of benchmarking the NCS sample weights to OES employment counts by area, occupation, and wage interval.

9 The illustration is taken from “Occupational Employment Statistics,” BLS Handbook of methods. 

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About the Author

Michael K. Lettau
lettau.michael@bls.gov

Michael K. Lettau is Branch Chief, Division of Data Validation and Estimation, Office of Compensation and Working Conditions, Bureau of Labor Statistics.

Dee A. Zamora
zamora.dee@bls.gov

Dee A. Zamora is a mathematical statistician in the Statistical Methods Group, Office of Compensation and Working Conditions, Bureau of Labor Statistics.