Chapter 8.
National Compensation Measures

Uses and Limitations
The compensation, wage, and benefit data developed in BLS surveys have a variety of uses. Federal, State, and local agencies use them in compensation administration and in the formulation of public policy on compensation. The data are of value to Federal and State mediation and conciliation services and to State employment compensation agencies in judging the suitability of job offers. Bureau data are also used in private industry for determining compensation. Survey data are considered by employers in selecting locations for new facilities and in cost estimating relating to contract work.

In addition, the data are used in economic analysis. Knowledge of levels, structures, and trends of pay rates and benefit practices is required in the analysis of current economic developments and in studies relating to wage dispersion and differentials. The integration of the compensation surveys allows costs to be linked to specific benefit practices because all data are based on the same survey methodology and definitions.

The ECI has been designated a principal Federal economic indicator by OMB. It is the only measure of labor costs that treats wages and salaries and total compensation consistently and provides consistent subseries by occupation and industry. The ECI is used by the Federal Reserve Board to monitor the effects of fiscal and monetary policies and to formulate those policies. It enables analysts and policymakers to assess the effects of labor cost changes on the economy, both in the aggregate and by sectors. The ECI is particularly important in studies of the relationships among prices, productivity, labor costs, and employment.

Although these measures of compensation have many uses, their limitations must be kept in mind. The data are subject to sampling errors, which may cause deviations from the results that would be obtained if the actual records of all establishments could be used. The sampling error is described in the earlier section on Reliability of Estimates.

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