Earnings Functions and Nonpecuniary Benefits

Abstract

Past empirical studies of earnings functions have used only pecuniary earnings measures. In this article, pecuniary, fringe, and certain nonpecuniary benefits are treated as additive components of a more comprehensive measure of labor market reward. The implications of including these additional benefits for estimates of earnings functions are assessed with two national sample data sets. It is found that the explanatory power of the simple human capital earnings model increases as the nonwage variables are added into the earnings measure. The importance of education clearly increases when fringe and nonpecuniary benefits are added; the change in the association between labor market experience and earnings is small. The increased importance of education is sustained even when measures of cognitive skills, motivation, and family background are taken into account.

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