Labor Supply Estimation Biases from Disregarding Non-Wage Benefits

Abstract

Labor supply models and research underpinned by labor supply decisions typically assume the agents’ choices are functions of wage and wage offers. However, there is evidence that these selections are not only wage-driven, but at least in part depend on non-wage benefits encompassed in jobs and occupations. In this paper, I develop and estimate a stochastic dynamic model of occupational and job choice, where non-wage benefits are directly incorporated into the decision alongside wages. A nested model within this is a wage model, representing common practice in the literature, where non-wage benefits are disregarded. I separately estimate the full model and the nested wage model in order to compare the implications of omitting non-wage benefits. Three analyses are compared: elasticities, economy-wide structural changes in occupations, and inequality reduction intervention policies. I find that while disregarding non-wage benefits generally causes biases, there are cases when the two models predict very similar outcomes and have close estimates, such as in occupational-specific elasticities and job transition elasticities. However, I demonstrate that these special cases are products of canceling biases, and that the same estimates on subpopulations are biased. These results suggest that in most cases, ignoring non-wage benefits will bias estimates by overestimating the importance of wage in the selection process (and so any intervention or change in wages will be over-emphasized) and by disregarding changes in relative prices between wage and non-wage benefits, such as happens through changes in wage taxes or in non-wage benefits. These biases can be severe. The results suggest that ignoring non-wage benefits in labor supply decisions is appropriate only in the special case in which subpopulation biases negate each other, which is atypical.