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The causal effect of education on earnings
TL;DR: This paper surveys the recent literature on the causal relationship between education and earnings and concludes that the average (or average marginal) return to education is not much below the estimate that emerges from a standard human capital earnings function fit by OLS.
Abstract: This paper surveys the recent literature on the causal relationship between education and earnings. I focus on four areas of work: theoretical and econometric advances in modelling the causal effect of education in the presence of heterogeneous returns to schooling; recent studies that use institutional aspects of the education system to form instrumental variables estimates of the return to schooling; recent studies of the earnings and schooling of twins; and recent attempts to explicitly model sources of heterogeneity in the returns to education. Consistent with earlier surveys of the literature, I conclude that the average (or average marginal) return to education is not much below the estimate that emerges from a standard human capital earnings function fit by OLS. Evidence from the latest studies of identical twins suggests a small upward "ability" bias -- on the order of 10%. A consistent finding among studies using instrumental variables based on institutional changes in the education system is that the estimated returns to schooling are 20-40% above the corresponding OLS estimates. Part of the explanation for this finding may be that marginal returns to schooling for certain subgroups -- particularly relatively disadvantaged groups with low education outcomes -- are higher than the average marginal returns to education in the population as a whole.
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01 Jan 2015
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TL;DR: In this article, the authors investigated discrimination against women within the Brazilian labor market using firm-level data and considering the proportion of female employees as a proxy for the extent of discrimination.
Abstract: In this study, we investigated discrimination against women within the Brazilian labor market using firm-level data and considering the proportion of female employees as a proxy for the extent of discrimination. Estimating the profit efficiency of firms using data envelopment analysis, and regressing it on the proportion of female employees and other firm characteristics, we found that the proportion of female employees is positively correlated with firm profit efficiency. Our finding indicates that firms employing a high proportion of female workers incur a lower labor cost while producing the same level of output compared to firms employing a low proportion of female employees, and provide strong evidence of the existence of discrimination against female employees within the Brazilian labor market.
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TL;DR: In this article, the authors proposed refutable nonparametric local restrictions to identify individual-specific causal effects of an ordered discrete endogenous variable by identifying the partial differences of a structural relation.
Abstract: This paper discusses how to identify individual-specific causal effects of an ordered discrete endogenous variable. The counterfactual heterogeneous causal information is recovered by identifying the partial differences of a structural relation. The proposed refutable nonparametric local restrictions exploit the fact that the pattern of endogeneity may vary across the level of the unobserved variable. The restrictions adopted in this paper impose a sense of order to an unordered binary endogeneous variable. This allows for a unified structural approach to studying various treatment effects when self-selection on unobservables is present. The usefulness of the identification results is illustrated using the data on the Vietnam-era veterans. The empirical findings reveal that when other observable characteristics are identical, military service had positive impacts for individuals with low (unobservable) earnings potential, while it had negative impacts for those with high earnings potential. This heterogeneity would not be detected by average effects which would underestimate the actual effects because different signs would be cancelled out. This partial identification result can be used to test homogeneity in response. When homogeneity is rejected, many parameters based on averages may deliver misleading information.
2 citations