Persistence bias and the wage-schooling model - Corrado Andini (Institute for the Study of Labor (IZA), 2013)
This paper provides an expression for the bias of the OLS estimator of the schooling coefficient in a simple static wage-schooling model where earnings persistence is not accounted for. It is argued that the OLS estimator of the schooling coefficient is biased upward, and the bias is increasing with potential labor-market experience and the degree of earnings persistence. In addition, NLSY data are used to show that the magnitude of the persistence bias is non-negligible, and the bias cannot be cured by increasing the control set. Further, it is shown that disregarding earnings persistence is still problematic for the estimation of the schooling coefficient even if individual unobserved heterogeneity and endogeneity are taken into account. Overall, the findings support the dynamic approach to the estimation of wage-schooling models recently suggested by Andini (2012; 2013).
Keywords: C23; I21; J31; 330; schooling; wages; dynamic panel-data models