This paper provides an expression for the bias of the OLS estimator of the schooling coefficient in a simple static … 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 …

We characterize the bias of propensity score based estimators of common average treatment effect parameters in the case …

This paper introduces bias-corrected estimators for nonlinear panel data models with both time invariant and time …/selection bias. We then estimate the primary equation by fixed effects including an appropriately constructed control function from … both steps might employ nonlinear fixed effects procedures it is necessary to bias adjust the estimates due to the …

cross-sectional average of the variables under consideration. We propose bias corrected estimators, derive their asymptotic …

This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao … trivial due to the incidental parameters problem that arises, and its implications for estimation and inference. We approach …

) bias in β^. We add to this literature in two important ways. First, we focus on estimation of the fixed effects proper, as … these have become increasingly important in applied work.Second, we build on a bias-reduction approach originally developed …

This paper uses the control function to develop a framework for testing for selection bias. The idea behind our … magnitude of potential selection bias. Averaging this correction term with respect to appropriate weights yields the degree of … selection bias for alternative treatment effects of interest. One advantage of our framework is that it motivates when is …