I demonstrate that Ai and Norton's (2003) point about cross differences is not relevant for the estimation of the treatment effect in nonlinear "difference-in-differences" models such as probit, logit or tobit, because the cross difference is not equal to the treatment effect, which is the...

This paper gives a short overview of Monte Carlo studies on the usefulness of Heckman's (1976, 1979) two-step estimator for estimating a selection model. It shows that exploratory work to check for collinearity problems is strongly recommended before deciding on which estimator to apply. In the...

This paper gives a short overview of Monte Carlo studies on the usefulness of Heckman's (1976, 1979) twostep estimator for estimating a selection model. It shows that exploratory work to check for collinearity problems is strongly recommended before deciding on which estimator to apply. In the...

Criteria used in hiring workers often do not reflect the skills required on the job. By comparing trainee performance for newly hired workers conditional on competitive civil service examination scores for hiring French public sector workers, we test whether women and men with the same civil...

I demonstrate that Ai and Norton's (2003) point about cross differences is not relevant for the estimation of the treatment effect in nonlinear difference-in-differences models such as probit, logit or tobit, because the cross difference is not equal to the treatment effect, which is the...

Because accountability may improve the comparability that is compromised by lenient grading, we compare exit exam outcomes in the same schools before and after a policy change that increased teacher accountability by anchoring grading scales. In particular, using a large administrative dataset...