investigate the performance of stacked DID estimators. We show that the most basic stacked estimator does not identify the target … bias can be eliminated using corrective sample weights. We present a weighted stacked DID estimator, and show that it … correctly identifies the target aggregate, providing justification for using the estimator in applied work …

the finite sample performance of the BLP estimator, particularly when using well-targeted summary statistics or "optimal …

parameter can invoke strong assumptions to motivate a restricted estimator that is precise but may be heavily biased, or they … can relax some of these assumptions to motivate a more robust, but variable, unrestricted estimator. When a bound on the … bias of the restricted estimator is available, it is optimal to shrink the unrestricted estimator towards the restricted …

Econometrica paper that developed what later became known as the Tobit estimator. This golden anniversary milestone provides a … modeling has played in empirical health economics. Of primary focus here is how Tobin's estimator came to be and came to take … root in empirical health economics. The paper provides a brief history of Tobin's estimator and related methods up through …