Bias correction can often improve the finite sample performance of estimators. We show that the choice of bias correction method has no effect on the higherorder variance of semiparametrically efficient parametric estimators, so long as the estimate of the bias is asymptotically linear. It is...

We study cluster-robust inference for binary response models. Inference based on the most commonly-used cluster-robust variance matrix estimator (CRVE) can be very unreliable. We study several alternatives. Conceptually the simplest of these, but also the most computationally demanding, involves...

In the data envelopment analysis (DEA) literature, productivity change captured by the Malmquist productivity index, especially in terms of a deterministic environment and stochastic variability in inputs and outputs, has been somewhat ignored. Therefore, this study developed a frm-specifc,...