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...

In this paper, we study the asymptotic behavior of specification tests in conditional moment restriction models under first-order local identification failure with dependent data. More specifically, we obtain conditions under which the conventional specification test for conditional moment...

I refine the test for clustering of Patton and Weller (2022) to allow for cluster switching. In a multivariate panel setting, clustering on timeaverages produces consistent estimators of means and group assignments. Once switching is introduced, we lose the consistency. In fact, under switching...

Modeling policy effects in the context of high-dimensional data requires a balanced consideration of omitted interaction bias and overfitting problems. This paper investigates the role of machine learning algorithms in stabilizing estimates and demonstrates the possible regularization bias...