Maximum Likelihood (ML) shows both lower power and higher bias in small sample Monte Carlo experiments than Indirect Inference (II) and IIís higher power comes from its use of the model-restricted distribution of the auxiliary model coeffi cients (Le et al. 2016). We show here that IIís higher...

"Since the advent of heteroskedasticity-robust standard errors, several papers have proposed adjustments to the original White formulation. We replicate earlier findings that each of these adjusted estimators performs quite poorly in finite samples. We propose a class of alternative...