Leverage and Covariance Matrix Estimation in Finite-Sample IV Regressions

Abstract

This paper develops basic algebraic concepts for instrumental variables (IV) regressions which are used to derive the leverage and influence of observations on the 2SLS estimate and compute alternative heteroskedasticity-consistent (HC1, HC2 and HC3) estimators for the 2SLS covariance matrix in a finite-sample context. Monte Carlo simulations and applications to growth regressions are used to evaluate the performance of these estimators. The results support the use of HC3 instead of White’s robust standard errors in small and unbalanced data sets. The leverage and influence of observations can be examined with the various measures derived in the paper.