Implementing weak-instrument robust tests for a general class of instrumental-variables models

Abstract

We present a minimum distance approach for conducting hypothesis testing in the presence of potentially weak instruments. Under this approach, we propose size-correct tests for limited dependent variable models with endogenous explanatory variables such as endogenous tobit and probit models. Additionally, we extend weak-instrument tests for the linear instrumental-variables model by allowing for variance-covariance estimation that is robust to arbitrary heteroskedasticity or intracluster dependence. We invert these tests to construct confidence intervals on the coefficient of the endogenous variable. We also provide a postestimation command for Stata, called rivtest, for computing the tests and estimating confidence intervals. © 2009 StataCorp LP.