Simple tests for exogeneity of a binary explanatory variable in count data regression models

Abstract

This article investigates power and size of some tests for exogeneity of a binary explanatory variable in count models by conducting extensive Monte Carlo simulations. The tests under consideration are Hausman contrast tests as well
as univariate Wald tests, including a new test of notably easy implementation.
Performance of the tests is explored under misspecification of the underlying model and under different conditions regarding the instruments. The results indicate that
often the tests that are simpler to estimate outperform tests that are more demanding.
This is especially the case for the new test.