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...

The usual decomposition of effects in corner solution models into extensive and intensive margins is generally incompatible with a causal interpretation. This paper proposes a decomposition based on the joint distribution of potential outcomes which is meaningful in a causal sense. The...

Applications of zero-inflated count data models have proliferated in empirical economic research. There is a downside to this development, as zero-inflated Poisson or zero-inflated Negative Binomial Maximum Likelihood estimators are not robust to misspecification. In contrast, simple Poisson...

The paper re-examines existing estimators for the panel data fixed effects ordered logit model, proposes a new one, and studies the sampling properties of these estimators in a series of Monte Carlo simulations. There are two main findings. First, we show that some of the estimators used in the...

Many applied settings in empirical economics require estimation of a large number of fixed effects, like teacher effects or location effects. In the context of binary response variables, previous studies have been limited to the linear probability model, citing perfect prediction and incidental...