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...

Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly...

We present motivation and new Stata commands for modeling count data. While the focus of this article is on modeling data with underdispersion, the new command for fitting generalized Poisson regression models is also suitable as an alternative to negative binomial regression for overdispersed data.