Abstract
Many measures of health-care use that are analyzed and modeled in econometrics are event counts, for example, number of hospital admissions, doctor visits, emergency room visits. Event count models such as the Poisson regression is a common but restrictive starting point in many investigations. To overcome several key limitations of the Poisson regression model, a number of alternatives have been developed that are widely used. These include the negative binomial regression, the two-part model, the quantile count regression, and the latent class model. This article surveys popular modeling frameworks, associated issues of statistical inference, and their key features. Models for both cross-section and panel data are covered.
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