Abstract
In this paper, we develop a panel data negative binomial count model that corrects for endogenous stratification and truncation. We also incorporate a latent class structure into our panel specification, which assumes that the observations are drawn from a finite number of segments, where the distributions differ in the intercept and the coefficients of the explanatory variables. The paper argues that count data panel models corrected for on-site sampling may still be inadequate and potentially misleading if the population of interest is heterogeneous with respect to the impact of the chosen explanatory variables. (JEL Q51, Q57)
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