Abstract
A method for incorporating unobserved heterogeneity into aggregate count data frameworks is presented and used to control for endogenous spatial sorting in zonal recreation models. The method is based on latent class analysis, which has become a popular tool for analyzing heterogeneous preferences with individual data but has not yet been applied to aggregate count data. The method is tested using data on backcountry hikers for a southern California study site and performs well for relatively small numbers of classes. The latent class model produces substantially smaller welfare estimates compared to a constrained version that assumes homogeneity throughout the population. (JEL Q51)
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