标题：Panel Travel Cost Count Data Models for On-Site Samples that Incorporate Unobserved Heterogeneity with Respect to the Impact of the Explanatory Variables
摘要：In this paper, we examine heterogeneity in the trip preferences of recreationists by applying a random parameters negative binomial model and a latent class negative binomial model to a panel data set of beach users at a site on the west coast of Ireland. This is the first such attempt in the literature to account for heterogeneity with respect to the impact of the chosen explanatory variables in contingent behaviour travel cost models of demand where the researcher also must account for the fact that the sample data has been collected on-site. The analysis also develops individual consumer surplus estimates and finds that estimates are systematically affected by both the random parameter and latent class specifications. There is also evidence that accounting for individual heterogeneity improves the statistical fit of the models and provides a more informative description of the drivers of recreationalist trip behaviour.
