We describe and employ a Bayesian posterior simulator for fitting a high-dimensional system of ordinal or count outcome equations. The model is then applied to describe the multiple site recreation demands of individual agents, and we argue that our approach provides advantages relative to...

Recreation demand models are typically plagued by limited information on site attributes. If these unobserved site attributes are correlated with the observed characteristics and/or the travel cost variable, the resulting parameter estimates are likely to be biased. We develop a Bayesian...

Random Utility Maximization (RUM) models of recreation demand are typically plaguedby limited information on environmental and other attributes characterizing the available sitesin the choice set. To the extent that these unobserved site attributes are correlated with theobserved characteristics...