CONTROLLING FOR OBSERVEDAND UNOBSERVED SITE CHARACTERISTICS IN RUMMODELS OF RECREATION DEMAND

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 vari-able, the resulting parameter estimates are likely to be biased. We develop a Bayesian approach to estimating amodel that incorporates a full set of alternative-specific constants, insulating the key travel cost parameter from the influence of unobservables. The proposed posterior simulator can be used in the mixed logit framework in which some parameters of the conditional utility function are random. We apply the estimation procedures to data from the Iowa Lakes Project. Key words: recreation demand, Bayesian econometrics, alternative specific constants