Comparing Recreation Benefits from On-Site versus Household Surveys in Count Data Travel Cost Demand Models with Overdispersion

Abstract

On-site surveys of tourists often lead to overestimates of annual tourism because tourists who are frequent repeat visitors are more likely to be sampled. This unrepresentative sample leads to statistical problems known as ‘truncation’ and ‘endogenous stratification’ in widely used travel cost demand models. Further, wide variation in the number of on-site visits among tourists can lead to overdispersion in the dependent variable of count data travel cost models. The authors present the first real-world data correction for all three problems and compare the corrected estimates with the ideal household survey. Correcting for truncation and endogenous stratification in a count data specification allowing for overdispersion (negative binomial specification) lowers the demand and benefit estimate to a mean value not significantly different from the household estimate. If tourism researchers wish to develop visitor use estimates from on-site surveys consistent with household level surveys, the authors' improved demand estimators would allow them to do so with some confidence in the results.