A Bivariate Count Data Model for Household Tourism Demand
Households' choice of the number of leisure trips and the total number of overnight stays is empirically studied using Swedish tourism data. A bivariate hurdle approach separating the participation (to travel and stay the night or not) from the quantity (the number of trips and nights) decision is employed. The quantity decision is modelled with a bivariate mixed Poisson lognormal model allowing for both positive as well as negative correlation between count variables. The observed endogenous variables are drawn from a truncated density and estimation is pursued by simulated maximum likelihood. The estimation results indicate a negative correlation between the number of trips and nights. In most cases ownprice effects are as expected negative while estimates of cross-price effects vary between samples. A small policy study reveals that household's who travel (before and after the policy measure) substitute trips for nights as the travel cost increases.
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