In this paper, we estimate price and income semi-elasticities of the length of stay at different destinations in Italy using the 'Multipurpose survey on tourism demand, holidays and trips' provided by the Italian National Institute of Statistics (ISTAT). We derive the conditional demand function for the length of stay, which depends on tourists' socio-demographic characteristics, travel characteristics, income and price of touristic services. Since income was not reported in our database, we use the propensity score matching to retrieve this information from the 'Survey on household income and wealth (SHIW)', and we use quantile regression to account for the multimodality of the length of stay. Â© 2012 John Wiley & Sons, Ltd.
- Count quantile regression
- Geography, Planning and Development
- Length of stay
- Nature and Landscape Conservation