Tourism Demand in Catalonia: Detecting External Economic Factors
There is a lack of studies on tourism demand in Catalonia. To fill the gap, this paper focuses on detecting the macroeconomic factors that determine tourism demand in Catalonia. We also analyse the relation between these factors and tourism demand. Despite the strong seasonal component and the outliers in the time series of some countries, overnight stays give a better indication of tourism demand in Catalonia than the number of tourists. The degree of linear association between the macroeconomic variables and tourism demand is also higher when using quarterly rather than monthly data. Finally, there are notable differences between the results obtained for the different countries analysed. These results indicate that the best way to model tourism demand in Catalonia is to specify a quarterly model of overnight stays, differentiating between an aggregate demand model for the total number of tourists and specific models for each of the countries analysed.
|Date of creation:||05 Feb 2008|
|Date of revision:||12 Apr 2008|
|Publication status:||Published in TOURISMOS: An International Multidisciplinary Journal of Tourism 1.4(2009): pp. 13-28|
|Contact details of provider:|| Postal: Ludwigstraße 33, D-80539 Munich, Germany|
Web page: https://mpra.ub.uni-muenchen.de
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- Teresa Garin-Munoz & Teodosio Perez Amaral, 2000. "An econometric model for international tourism flows to Spain," Applied Economics Letters, Taylor & Francis Journals, vol. 7(8), pages 525-529.
- Witt, Stephen F. & Witt, Christine A., 1995. "Forecasting tourism demand: A review of empirical research," International Journal of Forecasting, Elsevier, vol. 11(3), pages 447-475, September.
- Claveria, Oscar & Pons, Ernest & Ramos, Raul, 2007. "Business and consumer expectations and macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 47-69.
- Gonzalez, Pilar & Moral, Paz, 1995. "An analysis of the international tourism demand in Spain," International Journal of Forecasting, Elsevier, vol. 11(2), pages 233-251, June.
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