Abstract
In contrast with the rapid development of forecast modeling in tourism, there has been little attention given to identifying the best measures of important explanatory variables. This article focused on selecting the best surrogate of tourism price from two measures considered important determinants in modeling tourism demand: the exchange rate-adjusted consumer price index ratio of origin and destination countries, and the divided variables of exchange rate and relative consumer price indexes. Two different models using these measures of tourism prices were compared in terms of their forecasting performance using the Johansen multivariate cointegration approach. We used aggregate data on international tourism demand in Korea. Test results, including forecasting performance and forecast error decompositions, were not clear cut but indicated that the divided measures of tourism prices variables with exchange rate and relative consumer price index are likely best for tourism demand modeling.
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