A Multivariate Prediction Copula Model to Characterize the Expenditure Categories in Tourism

Abstract

The aim of this article is to introduce a multivariate statistical model that represents the expenditure of tourists disaggregated by categories. The model is applied to study the distribution of the expenditure of cruise passengers in Uruguay, using data of the 2016-2017 cruise season survey (collected by the Ministry of Tourism). Given the mixed distribution in each component of the main variable, the model is implemented in two stages and using copulas to obtain a conditional distribution of the different items of expenditure, characterizing the dependence between them. The empirical results show that the key variables that determine the average spending of cruise tourists are their residence and the port of arrival of the cruise. The parameters representing dependence of the copula show moderate association between the different categories of expenditure, in particular for cruisers disembarking in Montevideo, the capital of Uruguay. In addition, it can be noted that the expenditure pattern in each item shows time dependence. In general, the empirical results show that a cruiser that spends more on one item is likely to spend more (less) on a complementary (noncomplementary) items of expense.