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.

Compositional tourists’ expenditure: Modeling through Dirichlet regression

“…This study shows that expenditure patterns in accommodation, in food, and other expense items vary (significantly) according to the season, the tourist destination, the type of accommodation, and the tourist's nationality. In general terms, these results are consistent with those obtained by Brida et al (2021) applying different methodologies. In this sense, this research provides inputs and tools to analyze the behavior of tourists (concerning spending patterns) as consumers visiting Uruguay.…”

“…The covariates that are surveyed for each group and that are used for the analysis are: average age, nationality, main destination in Uruguay, occupation of the respondent, and the accommodation in which they stayed the most days. Occupations and nationalities are grouped in the same way as in Brida et al (2021). Table 1 shows the conformation marginal percentages according to the different covariates.…”

“…In this study, only those groups that declare spending in at least one of the items are considered, (∑i=1mXi≠0). To include these groups of tourists, who do not report expenses, a feasible way is to carry out a two-step model, as in Brida et al (2018) and Brida et al (2021), where in the first step a logistic model is adjusted to allow classifying the group in whether or not it reports any expenses. Once the normalization has been carried out (it is satisfied that ∑i=1mYi=1), the multivariate vector of relative expenditures by group Y = ( Y 1 , …, Y m ) whose components add up to 1 is a compositional data, that is, it is located in the closed simplex of dimension m ,…”