Abstract
This paper introduces the use of graphical models for assessing the determinants of individual tourist spending. These models have the advantage of synthesizing and visualizing the relationships occurring within large sets of random variables, through an easy to interpret output. To this end, individual data from a large official survey of international tourists in Uruguay are used. Symmetric conditional independence structures are first investigated. Then subgraphs of each expenditure item's neighbourhood are extracted in order to assess the impact of main effects and interactions through proportional ordinal logistic regression. Results highlight the marginal role of socio-demographic variables and direct importance of accommodation type, destination and length of stay.