A Comparative Study of the Use of GAM and GLM in Tourism Research

Abstract

In this paper, we investigate the impact that spatial and micro-economic variables have on the probability that a household goes on holiday. In doing so, we propose two alternative modelling specifications: a classic discrete choice model and a semiparametric logistic model. The semiparametric model extends the classic logistic model, usually employed in studies on participation in tourism, allowing modelling in a flexible manner for continuous predictors without making any a priori assumption. This is achieved via the use of penalized regression splines. A sample of Italian households was considered for our study. Comparing the results of the two approaches, we found that both methods opportunely captured, in terms of signs, the relationships under investigation. However, the use of a more flexible approach has allowed us to uncover some interesting non-linearities that are usually not assumed a priori, thus improving the interpretation of the results.

Keywords: cubic regression spline, logistic regression, micro-economic factors, predicted probabilities, tourism

JEL Classification: C14, D01