Predicting Random Level and Seasonality of Hotel Prices: a Latent Growth Curve Approach

This article examines the effect on price of different characteristics of holiday hotels in the sun-andbeach segment, under the hedonic function perspective. Monthly prices of the majority of hotels in the five major tourist regions in the Spanish continental Mediterranean coast were gathered from May to October 1999, from the tour operator catalogues. Hedonic functions are specified as random-effect models and parameterized as structural equation models with two latent variables, a random peak season price and a random width of seasonal fluctuations. This model can be considered to be a latent growth curve model applied to seasonality rather than growth. Characteristics of the hotels were used as predictors of both latent variables in models fitted for each region separately. Hotel category, region, distance to the beach, availability of parking place, and room equipment have an effect on both peak price and seasonality. Three-star hotels have the highest seasonality and hotels located in the southern regions the lowest. This can be explained by a warmer climate in autumn in the southern regions. The model is fitted to the pooled data of all regions and expanded to include the effect of climate on prices.