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Weather conditions are important determinants of tourism demand. After reviewing the main contributions of previous research on the role of climatic variables in tourism demand functions, we explore different modelling alternatives to introduce temperature and rainfall in a gravity model. The dataset used comprises interregional tourism flows by Spanish residents from 2011 to 2015. We first estimate a benchmark model with both temperature and rainfall at the destination expressed in levels, and then consider some extensions to this model. In particular, special attention is paid to analyzing whether the sensitivity that tourists may have to weather factors can change across seasons. Other modelling issues examined include the relationship between climatic variables at the destination and at home, the influence of weather in previous periods (lagged values of temperature and rain), the variability of the weather variables (captured by the standard deviation of these variables), or whether the effect of temperature varies with the climatic characteristics of the region. Our empirical results confirm that spring and summer tourism in Spain is more sensitive to weather conditions, that the number of domestic overnight stays in Spain is strongly influenced by changes in the difference in temperature between tourists’ home and destination regions, that the estimated parameters of lagged weather variables are higher than those corresponding to the travelling months, that temperature variability in the destination region reduces tourism demand, and that the effect of temperature on destination choice for residents in moderate-climate regions is lower than for residents in other types of regions.

Modelling the effect of weather on tourism: does it vary across seasons?