Vigo, España
Palma de Mallorca, España
This paper investigates the possibility of improving the predictive ability of a tourism demand model with meteorological explanatory variables. The authors use as a case study the monthly British tourism demand for the Balearic Islands (Spain). For this purpose, a transfer function model and causal artificial neural network are fitted. The results are compared with those obtained by non-causal methods: an ARIMA model and an autoregressive neural network.
The results indicate that incorporating meteorological variables can increase predictive power, although the most accurate prediction is obtained using a non-causal model - specifically, an autoregressive neural network.
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