Forecasting British Tourist Arrivals in the Balearic Islands Using Meteorological Variables

Marcos à lvarez-Díaz and Jaume Rosselló-Nadal
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Marcos à lvarez-Díaz: Department of Economics, University of Vigo, Lagoas-Marcosende s/n, 36200 Vigo, Spain
Jaume Rosselló-Nadal: Departament d'Economia Aplicada, Centre de Recerca Econòmica (UIB·Sa Nostra), Carretera Valldemossa km 7.5, 07122 Palma de Mallorca, Spain
Authors registered in the RePEc Author Service: Jaume Rossello ()

Tourism Economics, 2010, vol. 16, issue 1, 153-168

Abstract: 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.

Keywords: tourism forecasting; meteorological variables; artificial neural networks; Balearic Islands (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:sae:toueco:v:16:y:2010:i:1:p:153-168

DOI: 10.5367/000000010790872079

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