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Modelling and forecasting tourism from East Asia to Thailand under temporal and spatial aggregation

Listed author(s):
  • Chang, Chia-Lin
  • Sriboonchitta, Songsak
  • Wiboonpongse, Aree

Tourism is one of the key service industries in Thailand, with a 5.27% share of Gross Domestic Product in 2003. Since 2000, international tourist arrivals, particularly those from East Asia, to Thailand have been on a continuous upward trend. Tourism forecasts can be made based on previous observations, so that historical analysis of tourist arrivals can provide a useful understanding of inbound trips and the behaviour of trends in foreign tourist arrivals to Thailand. As tourism is seasonal, a good forecast is required for stakeholders in the industry to manage risk. Previous research on tourism forecasts has typically been based on annual and monthly data analysis, while few past empirical tourism studies using the Box–Jenkins approach have taken account of pre-testing for seasonal unit roots based on Franses [P.H. Franses, Seasonality, nonstationarity and the forecasting of monthly time series, International Journal of Forecasting 7 (1991) 199–208] and Beaulieu and Miron [J.J. Beaulieu, J.A. Miron, Seasonal unit roots in aggregate U.S. data, Journal of Econometrics 55 (1993) 305–328] framework. An analysis of the time series of tourism demand, specifically monthly tourist arrivals from six major countries in East Asia to Thailand, from January 1971 to December 2005 is examined. This paper analyses stationary and non-stationary tourist arrivals series by formally testing for the presence of unit roots and seasonal unit roots prior to estimation, model selection and forecasting. Various Box–Jenkins autoregressive integrated moving average (ARIMA) models and seasonal ARIMA models are estimated, with the tourist arrivals series showing seasonal patterns. The fitted ARIMA and seasonal ARIMA models forecast tourist arrivals from East Asia very well for the period 2006(1)–2008(1). Total monthly and annual forecasts can be obtained through temporal and spatial aggregation.

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Article provided by Elsevier in its journal Mathematics and Computers in Simulation (MATCOM).

Volume (Year): 79 (2009)
Issue (Month): 5 ()
Pages: 1730-1744

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Handle: RePEc:eee:matcom:v:79:y:2009:i:5:p:1730-1744
DOI: 10.1016/j.matcom.2008.09.006
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  1. Joseph Beaulieu, J. & Miron, Jeffrey A., 1993. "Seasonal unit roots in aggregate U.S. data," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 305-328.
  2. Franses, Philip Hans, 1991. "Seasonality, non-stationarity and the forecasting of monthly time series," International Journal of Forecasting, Elsevier, vol. 7(2), pages 199-208, August.
  3. Christine Lim & Michael McAleer, 2000. "A seasonal analysis of Asian tourist arrivals to Australia," Applied Economics, Taylor & Francis Journals, vol. 32(4), pages 499-509.
  4. Lim, Christine & McAleer, Michael, 1999. "A seasonal analysis of Malaysian tourist arrivals to Australia," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 48(4), pages 573-583.
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