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

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  • Chang, Chia-Lin
  • Sriboonchitta, Songsak
  • Wiboonpongse, Aree

Abstract

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.

Suggested Citation

  • Chang, Chia-Lin & Sriboonchitta, Songsak & Wiboonpongse, Aree, 2009. "Modelling and forecasting tourism from East Asia to Thailand under temporal and spatial aggregation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(5), pages 1730-1744.
    • 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. 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.
    2. 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.
    3. Franses, P. H., 1990. "Testing For Seasonal Unit Roots In Monthly Data," Econometric Institute Archives 272393, Erasmus University Rotterdam.
    4. 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.
    5. 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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    Cited by:

    1. Daniya Tlegenova, 2015. "Forecasting Exchange Rates Using Time Series Analysis: The sample of the currency of Kazakhstan," Papers 1508.07534, arXiv.org.
    2. Chia-Lin Chang & Thanchanok Khamkaew & Roengchai Tansuchat & Michael McAleer, 2011. "Interdependence of International Tourism Demand and Volatility in Leading ASEAN Destinations," Tourism Economics, , vol. 17(3), pages 481-507, June.
    3. Ponjan, Pathomdanai & Thirawat, Nipawan, 2016. "Impacts of Thailand’s tourism tax cut: A CGE analysis," Annals of Tourism Research, Elsevier, vol. 61(C), pages 45-62.
    4. Hari Sharma Neupane & Chandra Lal Shrestha & Tara Prasad Upadhyaya, 2012. "Modelling Monthly International Tourist Arrivals and Its Risk in Nepal," NRB Economic Review, Nepal Rastra Bank, Research Department, vol. 24(1), pages 28-47, April.
    5. Andrawis, Robert R. & Atiya, Amir F. & El-Shishiny, Hisham, 2011. "Combination of long term and short term forecasts, with application to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 27(3), pages 870-886, July.
    6. So, Mike K.P. & Chung, Ray S.W., 2014. "Dynamic seasonality in time series," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 212-226.
    7. Juan Gabriel Brida & Wiston Adrián Risso, 2011. "Research Note: Tourism Demand Forecasting with SARIMA Models – the Case of South Tyrol," Tourism Economics, , vol. 17(1), pages 209-221, February.
    8. Ntebogang Dinah Moroke, 2014. "The robustness and accuracy of Box-Jenkins ARIMA in modeling and forecasting household debt in South Africa," Journal of Economics and Behavioral Studies, AMH International, vol. 6(9), pages 748-759.
    9. Komkrit Wongkhae & Songsak Sriboonchitta & Kanchana Choketaworn & Chukiat Chaiboonsri, 2012. "Does price matter? The FMOLS and DOLS estimation of industrial countries tourists outbound to four ASEAN countries," The Empirical Econometrics and Quantitative Economics Letters, Faculty of Economics, Chiang Mai University, vol. 1(4), pages 107-128, December.
    10. Tamerlan Mashadihasanli, 2022. "Stock Market Price Forecasting Using the Arima Model: an Application to Istanbul, Turkiye," Journal of Economic Policy Researches, Istanbul University, Faculty of Economics, vol. 9(2), pages 439-454, July.
    11. Hari Sharma Neupane & Chandra Lal Shrestha & Tara Prasad Upadhyaya, 2012. "Modelling Monthly International Tourist Arrivals and Its Risk in Nepal," NRB Economic Review, Nepal Rastra Bank, Economic Research Department, vol. 24(1), pages 28-47, April.

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