Regional Data Forecasting Accuracy: The Case of Thailand

This article focuses on nine city-based regions in Thailand, using accommodation data from 1996 to 2002. The basic structural and seasonal autoregressive integrated moving average (ARIMA) models are used, with an ex ante forecasting period 2003 to 2004. Forecasts are derived regionally, and accuracy is compared using a benchmark of the forecasts for the whole of Thailand. The analysis determines whether it is possible to accurately forecast interregional tourist arrivals. The findings are that more accurate regional forecasts can be derived than international arrivals forecasts in this case and that a comparison of domestic and international regional arrivals forecasts is very useful in examining potential future tourism-based regional growth. Consequently, regional arrivals data are useful for accurately forecasting regional tourism demand not only in Thailand but also for other countries where regional data are available, such as China and India, to examine the impact of tourism either economically or socially.

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