An Assessment of Combining Tourism Demand Forecasts over Different Time Horizons
Shen, S, Li, G and Song, H (2008) An Assessment of Combining Tourism Demand Forecasts over Different Time Horizons Journal of Travel Research, 47 (2). 197 - 207. ISSN 0047-2875
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This study investigates the performance of combination forecasts in comparison to individual forecasts. The empirical study focuses on the U. K. outbound leisure tourism demand for the United States. The combination forecasts are based on the competing forecasts generated from seven individual forecasting techniques. The three combination methods examined in this study are the simple average combination method, the variance-covariance combination method, and the discounted mean square forecast error method. The empirical results suggest that combination forecasts overall play an important role in the improvement of forecasting accuracy in that they are superior to the best of the individual forecasts over different forecasting horizons. The variance-covariance combination method turns out to be the best among the three combination methods. Another finding is that the encompassing test does not significantly contribute to the improved accuracy of combination forecasts. This study provides robust evidence for the efficiency of combination forecasts.
|Uncontrolled Keywords:||combination forecast, tourism demand, econometric model, forecast performance, encompassing test, ECONOMIC FORECASTS, COMBINATION, COINTEGRATION, MODELS, TESTS, REGRESSION, ACCURACY, SERIES|
|Divisions:||Faculty of Business, Economics and Law > Hospitality and Tourism Management|
|Depositing User:||Mr Adam Field|
|Date Deposited:||09 Nov 2011 12:05|
|Last Modified:||09 Jun 2014 13:31|
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