Forecasting tourism demand: a cubic polynomial approach

Abstract

This paper examines the accuracy of a forecasting model in predicting international tourism arrivals, as represented by the number of worldwide visitors to Singapore. The cubic polynomial model is employed to forecast the volume of tourist arrivals from January 1989 to July 1990. The results are then compared with studies of the accuracy of forecasts by earlier work. The results demonstrate that the cubic polynomial method generates a slightly higher value of mean absolute percentage errors than that of sine wave nonlinear regression and seasonal–nonseasonal ARIMA. However, the cubic polynomial model has the advantage of generating forecasts with lower cost because of its intrinsic linearity. Finally, the diagnostic tool is applied to identify those predictive errors that manifest unusual features, and which result in deterioration of the mean absolute percentage error as our forecasting horizon expands.