Forecasting foreign tourist arrivals to India using alternative forecasting combinations

Abstract

In this study, Naive I & Naive II, Grey and vector error correction (VEC) models are applied to forecast foreign tourist arrivals (FTAs) to India. Bates and Granger (1969) developed combination of forecasts by using the various combination methods in order to improve the single forecasts accuracy. Therefore, the combination methods based on simple average (SA) and inverse of mean absolute percentage error (IMAPE) is applied to improve the efficiency of individual forecasting methods. The data of FTAs to India from January 2003 to December 2016 obtained from http://www.indiastat.com are used for the overall empirical analysis. The results of the empirical study show that the combination forecasts have a better accuracy than the individual forecasts under root mean square error (RMSE), mean absolute percentage error (MAPE) and U-statistic (U) criteria. The study also demonstrates that the inverse of MAPE combination method is more suitable for forecasting of FTAs than simple average and others time series models.