Time varying parameter error correction model approach to forecasting tourist arrivals in South Africa

In the field of tourism forecasting, the application of time-varying parameters has been successful in forecasting arrivals taking into account the changing behavior of tourists. This article uses quarterly data to forecast intercontinental tourism demand for a long-haul, developing destination (South Africa) by applying time-varying parameters (TVP) to single equation estimates, and comparing these with vector autoregressive results. Ex-ante forecasts are done for tourist arrivals from various continents, and forecasting accuracy is evaluated by determining the Mean Absolute Percentage Error (MAPE), the Mean Absolute Deviation/Mean ratio (MAD/mean), the percentage Root Mean Square Error (RMSE) and Theil's inequality coefficient. The results show that TVP do not always outperform other forecasting techniques.