Forecasting international quarterly tourist flows using error-correction and time-series models

Abstract

This paper compares a range of forecasting models in the context of predicting quarterly tourist flows into Australia from the major tourist markets of USA, Japan, UK and New Zealand. Models considered include the error-correction model, the autoregressive model, the autoregressive integrated moving average model, the basic structural model and a regression based time series model. Seasonality is an important feature of these series that requires careful handling. The relative performance of each model varies from country to country. The main conclusion is that relative to the time-series models, the error correction models perform poorly. This may be caused by the way in which decisions on how best to model nonstationarity and seasonality are made.