Abstract
This study examines the performance of four alternative univariate seasonal time series forecasting models (seasonal autoregressive integrated moving average [SARIMA], SARIMA with Fourier transformation, ARAR, and fractionally integrated autoregressive-moving average) of tourist arrivals to 20 Croatian counties and the City of Zagreb. Both in-sample and out-of-sample forecasts reveal that the SARIMA model with Fourier transformation consistently outperforms the other models across the respective regions investigated.
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