
Modeling and forecasting techniques of the tourist arrivals are many and diverse. There is no unique model that exactly outperforms the other models in every situation. Actually a few studies have realized modeling and forecasting the tourist arrivals to Turkey and these studies have not focused on the total tourist arrivals. These studies have focused on the tourist arrivals to Turkey country by country (or OECD countries). In addition to this, structural time series models have not been used in modeling and forecasting the tourist arrivals to Turkey. In this sense, this paper is the first study which uses the seasonal autoregressive integrated moving average model and the structural time series model in order to forecast the total tourist arrivals to Turkey. Two different models are developed to forecast the total tourist arrivals to Turkey using monthly data for the period 2002-2013. The results of the study show that two models provide accurate predictions but the seasonal autoregressive integrated moving average model produces more accurate short-term forecasts than the structural time series model. It is noted that the seasonal autoregressive integrated moving average model shows a very successful performance in the forecasting the total tourist arrivals to Turkey.
Turkey, tourist arrivals, structural time series models, arima, tourist demand
Turkey, tourist arrivals, structural time series models, arima, tourist demand
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