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Forecasting tourist arrivals to Turkey

Authors: Yilmaz, Engin;

Forecasting tourist arrivals to Turkey

Abstract

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.

Country
Croatia
Related Organizations
Keywords

Turkey, tourist arrivals, structural time series models, arima, tourist demand

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
bronze