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Forecasting tourist arrivals to Turkey

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  • Yılmaz, Engin

Abstract

Modeling and forecasting techniques of the tourist arrivals are many and diverse. Th ere 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. Th ese 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 fi rst 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 diff erent models are developed to forecast the total tourist arrivals to Turkey using monthly data for the period 2002-2013. Th e 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.

Suggested Citation

  • Yılmaz, Engin, 2015. "Forecasting tourist arrivals to Turkey," MPRA Paper 68616, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:68616
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    References listed on IDEAS

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    Cited by:

    1. Nyoni, Thabani, 2021. "Modeling and forecasting international tourism demand in Zimbabwe: a bright future for Zimbabwe's tourism industry," MPRA Paper 110901, University Library of Munich, Germany, revised 01 Dec 2021.
    2. Salim Jibrin Danbatta & Asaf Varol, 2022. "ANN–polynomial–Fourier series modeling and Monte Carlo forecasting of tourism data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 920-932, August.

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    More about this item

    Keywords

    structural time series models; arima; tourist arrivals; tourist demand; Turkey;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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