Forecasting tourist arrivals to Turkey

Engin Yilmaz

MPRA Paper from University Library of Munich, Germany

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.

Keywords: structural time series models; arima; tourist arrivals; tourist demand; Turkey (search for similar items in EconPapers)
JEL-codes: C53 (search for similar items in EconPapers)
Date: 2015-12-28
New Economics Papers: this item is included in nep-ara, nep-cwa and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Published in Tourism: An International Interdisciplinary Journal 4.64(2015): pp. 435-445

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:68616

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