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Predicting tourism demand by A.R.I.M.A. models

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  • Biljana Petrevska

Abstract

The paper provides a short-run estimation of international tourism demand focusing on the case of F.Y.R. Macedonia. For this purpose, the Box–Jenkins methodology is applied and several alternative specifications are tested in the modelling of original time series and international tourist arrivals recorded in the period 1956–2013. Upon the outcomes of standard indicators for accuracy testing, the research identifies the model of A.R.I.M.A.(1,1,1) as most suitable for forecasting. According to the research findings, a 13.9% increase in international tourist arrivals is expected by 2018. The forecasted values of the chosen model can assist in mitigating any potential negative impacts, as well as in the preparation of a tourism development plan for the country.

Suggested Citation

  • Biljana Petrevska, 2017. "Predicting tourism demand by A.R.I.M.A. models," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 30(1), pages 939-950, January.
    • Handle: RePEc:taf:reroxx:v:30:y:2017:i:1:p:939-950
    DOI: 10.1080/1331677X.2017.1314822
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    Cited by:

    1. İhsan Erdem Kayral & Tuğba Sarı & Nisa Şansel Tandoğan Aktepe, 2023. "Forecasting the Tourist Arrival Volumes and Tourism Income with Combined ANN Architecture in the Post COVID-19 Period: The Case of Turkey," Sustainability, MDPI, vol. 15(22), pages 1-20, November.
    2. Musara Chipumuro & Delson Chikobvu & Tendai Makoni, 2024. "Statistical Analysis of Overseas Tourist Arrivals to South Africa in Assessing the Impact of COVID-19 on Sustainable Development," Sustainability, MDPI, vol. 16(13), pages 1-17, July.

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