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Cross country relations in European tourist arrivals

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  • Silva, Emmanuel Sirimal
  • Ghodsi, Zara
  • Ghodsi, Mansi
  • Heravi, Saeed
  • Hassani, Hossein

Abstract

This paper introduces an optimized Multivariate Singular Spectrum Analysis (MSS) algorithm for identifying leading indicators. Exploiting European tourist arrivals data, we analyse cross country relations for European tourism demand. Cross country relations have the potential to aid in planning and resource allocations for future tourism demand by taking into consideration the variation in tourist arrivals across other countries in Europe. Our findings indicate with statistically significant evidence that there exists cross country relations between European tourist arrivals which can help in improving the predictive accuracy of tourism demand. We also find that MSSA has the capability of not only identifying leading indicators, but also forecasting tourism demand with far better accuracy in comparison to its univariate counterpart, Singular Spectrum Analysis.

Suggested Citation

  • Silva, Emmanuel Sirimal & Ghodsi, Zara & Ghodsi, Mansi & Heravi, Saeed & Hassani, Hossein, 2017. "Cross country relations in European tourist arrivals," Annals of Tourism Research, Elsevier, vol. 63(C), pages 151-168.
    • Handle: RePEc:eee:anture:v:63:y:2017:i:c:p:151-168
    DOI: 10.1016/j.annals.2017.01.012
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    Cited by:

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    2. Mahdi Kalantari & Hossein Hassani, 2019. "Automatic Grouping in Singular Spectrum Analysis," Forecasting, MDPI, vol. 1(1), pages 1-16, October.
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    4. Hassani, Hossein & Rua, António & Silva, Emmanuel Sirimal & Thomakos, Dimitrios, 2019. "Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1263-1272.
    5. Hassani, Hossein & Silva, Emmanuel Sirimal, 2018. "Forecasting UK consumer price inflation using inflation forecasts," Research in Economics, Elsevier, vol. 72(3), pages 367-378.
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    7. Guan, Bo & Silva, Emmanuel Sirimal & Hassani, Hossein & Heravi, Saeed, 2022. "Forecasting tourism growth with State-Dependent Models," Annals of Tourism Research, Elsevier, vol. 94(C).
    8. Mitra, Subrata Kumar & Chattopadhyay, Manojit & Jana, R.K., 2019. "Spillover analysis of tourist movements within Europe," Annals of Tourism Research, Elsevier, vol. 79(C).
    9. Hatice Oncel Cekim & Coşkun Okan Güney & Özdemir Şentürk & Gamze Özel & Kürşad Özkan, 2021. "A novel approach for predicting burned forest area," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(2), pages 2187-2201, January.
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