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Forecasting Daily Air Arrivals in Mallorca Island Using Nearest Neighbour Methods

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  • Marcos álvarez Díaz

    (Department of Economics, University of Vigo, Cidade Universitaria Lagoas-Marcosende s/n, 36310 Vigo, Spain)

  • Josep Mateu-Sbert

    (Directorate General of Evaluation and Accreditation, Government of the Balearic Islands, Spain)

Abstract

This paper investigates the feasibility of using different generalizations of the nearest neighbour method in a tourism forecasting problem. The method is widely employed in different fields of research but, inexplicably, it is practically unknown in tourism forecasting. The analysis is centred not only in knowing the exact value of arrivals (point prediction), but also in anticipating the direction of the sign movement (sign prediction). Furthermore, this study also offers further evidence on a subject scarcely treated in tourism economics: the searching of predictable non-linear dynamics. The results encourage the use of this technique and reveal the existence of a non-linear seasonal effect in the analysed tourism time series.

Suggested Citation

  • Marcos álvarez Díaz & Josep Mateu-Sbert, 2011. "Forecasting Daily Air Arrivals in Mallorca Island Using Nearest Neighbour Methods," Tourism Economics, , vol. 17(1), pages 191-208, February.
    • Handle: RePEc:sae:toueco:v:17:y:2011:i:1:p:191-208
    DOI: 10.5367/te.2011.0022
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    References listed on IDEAS

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    1. Teresa Aparicio & Eduardo Pozo & Dulce Saura, 2002. "The nearest neighbour method as a test for detecting complex dynamics in financial series. An empirical application," Applied Financial Economics, Taylor & Francis Journals, vol. 12(7), pages 517-525.
    2. Richard A. Meese & Andrew K. Rose, 1991. "An Empirical Assessment of Non-Linearities in Models of Exchange Rate Determination," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 603-619.
    3. Donaldson, R Glen & Kamstra, Mark, 1996. "A New Dividend Forecasting Procedure That Rejects Bubbles in Asset Prices: The Case of 1929's Stock Crash," The Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 333-383.
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    Cited by:

    1. Rice, William L. & Park, So Young & Pan, Bing & Newman, Peter, 2019. "Forecasting campground demand in US national parks," Annals of Tourism Research, Elsevier, vol. 75(C), pages 424-438.
    2. Zheng, Weimin & Huang, Liyao & Lin, Zhibin, 2021. "Multi-attraction, hourly tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 90(C).
    3. Eden Xiaoying Jiao & Jason Li Chen, 2019. "Tourism forecasting: A review of methodological developments over the last decade," Tourism Economics, , vol. 25(3), pages 469-492, May.

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