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Economic crises and market performance—A machine learning approach

Author

Listed:
  • José Francisco Perles-Ribes

    (University of Alicante, Spain)

  • Ana Belén Ramón-Rodríguez

    (University of Alicante, Spain)

  • Luis Moreno-Izquierdo

    (University of Alicante, Spain)

  • Martín Sevilla-Jiménez

    (University of Alicante, Spain)

Abstract

This note analyzes the relationship between economic crises and tourism performance in Spain during the period 1970–2013 using machine learning techniques. Specifically, a regression tree is estimated to confirm that, although the dynamics of Spanish tourism performance is influenced by the general variables established by the literature, the crisis periods disrupt the natural functioning of these dynamics, provoking disturbances that affect the tourism market position of destinations to a greater extent than expected. Conversely, to other econometric techniques, machine learning approach allows us to achieve greater flexibility and enriches the information, estimating the interrelations and thresholds operating in this context.

Suggested Citation

  • José Francisco Perles-Ribes & Ana Belén Ramón-Rodríguez & Luis Moreno-Izquierdo & Martín Sevilla-Jiménez, 2017. "Economic crises and market performance—A machine learning approach," Tourism Economics, , vol. 23(3), pages 692-696, May.
  • Handle: RePEc:sae:toueco:v:23:y:2017:i:3:p:692-696
    DOI: 10.5367/te.2015.0536
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    Cited by:

    1. Noelia Araújo-Vila & Jose Antonio Fraiz-Brea & Arthur Filipe Araújo, 2020. "Spanish Economic-Financial Crisis: Social and Academic Interest," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 16(2), pages 135-149, November.

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