Economic crises and market performance—A machine learning approach

José Francisco Perles-Ribes, Ana Belén Ramón-Rodríguez, Luis Moreno-Izquierdo and Martín Sevilla-Jiménez
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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
Authors registered in the RePEc Author Service: José Francisco Perles Ribes

Tourism Economics, 2017, vol. 23, issue 3, 692-696

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.

Keywords: machine learning; market performance; regression trees; Spain (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:toueco:v:23:y:2017:i:3:p:692-696

DOI: 10.5367/te.2015.0536

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