Analyzing the Impact of High-Speed Rail on Tourism with Parametric and Non-Parametric Methods: The Case Study of China

Francesca Pagliara, Filomena Mauriello and Yin Ping
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Francesca Pagliara: Department of Civil, Architectural and Environmental Engineering, University of Naples Federico II, 80125 Napoli, Italy
Filomena Mauriello: Department of Civil, Architectural and Environmental Engineering, University of Naples Federico II, 80125 Napoli, Italy
Yin Ping: Department of Tourism Management, School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China

Sustainability, 2021, vol. 13, issue 6, 1-10

Abstract: High-speed rail (HSR) and tourism are closely related activities since improved mobility is perceived to facilitate tourist behavioral changes. The interest in research is very high and this contribution tries to provide an insight into this topic by making a comparison between the estimation of the parametric Generalized Estimating Equation (GEE) approaches with the non-parametric Classification and Regression Tree (CART). A dataset containing information both on tourism and transport for thirty Chinese provinces, during the 2001–2017 period, has been collected. The finding of this paper shows that the presence of HSR has value in the explanation of tourist arrivals.

Keywords: high-speed rail; tourism market; generalized estimating equation; classification and regression tree; Chinese provinces (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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