A panel data quantile regression analysis of the impact of corruption on tourism

Abstract

Employing a data set of 62 nations over the period of 1998–2011, we adopt the quantile regression model to provide a broad description of the relationship between tourism demand and corruption across the demand distribution. Our results confirm some findings in the literature, and also provide some new conclusions. More specifically, our empirical results indicate that the nonlinear relationship between corruption and tourism demand is only significant at the 50th and 75th quantiles. Moreover, we also find a significant positive relationship between income and tourism demand across various quantiles, and the strength of the relationship is larger at lower demand levels. These findings may suggest that the existing level of demand is as important as other determinants of the tourism demand, and thereby this paper opens up new insights for national tourism administration policy-makers as well as for managerial purposes.

Keywords:

• corruption
• tourism
• quantile regression
• panel data
• heterogeneity

Acknowledgements

This paper benefitted immensely from the contributions of an anonymous reviewer. The authors would like to thank the anonymous reviewer and the editors (Prof. Chris Cooper and Prof. C. Michael Hall) of Current Issues in Tourism for their valuable suggestions. Nevertheless, any shortcomings that remain in this research paper are solely our responsibility.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research is partially supported by the Doctoral Starting up Foundation of Xiangtan University of China [grant number KZ08066], and the Hunan provincial innovation foundation for postgraduate [CX2015B101].