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Modelling dependence between tourism demand and exchange rate using the copula-based GARCH model

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  • Jiechen Tang
  • Songsak Sriboonchitta
  • Vicente Ramos
  • Wing-Keung Wong

Abstract

This paper investigates dependence between tourism demand and exchange rate, using the case of China, and from a new perspective by using copula–GARCH models. The empirical results show that the volatility of exchange rate is not a determinant factor in fluctuation of China's inbound tourism demand from the countries being studied. Furthermore, only Russia exhibits risk-adverse behaviour with extreme SUR depreciation, or CNY appreciation associated with an extreme decline in arrivals. Third, introducing the tail dependence and dynamic dependence between growth rates of tourism demand and exchange rate add much to the explanatory ability of the model. The findings of this study have important implications for destination manager and travel agent as it helps to understand the impact of exchange rates on China inbound tourism demand and provide a complementary academic approach on evaluating the role of exchange rates in the international tourism demand model.

Suggested Citation

  • Jiechen Tang & Songsak Sriboonchitta & Vicente Ramos & Wing-Keung Wong, 2016. "Modelling dependence between tourism demand and exchange rate using the copula-based GARCH model," Current Issues in Tourism, Taylor & Francis Journals, vol. 19(9), pages 876-894, July.
    • Handle: RePEc:taf:rcitxx:v:19:y:2016:i:9:p:876-894
    DOI: 10.1080/13683500.2014.932336
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    Cited by:

    1. Ennadifi Imane & Bisharat Hussain Chang & Tarek Abbas Elsherazy & Wing-Keung Wong & Mohammed Ahmar Uddin, 2023. "The External Exchange Rate Volatility Influence on The Trade Flows: Evidence from Nonlinear ARDL Model," Advances in Decision Sciences, Asia University, Taiwan, vol. 27(2), pages 75-98, June.
    2. Jianxu Liu & Vicente Ramos & Bing Yang & Mengjiao Wang & Songsak Sriboonchitta, 2024. "Analysing the dynamic co-movement between tourism and expected economic growth considering extreme events," Tourism Economics, , vol. 30(1), pages 3-26, February.

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