Modelling the interdependence of tourism demand: The global vector autoregressive approach

Zheng Cao, Gang Li, Haiyan Song

Research output: Contribution to journalArticlepeer-review

Abstract

This study develops a global vector autoregressive (global VAR or GVAR) model to quantify the cross-country co-movements of tourism demand and simulate the impulse responses of shocks to the Chinese economy. The GVAR model overcomes the endogeneity and over-parameterisation issues found in many tourism demand models. The results show the size of co-movements in tourism demand across 24 major countries in different regions. In the event of negative shocks to China’s real income and China’s tourism price variable, almost all of these countries would face fluctuations in their international tourism demand and in their tourism prices in the short run. In the long run, developing countries and China’s neighbouring countries would tend to be more negatively affected than developed countries.
Original languageEnglish
Pages (from-to)1-13
JournalAnnals of Tourism Research
Volume67
Early online date4 Aug 2017
DOIs
Publication statusPublished - 1 Nov 2017

Keywords

  • Tourism demand
  • Co-movement
  • Economic interdependence
  • Global VAR
  • Impulse response

Fingerprint

Dive into the research topics of 'Modelling the interdependence of tourism demand: The global vector autoregressive approach'. Together they form a unique fingerprint.

Cite this