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A dynamic multidimensional Granger causality based on wavelet decomposition analysis of the tourism and economic growth in China

  • Hung Che Wu
  • , Tsung Pao Wu
  • , Shu Bing Liu
  • , Chien Ming Wang
  • , Yi Zheng*
  • , Shaodian Chu
  • , Ananda Sabil Hussein
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This study employs an innovative multimodal approach, integrating Granger causality analysis with wavelet decomposition, to explore the intricate relationship between China’s tourism sector and its economic development spanning from 1995 to 2022. The primary aim is to uncover the causal dynamics between the advancement of tourism and the expansion of the economy across various temporal scopes and dimensions. Through rigorous panel bootstrap causality examinations and meticulous assessments for cross-sectional dependence and slope homogeneity, this research underscores a dynamic and symbiotic connection between China’s economic progress and the growth of its tourism industry, particularly emphasising the enduring significance of this relationship over the short-run, mid-run, and long-run.

Original languageEnglish
JournalCurrent Issues in Tourism
DOIs
Publication statusAccepted/In press - 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  2. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • bootstrap panel Granger causality
  • economic growth
  • International tourism
  • wavelet decomposition

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