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Modelling structural breaks in the tourism-led growth hypothesis

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  • Nikeel Nishkar Kumar
  • Arvind Patel

Abstract

Structural breaks represent periods of turmoil that may influence how tourism affects economic growth. Current research on the tourism-led growth hypothesis (TLGH) measures the effect of structural breaks using dummy variables in regression models. However, the drawback of this approach is that there could be multiple structural breaks which result in an overfitting problem and reduce degrees of freedom in small samples. It also becomes difficult to isolate the effect of individual breaks when multiple structural breaks occur within the same year. We thus highlight the role of the Fourier ARDL model in addressing these shortcomings. We use three Pacific Island Countries: Fiji, Tonga, and Vanuatu as case studies to evaluate the efficacy of the Fourier ARDL model. Contrary to earlier research, our results indicate that tourism does not always lead to economic growth. Appropriate modelling of structural breaks also influences the outcome of asymmetric effects. These findings imply that future research should pay close attention to the effects of structural breaks in the TLGH.

Suggested Citation

  • Nikeel Nishkar Kumar & Arvind Patel, 2024. "Modelling structural breaks in the tourism-led growth hypothesis," Current Issues in Tourism, Taylor & Francis Journals, vol. 27(5), pages 701-709, March.
    • Handle: RePEc:taf:rcitxx:v:27:y:2024:i:5:p:701-709
    DOI: 10.1080/13683500.2023.2245954
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