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Tourism industry and employment generation in emerging seven economies: evidence from novel panel methods

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  • Jinfang Zhao
  • Dongxu Yang
  • Xia Zhao
  • Minghua Lei

Abstract

To analyze E-7 economies, the authors employ panel data and relevant panel data econometrics approaches for long-run relationships Mean group, fully modified and dynamic OLS (MG, FMOLS, DOLS) to monitor changes over time between variables, which is important in actual studies. The models’ primary findings are as follows: The panel cointegration tests confirm log-run associations among the targeted variables. International tourism has the largest influence on creating direct jobs in the tourist industry. The control variables like FDI and TI increase employment opportunities in the targeted economies. Furthermore, the results confirm that total natural resources reduce employment services in the E-7 economies. Other factors that might affect the performance of the tourist activity are not included in the model. Furthermore, given the availability of official and consistent data, it only includes what has been recorded up to 2020; our target was 2022, but due to data limitation, it covers 2020. The objective is to assess both the significance of tourist-related activities in creating jobs and the effect of tourism on country-level factors where public policy may influence economic activity.

Suggested Citation

  • Jinfang Zhao & Dongxu Yang & Xia Zhao & Minghua Lei, 2023. "Tourism industry and employment generation in emerging seven economies: evidence from novel panel methods," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 36(3), pages 2206471-220, December.
    • Handle: RePEc:taf:reroxx:v:36:y:2023:i:3:p:2206471
    DOI: 10.1080/1331677X.2023.2206471
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