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Scientific value of econometric tourism demand studies

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  • Gunter, Ulrich
  • Önder, Irem
  • Smeral, Egon

Abstract

The objective of this paper was to evaluate the scientific value of econometric tourism demand studies. Based on a questionnaire answered by ourselves we analyzed articles published in Annals of Tourism Research, Journal of Travel Research, Tourism Management, and Tourism Economics during the period 2007 to 2017. The evaluation showed that current scientific practice generally failed to differentiate between substantive (economic) significance and statistical significance, and used these terms interchangeably in many cases. In line with these flaws, most authors avoided discussing the estimation results in terms of their size and their reliability, as well as failing to adequately address the limitations of their studies and to justify the chosen methods.

Suggested Citation

  • Gunter, Ulrich & Önder, Irem & Smeral, Egon, 2019. "Scientific value of econometric tourism demand studies," Annals of Tourism Research, Elsevier, vol. 78(C), pages 1-1.
    • Handle: RePEc:eee:anture:v:78:y:2019:i:c:13
    DOI: 10.1016/j.annals.2019.06.005
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    Cited by:

    1. Demiralay, Sercan, 2020. "Political uncertainty and the us tourism index returns," Annals of Tourism Research, Elsevier, vol. 84(C).
    2. Li, Cheng & Zheng, Weimin & Ge, Peng, 2022. "Tourism demand forecasting with spatiotemporal features," Annals of Tourism Research, Elsevier, vol. 94(C).
    3. Frank Wogbe Agbola & Tarik Dogru & Ulrich Gunter, 2020. "Tourism Demand: Emerging Theoretical and Empirical Issues," Tourism Economics, , vol. 26(8), pages 1307-1310, December.
    4. José Alberto Martínez-González & Vidina Tais Díaz-Padilla & Eduardo Parra-López, 2021. "Study of the Tourism Competitiveness Model of the World Economic Forum Using Rasch’s Mathematical Model: The Case of Portugal," Sustainability, MDPI, vol. 13(13), pages 1-20, June.
    5. Gunter, Ulrich & Zekan, Bozana, 2021. "Forecasting air passenger numbers with a GVAR model," Annals of Tourism Research, Elsevier, vol. 89(C).
    6. Yuruixian Zhang & Wei Chong Choo & Yuhanis Abdul Aziz & Choy Leong Yee & Jen Sim Ho, 2022. "Go Wild for a While? A Bibliometric Analysis of Two Themes in Tourism Demand Forecasting from 1980 to 2021: Current Status and Development," Data, MDPI, vol. 7(8), pages 1-38, July.
    7. Zhang, Yishuo & Li, Gang & Muskat, Birgit & Law, Rob & Yang, Yating, 2020. "Group pooling for deep tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 82(C).
    8. Ulrich Gunter & Irem Önder & Egon Smeral, 2020. "Are Combined Tourism Forecasts Better at Minimizing Forecasting Errors?," Forecasting, MDPI, vol. 2(3), pages 1-19, June.
    9. Anca-Gabriela Turtureanu & Rodica Pripoaie & Carmen-Mihaela Cretu & Carmen-Gabriela Sirbu & Emanuel Ştefan Marinescu & Laurentiu-Gabriel Talaghir & Florentina Chițu, 2022. "A Projection Approach of Tourist Circulation under Conditions of Uncertainty," Sustainability, MDPI, vol. 14(4), pages 1-21, February.

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