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A nonparametric panel data model for examining the contribution of tourism to economic growth

Ergun Dogan and Xibin Zhang

Economic Modelling, 2023, vol. 128, issue C

Abstract: We apply a nonparametric panel data model with cross-sectional and time-varying coefficients to examine the relationship between tourist arrivals and economic growth in the Schengen area from 1995 to 2019. In contrast to the parametric models employed in other studies, our nonparametric model makes no assumption about functional form and, hence, allows us to model the relationship nonlinearly. We find that the tourism–economic growth relationship in the Schengen area is nonlinear and time-varying. While the relationship between tourism and economic growth was positive and significant during 1995–2003, it was negative and significant during the Global Financial Crisis (2007–2008) and the European recession of 2012–2013. One additional contribution of the study is the finding that total factor productivity (TFP) has been growing at 1.45% per year. The results also show that country-level TFP growth was disrupted during the aforementioned negative economic shocks.

Keywords: Eurozone crisis; Global Financial Crisis; Nonparametric estimation; Time-varying panel data model; Total factor productivity; Tourism-led economic growth hypothesis (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1016/j.econmod.2023.106487

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