Exploring the N-shaped EKC in the top tourist destinations. Empirical evidence from cross-country analysis
Bibliographic Data
Tourism, energy consumption, economic growth, and financial development (FD) have serious consequences on environmental quality, which have gained attention of researchers. This research study attempts to highlight the impact of these variables on carbon dioxide (CO2) emissions in the Asian top-four tourism countries, namely, Thailand, Singapore, Malaysia and Hong Kong. To achieve these objectives, the study applied Fully Modified Ordinary Least Squares (FMOLS) econometric technique to estimate the long-run relationship, using annual data. Moreover, the study also applied the Dumitrescu-Hurlin panel causality test to identify the direction of the causality. The findings of the study show that energy consumption and trade openness have a negative impact on CO2 emissions. Moreover, tourism and FDI affect carbon emissions positively. Moreover, the study also validated the N-shaped environmental Kuznets curve in these countries, indicating that economic growth positively influences carbon emissions in the early stages. However, in the middle stage, economic growth positively affects CO2 emissions, while in the later stage, it affects positively. Further, a unidirectional causality has been found from trade, economic growth and tourist arrivals to FD. Furthermore, based on empirical findings, the study suggests various policy implications for the government of the top-four Asian tourist countries
Causality (physics) · Consumption (sociology) · Econometrics · Economics · Empirical evidence · Empirical research · Energy consumption · Environmental quality · Geography · Granger causality · Greenhouse gas · International economics · Kuznets Curve · Macroeconomics · Openness to experience · Ordinary least squares · Panel data · Political science · Tourism · Energy, Environment, and Transportation Policies · Energy, Environment, Economic Growth · Environmental Sustainability in Business · Psychology
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| Citations per year | 0.5 |
|---|---|
| Citation span | 2024 - 2024 (1) |
| Highly cited | No |