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Renewable energy and transitioning towards sustainable tourism: Inferences from kernel density and nonparametric approach

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  • Sofi, Arfat Ahmad
  • Bhat, Mohammad Younus
  • Ahmad, Laraib
  • Aara, Ruhi Refath
  • Aswani, RS

Abstract

This study considered a panel of twenty countries characterized by tourist glut to investigate the role of renewable energy towards sustainable tourism transition. We used a nonparametric kernel density approach to facilitate the analysis and examine the distributional dynamics; besides, using a nonparametric quantile regression approach to trace nexus through different strata. Kernel density estimates reflect multimodality character across the countries. Quantile estimates reveal the negative impact of economic growth on carbon emissions across all quantiles. The coefficient of the international tourist arrival is positive and significant in lower quantiles; nevertheless, it turns out to be negative at higher quantiles implying tourist arrivals reduce carbon emissions. Non-renewable energy consumption positively affects carbon emissions but negatively impacts international tourist arrivals. On the other hand, renewable energy consumption negatively affects carbon emissions but affects the international tourist arrivals positively. This study intends to guide policymakers to hold back fossil fuel dependence for sustainable tourism.

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  • Sofi, Arfat Ahmad & Bhat, Mohammad Younus & Ahmad, Laraib & Aara, Ruhi Refath & Aswani, RS, 2022. "Renewable energy and transitioning towards sustainable tourism: Inferences from kernel density and nonparametric approach," Renewable Energy, Elsevier, vol. 193(C), pages 963-975.
    • Handle: RePEc:eee:renene:v:193:y:2022:i:c:p:963-975
    DOI: 10.1016/j.renene.2022.04.132
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