Examined EKC Hypothesis in the Presence of Renewable & Nonrenewable Energy and Trade & Financial Developments for Pakistan

Main Article Content

Anam Aziz
Salah ud Din

Abstract

Most of the existing literature uses energy consumption to verify the effect of energy use on environmental degradation, but they fail to explore it. To achieve the revealed gap, the present study insists on the impact of the nonrenewable and renewable energy consumptions, financial development, trade liberalization & income on carbon dioxide (CO2) by using the environmental Kuznets curve theory. This study used Pakistan’s time series data for the time period of 1990 to 2018. This study used two famous unit root tests which are the Augmented Dickey-Fuller (ADF) and Phillips Perron (PP) test. Results confirm that RENERG has stationary at the level and NRENERG, CO2, GDP, GDP2, FINDEV, and TRD become stationary at first difference. Furthermore, ARDL bound test is used to analyze the model, the bound test indicates that there exists co-integration in the model and ARDL estimates the short and long-run estimates of the equation. The rise in renewable energy consumptions, economic developments, and trade openness reduces emanation of the carbon whereas the increase in renewable-energy consumption hints at carbon releases it also validates the EKC hypothesis in Pakistan. The study concludes that Pakistan’s government and regulatory authorities should initiate the programs by which they are aware of the public and citizens about the adoption of renewable energies and environmental protection levels.

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How to Cite
Aziz, A. ., & Din, S. ud . (2020). Examined EKC Hypothesis in the Presence of Renewable & Nonrenewable Energy and Trade & Financial Developments for Pakistan. IRASD Journal of Energy & Environment, 1(1), 14–25. https://doi.org/10.52131/jee.2020.0101.0002
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Articles
Author Biographies

Anam Aziz, The Islamia University of Bahawalpur, Pakistan

Department of Economics

Salah ud Din, Pakistan Institute of Development Economics, Islamabad, Pakistan

Department of Econometrics and Statistics