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    Energy productivity and environmental degradation in germany: evidence from novel fourier approaches
    (MDPI, 2022) Addai, Kwaku; Ozbay, Rahmi Deniz; Castanho, Rui Alexandre; Genc, Sema Yilmaz; Couto, Gualter; Kirikkaleli, Dervis
    The increased consumption of fossil fuels worldwide has resulted in unprecedented historic environmental degradation and global warming. According to the United Nations, this is both the defining crisis of our time and a race the world could win given the right policy attention. Researchers seek to find critical pathways to provide policy recommendations for reducing environmental degradation. This paper aims to investigate the effect of energy productivity on environmental degradation in Germany while controlling for economic growth, primary energy consumption, and globalization for the period between 1990Q1 and 2019Q4. The outcomes of the Fourier ARDL long-run estimates indicate that (i) both energy productivity and globalization have a negative effect on carbon emissions in Germany, and (ii) both economic growth and primary energy consumption have positive effects on carbon dioxide emissions. These outcomes provide significant policy insights to EU members with respect to reducing their reliance on Russian energy imports amidst the rising energy bills and ongoing geopolitical war with Ukraine while increasing investments to realize their energy turnaround policy objectives.
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    Towards environmental sustainability in china: role of globalization and hydroelectricity consumption
    (MDPI, 2022) Özbay, Rahmi Deniz; Athari, Seyed Alireza; Saliba, Chafic; Kirikkaleli, Dervis
    Countries encounter conflicting policy options in reaching fast development goals due to high resource use, rapid economic expansion, and environmental degradation. Thus, the present research examined the connection between CO2 emissions and urbanization, globalization, hydroelectricity, and economic expansion in China utilizing data spanning the period between 1985 and 2018. The novel quantile-on-quantile (QQ) and quantile regression (QR) approaches were applied to assess this interconnection. The QQ approach is characterized by its ability to incorporate quantile regression fundamentals and non-parametric estimation research. As a result, the method appears to transform the quantile of one parameter into another. The QQ outcomes revealed that in all quantiles (0.1–0.95), gross domestic product (GDP), urbanization, and globalization trigger CO2 emissions in China, while in each quantile (0.1–0.985), hydroelectricity consumption mitigates CO2 emissions. The QR outcomes also affirmed the outcomes of the QQ regression estimates. Policies are suggested based on these findings.