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Spatial Effects of Energy Consumption and Green GDP in Regional Agreements

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  • Mahnaz Kalantaripor

    (Agricultural Economics Department, Tarbiat Modares University, Tehran 14115-336, Iran)

  • Hamed Najafi Alamdarlo

    (Agricultural Economics Department, Tarbiat Modares University, Tehran 14115-336, Iran)

Abstract

One of the main factors in environmental degradation and climate change is the consumption of fossil fuels. For this reason, cooperation between countries to overcome environmental challenges is seen more than ever. In this regard, regional economic treaties are a good platform for advancing common policies in the development of renewable energy, because this type of energy has fewer external effects on the environment. Accordingly, the purpose of this paper is to investigate the spatial effects of energy consumption and green production in Shanghai Cooperation Organization member states. For this purpose, the spatial panel data econometric approach has been used. Spatial effects refer to the effects of neighboring countries. According to CO 2 emissions, the spatial effects of the positive or negative effects of these emissions and other determinants of neighboring countries are local. The results show that although both fossil fuels and renewable energy have a negative effect on green GDP, the impact of fossil fuels is almost four times greater. On the other hand, proximity and membership in the Shanghai Cooperation Organization have had a positive effect on green GDP in member countries, as countries have tried to coordinate their development policies in the field of renewable energy. Therefore, the development and strengthening of regional cooperation can play an effective role in controlling pollution caused by fossil fuel consumption and ultimately improve green production.

Suggested Citation

  • Mahnaz Kalantaripor & Hamed Najafi Alamdarlo, 2021. "Spatial Effects of Energy Consumption and Green GDP in Regional Agreements," Sustainability, MDPI, vol. 13(18), pages 1-14, September.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:18:p:10078-:d:631778
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    2. Qingwen Li & Guangxi Yan & Chengming Yu, 2022. "A Novel Multi-Factor Three-Step Feature Selection and Deep Learning Framework for Regional GDP Prediction: Evidence from China," Sustainability, MDPI, vol. 14(8), pages 1-21, April.
    3. Saša Stjepanoviæ & Daniel Tomiæ & Marinko Škare, 2022. "A new database on Green GDP; 1970–2019: a framework for assessing the green economy," Oeconomia Copernicana, Institute of Economic Research, vol. 13(4), pages 949-975, December.
    4. Siba Sankar Mohanty & Himanshu Mallik, 2022. "Discounting GDP for Pollution, Waste Generation and Natural Resources Depletion: A Comparative Analysis of selected High, Middle and Low income countries," Journal of Studies in Dynamics and Change (JSDC), ISSN: 2348-7038, Voices of Inclusive Change and Expressions- (VOICE) Trust, Dehradun, Uttarakhand, vol. 9(4), pages 13-27, October-D.
    5. Aleksy Kwilinski & Oleksii Lyulyov & Tetyana Pimonenko, 2023. "Greenfield Investment as a Catalyst of Green Economic Growth," Energies, MDPI, vol. 16(5), pages 1-16, March.

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