Renewable Energy, Urbanization, and CO2 Emissions: A Global Test

The impact of agriculture production and renewable energy consumption on CO2 emissions in developing countries: the role of governance

Environmental pollution has aggravated the climate change issues posing unusual challenges to the survival and growth of humanity, including extreme weather, loss of species, and sustainability of the ecosystem in developing countries. Unlike previous studies, this paper adds new dimension to the literature by incorporating corruption into agriculture production-environment nexus. This study adds new dimension to the literature by examining corruption, agriculture, and renewable energy on CO2 emissions. The study therefore examines the effects of governance (corruption) and agriculture production on CO2 emissions in 20 countries in Africa from 1990 to 2019. The study employed recent panel econometric approach which accounts for cross-sectional dependence in the variables. The findings of the fixed effect model and panel dynamic ordinary least squares (PDOLS) show that forest and renewable energy consumption decrease CO2 emissions. However, corruption, agriculture production, export, and urbanization escalate CO2 emissions in African countries covered in the paper. Moreover, the Dumitrescu-Hurlin Granger causality indicates a bidirectional causality between agriculture production and CO2 emissions, renewable energy use, agricultural output, and forest. Also, unidirectional Granger causality runs from corruption to forest and agriculture production. On these premises, consented efforts by governments should be made to support good institutions in order to promote good governance to avert pervasive consequences of corruption on the environment.

Asymmetrical analysis of economic complexity and economic freedom on environment in South Asia: A NARDL approach

The environment has become a growing concern for many countries, as pollution and other environmental degradation can harm human health, economic growth, and overall well-being. This paper probes into the asymmetrical implications of economic complexity and freedom on ecological quality in four South Asian countries from 1995 to 2019. Using Nonlinear Autoregressive Distributed Lag methodology approach, our findings indicate that carbon dioxide (CO2) emissions are intensified by economic freedom both in the long and short term, while negative and positive shocks to economic complexity increase CO2 emissions in the long term. However, a negative economic complexity shock increases CO2 emissions, whereas a positive shock has the opposite effect in the short run. Moreover, our results confirm the validity of the environmental Kuznets curve (EKC) hypothesis in the long run. Furthermore, we find that renewable energy usage and the interaction of FDI and renewable energy usage can help reduce environmental damage in both the short and long run. The findings suggest that countries should focus on attracting foreign direct investment that promotes the use of renewable energy. Additionally, policies aimed at encouraging renewable energy use should be implemented. It is important to note that as economic freedom and complexity increase, there is a corresponding increase in CO2 emissions. Therefore, South Asian policy makers are advised to prioritize the reduction in fossil fuels, the promotion of energy-saving technologies and efficient production, and trade that encourages the transition of renewable energy sources to reduce CO2 emissions.

Social, economic, and technical factors affecting CO2 emissions in Iran

Most scholars support the increase in carbon dioxide (CO2) emissions as one of the major causes of the increase in global climate change. Therefore, reducing CO2 emissions from the main emitter countries, including Iran as the sixth emitter, is important to deal with the harmful effects of global climate change. Accordingly, the main aim of this paper was to analyze the social, economic, and technical factors affecting CO2 emissions in Iran. Previous studies on diverse variables affecting emissions are not very accurate and reliable as they do not consider indirect effects. This study applied a structural equation model (SEM) to estimate the direct and indirect impacts of factors on the emissions by panel data for 28 provinces of Iran from 2003 to 2019. According to geographical location, three distinct regions, the north, center, and south of Iran were considered. The findings suggest that a 1% increase in social factor directly increased CO2 emissions by 2.23% (in the north) and 1.58% (in the center), but indirectly reduced emissions by 0.41% (in the north) and 0.92% (in the center). Hence, the total effects of the social factor on CO2 emissions were estimated at 1.82%, and 0.66% in the northern, and central regions, respectively. In addition, the total effects of the economic factor on CO2 emissions were estimated at 1.52%, and 0.73% in those regions. The results of this study showed that the direct effects of a technical factor on CO2 emissions were negative in the north and center. However, they were positive in the south of Iran. Based on the empirical results of this study, three policy implications are discussed in order to control CO2 emissions in regional distinctions of Iran as follows: First, policymakers should pay attention to the social factor, i.e., the growth of human capital in the southern region with the aim of increasing sustainable development. Second, Iranian policymakers must prevent unilaterally increasing gross domestic product (GDP) and financial development in the north and center. Third, policymakers should pay attention to the technical factor, i.e., improving energy efficiency, as well as upgrading information and communications technology (ICT) in the northern and central regions, and limiting the technical factor in the southern region.

The effect of institutions and urbanization on environmental quality: evidence from the Belt and Road Initiative countries using dynamic panel models

Increased globalization in urban areas raise energy consumption that leads to high carbon dioxide discharge and degrade environmental quality. Other economic activities also produce emission; however, a well-established institutional framework can overcome the issues of environmental degradation and minimize the effect of harmful factors on the environment. In this regard, this study investigates the effect of urbanization, energy consumption, and industrialization on carbon dioxide emission by taking into consideration the role of institutional quality in the Belt and Road Initiative (BRI) countries for the period of 2002 to 2019. Employing dynamic panel techniques, the results are in line with theories which show that increased urbanization, energy consumption, industrialization, and economic growth raise carbon dioxide emission and lead to environmental degradation. The study also found that international trade and political stability reduce emission; however, institutional quality as a whole positively affects carbon dioxide emission. The study also found a U-shape relationship between urbanization and carbon dioxide emission. The interaction term between institutional quality and urbanization significantly mitigates carbon dioxide emission and raise environmental sustainability. The findings of this study have considerable policy suggestions for the sample countries.

The driving influence of multidimensional urbanization on green total factor productivity in China: evidence from spatiotemporal analysis

China is experiencing a swift transformation from a rural to an urban society. This societal transition is the result of a country's ambition toward economic development. Rapid urbanization impacts on human wellbeing, environment, and infrastructure. Unlike many cases of urban extension, China's urbanization has led to increase in environmental issues, rather than to contain, and posed serious challenges to achieve sustainable development. To date, nevertheless, there is a little empirical enquiry on the spatiotemporal effects of multidimensional urbanization on green total factor productivity. Taking this into account, this article constructs a spatial panel data model based on 283 Chinese cities during 2006-2019. The results showed that the three types of urbanization (i.e., population, land, and economic) have positive effect on green total factor productivity (GTFP). Population urbanization has indirect positive effect on GTFP. Local land urbanization inhibits while surrounding land urbanization promotes GTFP. Economic urbanization has positive direct effect on GTFP. Considering regional heterogeneity, population and economic urbanization have positive effect on GTFP in eastern region. In central region, land urbanization significantly promotes GTFP, while economic urbanization has significant negative effect on GTFP. In the western region, the three types of urbanization are not conducive to GTFP. Considering sized heterogeneity, population and economic types of urbanization have significant negative effect on GTFP in small- and medium-sized cities. In large cities, the three types of urbanization have significant positive effects on GTFP. Considering temporal heterogeneity, the three types of urbanization significantly promote GTFP before 2014, but economic urbanization deteriorates GTFP after 2014. Our results recommend loosening Hukou system, improving land use efficiency, and developing technology and knowledge-intensive industries.