• Energy Research
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The purpose of this study is to examine the relationship between renewable energy sources and economic growth of the South Asian Association for regional cooperation (SAARC) countries. This study uses three main renewable energy sources, namely geothermal, hydro, and wind.This study collects data set from SAARC countries from 1995 to 2018 and applies a fixed effect test and panel vector error correction model (PVECM) for data analysis. The overall results show that all three renewable energy sources have a positive significant impact on economic development among SAARC countries’ economies. Moreover, hydropower renewable energy has more effects and influences on economic growth as compared to the other two individual sources of renewable energy.

The G-7 economies comprise a few of the global, mainly economically developed countries. On the other hand, in conjunction with these high economic development performances, the ecological behaviors in G-7 anions have concurrently provoked to elevate deep apprehensions among the stakeholders. Therefore, the present research aims to empirically investigate the environmental influences of nuclear energy, industrialization, fossil fuel energy, and foreign direct investment (FDI) in the G-7 nations between 1991 and 2018. After checking the cross-sectional dependency, this study employed the first-generation ((full modified ordinary least square (FMOLS), dynamic ordinary least square (DOLS)) and second-generation (Driscoll and Kraay (D-K), feasible generalized least square (FGLS)) approaches for robust and reliable findings. The findings explore that nuclear energy production is ineffective in curbing the figure of ecological footprints in the long-run. Moreover, the industrialization process and fossil fuel energy consumption reduce environmental quality in the G-7 economies. More to the point, the empirical findings recommend that these nations can renovate their industrial production procedures in an eco-friendly behavior they can experience an unsoiled deployment of the energy transition. Similarly, the FDI also degrades environmental eminence in the long-run. This validates the pollution haven hypothesis in the G-7 countries. Based on these results, this study suggests the G-7 nations should reduce the production of nuclear energy levels, the transition from fossil fuels to renewable energy production in the industrial sector, reduce fossil fuel-based foreign investment, and assimilate ecological welfare strategies within their development planning.

This study aims to find the relationship between energy resource dependence and economic growth in consideration of interprovincial heterogeneity. This paper first uses panel data from 14 provinces with rich energy resources in China between 2001 and 2016 as a whole to test the energy resource curse hypothesis. It finds that there is no obvious resource curse from a general perspective. It further makes time prediction and transmission channel analysis based on regressions of each province and classifies them into four groups according to the different degrees of the resource curse. It shows the different roles of resource dependencies in different groups. Twelve provinces are subject to different degrees of the resource curse, among which, six provinces would eventually experience negative economic growth if they increase the degree of resource dependence. Next, this study discusses the mechanism of one particular group, “invisible energy resource curse”, which is when energy resources directly promote but indirectly hinder economic growth. Finally, based on the results, the present study offers policy suggestions according to provinces’ heterogeneous curse levels.

Environmental pollution damages public health and affects economic development. Environmental regulation is the main way for the government to solve environmental pollution. So what type of environmental regulation works better for public health and economic development? Can environmental regulation have an influence on economic development through public health? To solve these problems, this research uses China’s provincial panel data from 2013 to 2017 to divide environmental regulation into command-control policy tools and economic incentive policy tools and uses the mediating effect model to examine the relationship among environmental regulation, public health and economic development. The results show that: (1) There is a positive correlation between economic incentive policy tools and economic development; while no significant relationship between command-control policy tools and economic development is founded; (2) The relationship between command-control policy tools and public health is not significant, while the relationship between economic incentive policy tools and public health is positive; (3) Public health does not play a mediating role between command-control policy tools and economic development but plays a partial mediating role between economic incentive policy tools and economic development. Therefore, the government should strengthen the use of economic incentive policy tools to promote public health and sustainable economic development.

A growing number of countries worldwide have committed to achieving net zero emissions targets by around mid-century since the Paris Agreement. As the world’s greatest carbon emitter and the largest developing economy, China has also set clear targets for carbon peaking by 2030 and carbon neutrality by 2060. Carbon-reduction AI applications promote the green economy. However, there is no comprehensive explanation of how AI affects carbon emissions. Based on panel data for 270 Chinese cities from 2011 to 2017, this study uses the Bartik method to quantify data on manufacturing firms and robots in China and demonstrates the effect of AI on carbon emissions. The results of the study indicate that (1) artificial intelligence has a significant inhibitory effect on carbon emission intensity; (2) the carbon emission reduction effect of AI is more significant in super- and megacities, large cities, and cities with better infrastructure and advanced technology, whereas it is not significant in small and medium cities, and cities with poor infrastructure and low technology level; (3) artificial intelligence reduces carbon emissions through optimizing industrial structure, enhancing information infrastructure, and improving green technology innovation. In order to achieve carbon peaking and carbon neutrality as quickly as possible during economic development, China should make greater efforts to apply AI in production and life, infrastructure construction, energy conservation, and emission reduction, particularly in developed cities.

Fiscal policy is a crucial government tool for influencing and managing the national economy and creating a strong incentive for low carbon investment. Previous literature has reputable evidence that improving fiscal policy enhances environmental quality. However, the literature fails to classify the exact turning level (threshold point) below/above which the association may be negative or positive. In this regard, this research investigates the nexus between fiscal policy, foreign direct investment, financial development, trade openness, urban population, gross capital formation, labour force, and CO2 emissions in the era of globalization. The panel data set contained 105 countries over the period from 1990 to 2016. The empirical findings are estimated through linear and nonlinear panel data approaches such as fully modified ordinary least square and panel threshold regression. The subsequent findings are established: first, fiscal policy and globalization significantly increase environmental pollution. Second, the empirical results confirm the existence of the pollution haven hypothesis (PHV). Third, financial development and gross fixed capital formation are also considered some of the most crucial indicators to increase pollution levels. Fourth, trade openness, urban population, and labour force improve environmental quality. Fifth, panel threshold regression discovers that countries maintain a minimum level of fiscal policy at −1.2889. Based on these empirical findings, this study suggests that policymakers and governments of these countries should take steps to restructure their industrial sector and design macroeconomic-level carbon-free policies to support the implementation of low-energy-intensive and lower carbon production technologies.

The use of renewable energy sources and carbon emissions has been debated from various perspectives throughout recent decades. However, the causal relationship between green energy sources and carbon emissions volatility has received limited attention. This study aims to close a knowledge gap in this area. The current study analyzes the renewable energy sources (wind, hydro, and geothermal) and carbon emissions of four ASEAN countries (Indonesia, Thailand, Vietnam, and the Philippines) between 2000 and 2019. The present study combined Chudik and Pesaran’s (2015) newly developed Dynamic Common Correlated Effects (DCCE) with cutting-edge investigation tools such as first- and second-generation unit root tests; CS-dependence; Variance inflation factor test for multicollinearity; and Pedroni, Kao, and Wester Lund tests of co-integration. The Granger causality test is also used to check the short-term and long-term causal effects within the renewable energy sources and green energy sources, and carbon volatility. According to the empirical results, green energy sources make a positive and vital contribution to reducing carbon emissions growth in the above-noted ASEAN economies. Furthermore, short- and long-run causality runs from green energy sources to carbon emission volatility in the region. A significant causality relationship has also been observed within the green energy sources of ASEAN.