Analyzing the Asymmetric Effect of Renewable Energy Consumption on Environment in STIRPAT-Kaya-EKC Framework: A NARDL Approach for China

A revisit to the relationship between geothermal energy growth and underground water quality in EU economies

This study's main goal is to evaluate how the research will look at the impact of geothermal energy production on the quality of the subterranean in the 27 European nations from 1990 to 2021. A considerable decline in the subterranean water supply can occur in EU14 emerging nations employing geothermal energy growth compared to EU13 emerging economies, according to research that uses the autoregressive distributed lag (ARDL). Fossil fuel use, population growth, and economic expansion are some factors that have a more detrimental effect on the subterranean water supply in EU14 emerging economies than in EU13 emerging nations. In contrast, the study's findings indicate that EU13 emerging nations may be better able to enhance their underground water supply than EU14 emerging economies because of more effective institutional qualities. The findings so indicate that increasing the amount of geothermal energy generation among the 27 European Union countries can accelerate subsurface water degradation at a high capacity and help achieve unionism's 2030 energy-related goals. When this is achieved, climate change will be put to check, as pollution of the environment. All calculations projected were seen to be of a good level of validity, and this is ascertained through three estimators considered in this study.

Evaluating a pathway for environmental sustainability: the role of energy mix and research and development in European countries

Within the European Union (EU), the majority of countries are considered developed, and the level of economic activity is rising. As a result, carbon dioxide emissions have increased. If the European Union wants to maintain long-term, sustainable growth, it must act quickly to find solutions to pollution. Population, wealth, renewable energy, nuclear energy, and research and development (R&D) are all factored into the STIRPAT model to determine their respective environmental impacts. Slope heterogeneity and cross-sectional dependence are explored in panel data for 30 European nations from 1990 to 2021 using a newly developed Cross Section Autoregressive Distributed Lag (CS-ARDL) method. The study found that population growth and the continued use of fossil fuels are major causes of environmental degradation. Alternately, employing renewable and raising incomes both have the potential to significantly cut pollution over the long run. Likewise, investments in R&D assist lessen the damage done to the environment. The nuclear energy coefficients, however, are insignificant. However, fossil fuels have negative effects on the ecosystem. If the EU wishes to stop the degradation of the environment, the analysis demonstrates that renewable energy is the best way to do it. The time has come for the EU to make a gradual transition away from fossil fuels and toward more environmentally friendly alternatives. Economic growth should be matched by decreased CO2 emissions, and increasing investment in R&D can serve as a catalyst for environmental sustainability. The results were reviewed using three different estimators: the augmented mean group (AMG), the mean group (MG), and the common correlated effects mean group (CCEMG). Important policy recommendations for a sustainable European environment are also suggested by the research.

Impact of technology on the relation between disaggregated energy consumption and CO2 emission in populous countries of Asia

All around the world, but particularly in developing nations, carbon dioxide emissions are on the rise, and climate change and global warming are brought on by an increase in CO₂ emissions. This article provides an overview of the technological effect on energy consumption in the residential, transport, and industrial sector and its ultimate effect on the environment. Using the STIRPAT-Kaya-EKC model for the years 1990 to 2020, this study looked at the threshold impact of technological advancements on the link between disaggregated energy use and CO₂ emissions for a panel of 10 Asian countries using the panel threshold regression. Findings demonstrate that the EKC phenomenon is present in the chosen Asian region. Findings also suggest that technology has a threshold influence on the relationship between energy use and carbon emissions; however, this effect varies across sectors.

Environmental sustainability through aggregate demand and knowledge economy interaction-a case of very high-HDI countries

The magnitude of the economic activities is immense in very high-Human Development Index (HDI) countries, leading to environmental degradation, a crucial problem. This study is aimed at testing aggregate demand's role in the environmental Kuznets curve (EKC) perspective and explores the role of four pillars of the knowledge economy, viz., technology, innovations, education, and institutions, as proposed by World Bank, in maintaining sustainable development of environmental quality in these countries. The analysis covers the period ranging from 1995 to 2022. The departure of normality of the variables provides a solid base for panel quantile regression (PQR). Unlike ordinary least squares (OLS) regression, which estimates the conditional mean of the dependent variable, PQR estimates the conditional quantiles. The estimated results using PQR confirm both U and inverted U-shaped aggregate demand-based EKC. In fact, these knowledge pillars in the model determine the shape of EKC. Results also reveal that two knowledge pillars, i.e., technology and innovations, are responsible for significantly reducing carbon emissions. In comparison, education and institutions are responsible for expanding carbon emissions. As a moderator, all knowledge pillars except institutions are shifting the EKC downward. The key lessons from these findings are that technology and innovation can reduce carbon emissions, while education and institutions may have a mixed impact. The relationship between knowledge pillars and emissions may be moderated by other factors, underscoring the need for further research. Moreover, urbanization, energy intensity, financial development, and trade openness significantly contribute to environmental deterioration.

Investigating the nexus between trade policy uncertainty and environmental quality in the USA: empirical evidence from aggregate and disaggregate level analysis

Worldwide, environmental sustainability is a hot topic, particularly in industrialized countries due to their higher emission intensity. Environmental conservation and equitable economic growth have been prioritized in economic debate and policy development. Over the past three decades, the USA's emissions of carbon dioxide (CO₂e) have risen exponentially, as trade policy uncertainty (TPU). In this circumstance, this paper aims to contribute to the existing literature by exploring the effect of TPU on environmental quality by controlling the energy consumption, economic growth, and population in the USA over the period 1985M1 to 2022M3 employing the augmented ARDL and NARDL procedures in the presence of structural breaks. From our analysis, the results revealed that TPU affects negatively CO₂e in the residential sector, and negative changes in TPU positively affect CO₂e in the commercial sector both in the long and short run. On the other side, the outcomes show that energy consumption is a crucial key determinant factor in environmental degradation at the aggregate level and in all sectors. Furthermore, our findings clarify that economic growth upsurges the CO₂e at the aggregate level precisely in the industrial and residential sectors. Juxtaposing, in the long run, the results indicate that population growth could make additional pressure on environmental quality at the aggregate level, especially in commercial, power generation, and residential sectors. Accordingly, it is clear from our results that the regulations put in place to encourage Americans to buy locally created goods instead of those imported, especially in light of the high levels of TPU, maybe the best option to decrease the long-term impact of international trade on the environment to achieve sustainable development goals (SDGs).

Nexus of renewable energy, green financing, and sustainable development goals: an empirical investigation

Achieving the sustainable development goals (SDG) agenda, proposed by the United Nations by 2030, has become the main concern around the globe. The continuing ecological crises and energy sustainability issues can only be dealt with using sustainable solutions such as green finance. Green finance has become a pioneer in economic green transformation resulting in the collective development of both the economy and the environment. Therefore, this study aims to examine the influence of green finance on the achievement of the five major sustainable development goals in the context of the economy of Pakistan. The renewable energy scheme proposed by the State Bank of Pakistan in 2016 serves as a basis for this study. We innovate our research by studying the impact of green finance on five SDGs simultaneously. The association between the variables is checked using random effect modeling. The findings reveal that green finance supports SDG 3, 12, and 13 while having little effect on SDG 1 and SDG 2. Moreover, green finance is a suitable reform for the sustainable development of the economy and the environment. The study has robust policy implications for Pakistan.

Ensuring environmental inclusion in developing countries: the role of macroeconomic policies

In every society, there exist disadvantaged groups who have failed constantly to take part in the development of the economy and reap the benefits of economic growth as well. Along with economic and social factors, environmental factors are also accountable in making inclusion a challenge for the marginalized group. Contaminated drinking water, inappropriate sanitation systems, and pollution are the factors that affect health and wellbeing of the poor class by affecting their productivity. Thus, the lack of a clean environment leads the poor section towards further poverty and income inequality. Since the 2030 Agenda for Sustainable Development emphasizes three components to achieve sustainable development, namely economic, social, and environmental, this study inspects the role of macroeconomic policies in ensuring an inclusive clean environment in developing countries. Moreover, it considers the composite effect of fiscal policy and monetary policy on environmental inclusion by including interactive terms. This investigation uses FE-2SLS on a panel of 51 developing countries for the period of 1995-2019 to analyse the impact of macroeconomic policies on environmental inclusion. The study provides empirical evidence that fiscal and monetary policy has the potential to ensure an inclusive clean environment in developing countries. The findings imply that the macroeconomic policy actions depend on each other. Furthermore, governments in developing regions are required to cut nondeveloping expenditures and use expansionary monetary policy to promote green growth.

Do all renewable energy stocks react to the war in Ukraine? Russo-Ukrainian conflict perspective

This study investigates how renewable energy markets reacted to the war in Ukraine in 2022 using event study and network connectedness analyses and compares this effect to traditional energy sources. Combining event study with connectedness analysis is of great interest in identifying abnormal returns from the Russia-Ukraine conflict event. The risk-return profiles make clean energy more appealing to investors, and increased investment in clean energy subsectors leads to improved climate change mitigation. Sampled data are wrangled daily from 03 August 2021 to 30 March 2022. The results confirm that renewable energy markets have positive and significant cumulative abnormalities while traditional energy markets are heavily affected during the post-war. Moreover, we find higher pairwise return connectedness after the announcement event than during and before the war in Ukraine. The geothermal and full cell markets are the more robust net information transmitter to other clean energy subsectors. Finally, renewable energy appeared more pertinent during and after the Russian invasion of Ukraine, given its properties to serve diversifications and hedging tools.

Investigating the nexus between carbonization and industrialization under Kaya's identity: findings from novel multivariate quantile on quantile regression approach

Developing nations aim to industrialize and grow sustainably often ignoring the environmental consequences. However, few empirical studies have looked at the influence of industrialization-driven economic transition on carbon footprint in developing nations using a non-parametric approach. In this milieu, on the ground of Kaya's identity and the novel multivariate quantile-on-quantile regression (QQR) (extension of Sim and Zhou's (2015) bivariate QQR model), the present research studies the impact of industrial value-added (IGVA), population, energy intensity, and carbon intensity on CO₂ emissions in India. This study is one of the first in the literature to evaluate the industrialization-carbonization nexus in the context of Kaya's identity for the Indian economy utilizing an innovative multivariate QQR approach, which makes a methodological and empirical addition to the literature. The outcomes of the multivariate QQR technique demonstrate that economic and environmental development requires continual long-run strategies. The empirical findings revealed that there is no authentication that India's carbon emissions increased due to its industrialization, which exhibited that IGVA has a negative and significant connection with CO₂ emissions. In some quantiles, population size positively impacts CO₂ emissions. On the other hand, carbonization in the Indian economy is asymmetrically affected by GDP per capita and energy and carbon intensity. The quantile Granger causality study further supported the aforementioned results. The current analysis also offers policy suggestions for environmentally friendly sustainable economic growth and to achieve the sustainable development goals (SDGs) of India.

Human Capital, Trade Competitiveness and Environmental Efficiency Convergence Across Asia Pacific Countries

This study mainly investigates 14 Asia Pacific economies' environmental efficiency. Departing from previous studies ignoring environmental technology heterogeneity, we evaluate environmental efficiency through metafrontier super epsilon based model (EBM). We compare environmental efficiency convergence across different regions via unit root test and truncated regressions. We analyze how trade competitiveness impact environmental efficiency. We also explore effect of green technology and human capital on environmental efficiency from the perspective of endogenous growth. Our findings indicate that stochastic and absolute β-convergence tendencies were confirmed. Human capital can enhance environmental efficiency convergence. Trade competitiveness showed a mixed impact on environmental efficiency convergence, confirming scale, composition and technical effects. It is better to enhance human capital, strengthening environmental regulations under international competition as well as relentlessly pursuing green industrialization across Asia Pacific countries.