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While science has researched the impact of air pollution on human health, the economic dimension of it has been less researched so far. Renewable energy consumption is an important factor in determining the level of life expectancy and reducing health expenditure. Thus, this study aims to investigate the impact of renewable energy, carbon emissions, health expenditure and urbanization on life expectancy in G-7 countries over the period of 2000–2019.

This study has adopted a novel Method of Moments Quantile Regression (MMQR). Furthermore, as a robustness check for MMQR, the fully modified ordinary least square, dynamic ordinary least squares and fixed effect ordinary least square estimators have been used.

The results indicated that renewable energy consumption, health expenditure and urbanization lead to an increase in life expectancy across all quantiles (5th to 95th), whereas higher carbon dioxide emissions reduce life expectancy at birth across all the quantiles (5th to 95th).

The empirical findings conclude that governments should recognize their potential in renewable energy sources and devise policies such as tax-related regulations, or relevant incentives to encourage further investments in this field.

This paper in comparison to the other research studies used MMQR to investigate the impact of factors affecting life expectancy. Also, to the best of the authors’ knowledge, so far no study has investigated the impact of renewable energy on life expectancy in G-7 countries.

This paper aims to assess the moderating role of foreign direct investment (FDI) on the effect of economic complexity on carbon emissions, considering other drivers of carbon emissions such as renewable energy use and economic growth, using data set spanning between 1990 and 2018 in BRICS nations.

This research aims to fill the gap in ongoing literature. Cross-sectional IPS and cross-sectional augmented Dickey–Fuller tests, fully modified ordinary least square, dynamic ordinary least square, fixed effect ordinary least square, Westerlund cointegration and method of moments quantile regression (MMQR) econometric approaches are applied.

The Westerlund cointegration outcomes disclosed long-run interconnectedness between carbon emissions and its drivers. Furthermore, MMQR outcomes disclosed that in each tail (0.1–0.90), economic growth and economic complexity contribute to upsurge in carbon emissions while in each quantile (0.1–0.90) renewable energy abate carbon emissions. Furthermore, we affirmed the pollution-haven and environmental Kuznets curve hypotheses across all quantiles (0.1–0.90). Finally, at all quantiles (0.1–0.90), the joint effect of both FDI inflows and economic complexity reduced carbon emissions. Furthermore, the panel causality outcomes disclosed that all the exogenous variables can predict carbon emissions. Based on the findings, BRICS nation’s policymakers should place a greater emphasis on FDI inflows because it aids in abating environmental degradation.

To the best of the authors’ knowledge, this is the first research to test the moderating role of FDI on the effect of economic complexity on carbon emissions. Hence, this research aims to fill the gap in ongoing literature.

Due to their limited capacity for adaptation and dependence on natural resources for economic growth, developing countries (DCs) tend to be more prone to climate change. It is argued that climate finance (CF) is a significant financial innovation to mitigate the negative effects of climate variation. However, the heterogeneous impacts of CF on environmental sustainability (ES) and social welfare (SW) have been masked. Thus, this study aims to investigate the heterogeneous effects of CF on ES and SW in 80 CF receipt DCs from 2002 to 2018. This study also aims to investigate the effects of CF on ES and SW based on population size, income heterogeneity and the type of CF.

The method of moments quantile regression (MMQR) with fixed effects is utilized. Alternatively, the fully modified least square (FMOLS) and dynamic least square (DOLS) estimators are used for the robustness test.

The findings revealed that DCs with the lowest and middle quantiles of EF, carbon dioxide (CO₂) emissions and human development exhibit large beneficial impacts of CF on ES and SW. In contrast, the positive effects of CF on ES breakdown for countries with the largest distributions of EF and CO₂ emissions. Besides, the impacts of CF on ES and SW depend on income heterogeneity, population size and the type of CF.

This study calls for a framework to integrate CF into all economic development decisions to strengthen climate-resilient SW and ES in DCs.

To the best of the authors’ knowledge, this is the first study to investigate the effects of CF on ES and SW in a wide range of DCs. Thus, it complements existing related literature focusing on the effects of CF on ES and SW.

In this paper, the authors investigate the inbound tourism demand elasticities of the Middle East and North African (MENA) countries. The authors emphasize the role of external and internal conflicts, world gross domestic product and relative prices over the period 1995–2017.

This study applies the heterogeneous panel data estimators based on the fully modified-OLS (FM-OLS), dynamic-OLS (DOLS) and the recently developed method of moments quantile regression (MMQR).

The empirical results indicate that the effect of external and internal conflicts on inbound tourism demand is negative and inelastic with external conflict having a stronger effect. The effect of both classifications of conflicts diminishes as the market share of the tourist destination increases. In addition, the role of the world GDP on tourism demand is positive and elastic, suggesting that tourism is a luxury good while an increase in relative prices diminishes inbound tourism demand.

The paper, therefore, concludes that if policy measures are not put in place to curtail incidences of conflicts, economic growth in these countries may suffer setbacks. This by implications could affect the attainment of the sustainable development goals (SDGs) targets.

This paper aims to examine the reaction of energy inflation to geopolitical risks in the European Economic Area between 1990 and 2015.

This study applies the nonparametric time-varying coefficient panel data model with fixed effects. In addition, to further reveal potential tail effects that may not have been captured by conditional mean-based regressions, the method of moments quantile regression was also used.

The findings of this study are as follows: first, as European countries get exposed to geopolitical tensions, it is expected that energy prices will surge. Second, the ability of geopolitical risk to trigger energy inflation in recent times is not as powerful as it used to be. Third, countries with a lower inflation rate, when exposed to geopolitical risks, experience smaller increases in energy inflation compared to countries with a higher inflation rate.

The findings of this study lead us to the conclusion that transitioning from nonrenewable to renewable energy use is one channel through which the sampled countries can battle the energy inflation, which geopolitical risks trigger. A sound macroeconomic policy for inflation control is a complementary channel through which the same goal can be achieved.

Given the increasing level of energy inflation and geopolitical risks in the world today, this study is an attempt to reveal the time-varying characteristics of the relationship between these variables in European countries using a nonparametric time-varying coefficient panel data model and method of moments quantile regression with fixed effects.

Today, many industries are implementing creative approaches in response to increasing environmental awareness. It is of great importance to answer the question of whether the military sector, one of the most important sectors, can support renewable energy (RE) adaptation. This study aims to examine how military spending affects the supply of RE in 27 Organization for Economic Cooperation and Development (OECD) nations as well as the regulatory function of factors such as innovation, international trade and oil prices between 1990 and 2021.

The study examines the effects of military spending, income, green innovation, international trade, oil prices and the human development index on the supply of RE using various econometric approaches, which are the cointegration test, moments quantile regression and robustness test.

The findings demonstrate that all factors, excluding military spending, quite likely affect the expansion of the renewable supply. Military spending negatively influences the RE supply; specifically, a 1% increase in military spending results in a 0.88 reduction in the renewable supply. In addition, whereas income elasticity, trade and human development index in OECD nations are higher in the last quantiles of the regression than in the first quantiles, the influence of military spending and innovation on renewable supply is about the same in all quantiles.

OECD nations must consider the practical implications, which are essential to assess and update the military spending of OECD countries from a green energy perspective to transition to clean energy. Based on the study’s overall findings, the OECD countries should incorporate the advantages of innovation, economic growth and international trade into their clean energy transition strategies to lessen the impact of military spending on renewables.

The study aims to fill a gap in the literature regarding the role of military expenditures in the RE development of an OECD country. In addition, the results of the methodological analysis can be used to guide policymakers on how military spending should be in the field of RE.

The purpose of this examine the impact of income inequality and shadow economy on environmental degradation given the growing income inequality, shadow economy and ecological degradation in developing countries. Thus, this study is motivated to offer empirical insight into how income inequality and shadow economy influence the environment in African countries.

Data from 29 countries in Africa between 2000 and 2017 were used, while the novel method of moments quantile regression of Machado and Silva (2019) and Dumitrescu and Hurlin (D-H) (2012) granger causality is used as the estimation techniques.

The results established the presence of cross-sectional dependence and slope heterogeneity in the panel, while Westerlund panel cointegration confirmed the long-run cointegration among the variables. The results from the quantile regression suggest that income inequality increases environmental degradation from the 5th to the 30th quantiles, while from the 70th quantiles, income inequality reduces ecological degradation. The shadow economy negatively influences environmental degradation across the quantiles, strengthening environmental quality. Per capita income (economic growth) and financial development positively impact environmental degradation throughout the quantiles. However, urbanization reduces environmental degradation from 60th to 95th quantiles. The D-H causality established a two-way relationship between income inequality and environmental degradation, while one-way from shadow economy, per capita income and urbanization to environmental degradation were established.

This study provides fresh insights into the nexus between shadow economy and environmental quality in the presence of higher levels of income inequality for the case of African region. The study applies quantile analysis via moment proposed by Machado and Silva (2019). This technique shows that the impact of income inequality and shadow economy on environmental degradation is heterogeneous across the quantiles of ecological footprints in Africa.

Driven by the Sustainable Development Goals (goals 7, 8, 12 and 13), this study investigates the moderating role of financial development in the link between energy poverty and a sustainable environment in African nations.

Panel cointegration analysis, fully modified least squares, Driscoll and Kraay least squares and method of moments quantile regression were used as estimation techniques to examine the link between financial development, energy poverty and sustainable environment for 28 African nations. Energy poverty is measured using two proxies-access to clean energy and access to electricity, while the environment is gauged using ecological footprint.

The regression outcomes show that access to clean energy and electricity negatively impacts the ecological footprint across all the quantiles; hence, energy poverty increases environmental degradation. Financial development positively influences environmental degradation in the region at the upper quantiles. Similarly, the interactive term of energy poverty and financial development has a significant positive impact on ecological footprint; thus, the financial sector adds to energy poverty and environmental degradation. The results of other variables hint that per capita income and institutions worsen environmental quality while urbanisation strengthens the environment.

This study offers fresh insights into the moderating effect of financial development in the link between energy poverty and sustainable environment in African countries.

This study aims to examine the relationship between financial development (FD), financial risk, green finance and innovation related to carbon emissions in the G7 economies.

This quantitative study examines the roles that financial development [FD: Domestic credit to private sector by banks as percentage of gross domestic product (GDP)], economic growth (GDP: Constant US$ 2015), financial risk index (FRI), green finance (GFIN: Renewable energy public research development and demonstration (RD&D) budget as percentage of total RD&D budget), development of environment-related technologies (DERTI: percentage of all technologies) and human capital (HCI: index) have on the environmental quality of developed economies. Based on panel data, the study uses a novel approach method of moments quantile regression as a main method to tackle the issue of cross-sectional dependency, slope heterogeneity and nonnormality of the data.

The study confirms that increasing economic development increases emissions and negatively impacts the environment. However, efficient resource allocation, improved financial systems, and green innovation are likely to contribute to emission mitigation and the overall development of a sustainable viable economy. Furthermore, the study highlights the importance of risk management in financial systems for future emissions prevention.

The study uses a reliable estimation procedure, which extends the discussion on climate policy from a COP-27 perspective and offers practical implications for policymakers in developing more effective emission mitigation strategies.

The study offers policy suggestions for a sustainable economy, focusing on both COP-27 and the G7 countries. Recommendations include implementing carbon pricing, developing carbon capture and storage technologies, investing in renewables and energy efficiency and introducing financial instruments for emission mitigation. From a COP-27 standpoint, the G7 should prioritize transitioning to low-carbon economies and supporting developing nations in their sustainability efforts to address the pressing challenges of climate change and global warming.

In comparison to the literature, this study examines the importance of financial risk for G7 economies in promoting a sustainable environment. More specifically, in the context of FD and national income with carbon emissions, previous researchers have disregarded the importance of green innovation and human capital, so the current study fills the gap in the literature related to G7 economies by exploring the link between the identified variables related to carbon emissions.

In this study, the author intend to investigate the impacts of renewable energy use and environmental taxation on sustainable development measured by the adjusted net savings (ANS).

This study employs the quantile regression (QR) for a set of 24 Organization for Cooperation and Economic Development (OECD) countries over the period 1994–2018.

The main empirical findings of estimates show that access to renewable energy and environmental taxation generate positive and significant effects in increasing the ANS for most quantiles. Hence, they are practical tools for achieving sustainable development goals (SDGs).

This study has important implications for governments and policymakers of the OECD countries. Therefore, governments can use subsidies and incentives to promote the adoption of renewable energy sources, energy-efficient technologies and sustainable practices. Similarly, by imposing taxes on pollution and resource use, governments can encourage the adoption of cleaner technologies and practices toward more sustainable behavior.

This paper is based on a novel measure of sustainable development (ANS) and a novel econometric method (QR).