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This study investigates the relationship between economic growth, international trade, and environmental degradation in Sub-Saharan Africa (SSA), focusing on the validity of the environmental Kuznets hypothesis (EKC), the pollution havens hypothesis (PHH), and the factor endowment hypothesis (FEH).

The study uses annual data for 41 SSA countries between 1990 and 2017 and employs the bias-corrected least square dummy variable (LSDVC) estimation techniques. Environmental degradation is indicated by carbon dioxide (CO₂), delicate particulate matter (PM2.5) emissions, and deforestation.

The results confirm the validity of the EKC hypothesis for PM2.5 emissions and deforestation but not for CO₂ emissions. The results also indicate that international trade reduces deforestation and that both the PHH and FEH are valid for CO₂ emission but not for PM2.5 emissions and deforestation.

In this paper, the authors are able to illustrate that both economic growth and international trade can harm the environment if unchecked. Therefore, the conclusion of this study offers policy options through which SSA countries can achieve desired economic growth goals without affecting environmental quality. The study can be a benchmark for environmental policy in the region.

The authors provide an in-depth discussion of the growth-trade-environmental degradation nexus in SSA. The EKC, PHH, and FEH’s validity confirm that economic growth remains a threat to the local natural environment in SSA. Hence, the need for a trade-off between economic growth needs and environmental degradation and understanding where to compromise to achieve SSA's economic development priorities.

The purpose of this paper is to evaluate the impact of corruption on the environmental quality in Tunisia. Indeed, the post-revolution period is characterized by a remarkable increase in the rates of corruption.

The direct and indirect effects of control corruption on economic growth and CO₂ emissions in Tunisia have been examined using the autoregressive distributed lag (ARDL) cointegration framework among corruption, growth and CO₂ emissions.

Results substantiate a positive and significant relationship between control of corruption and economic growth, a negative and significant relationship between control of corruption and environmental quality (CO₂) and a negative and significant relationship between control of corruption and energy consumption. The findings suggest that while the control of corruption contributes to economic growth, its positive effect could be transposed indirectly via its impacts on environmental quality.

A strategy against corruption will reduce CO₂ emissions; however, its positive effect on economic growth indirectly contributes to reverse this relationship.

This study aims to analyze and compare the relationship between international trade in global value chains (GVC) and greenhouse gas (GHG) emissions for Brazil and China from 2000 to 2016.

The input-output method apply to multiregional tables from Eora-26 to decompose the GHG emissions of the Brazilian and Chinese productive structure.

The data reveals that Chinese production and consumption emissions are associated with power generation and energy-intensive industries, a significant concern among national and international policymakers. For Brazil, the largest territorial emissions captured by the metrics come from services and traditional industry, which reveals room for improving energy efficiency. The analysis sought to emphasize how the productive structure and dynamics of international trade have repercussions on the environmental dimension, to promote arguments that guide the execution of a more sustainable, productive and commercial development strategy and offer inputs to advance discussions on the attribution of climate responsibility.

The metrics did not capture emissions related to land use and deforestation, which are representative of Brazilian emissions.

Comparative analysis of emissions embodied in traditional sectoral trade flows and GVC, on backward and forward sides, for developing countries with the main economic regions of the world.

This study aims to empirically examine the influence of financial constraints on firm carbon emissions. In addition to the role of financial constraints in firm-level carbon emissions, this study also examines this influence in the presence of governance, environmental orientation and firm-level attributes.

Using pooled ordinary least square, this study examines the impact of financial constraints on firm-level carbon emissions using a panel of 1,536 US firm-year observations from 2008 to 2019. This study also used two-step generalized method of moment–based dynamic panel data and two-stage least square approaches to address potential endogeneity. The results are robust to endogeneity and collinearity issues.

The results suggest that financial constraints enhance the carbon emissions of the firms. The economic significance of financial constraints on carbon emissions is more pronounced for the firms that do not report environment-related expenditure investment and those that are highly leveraged. The authors further document that firms with a nondiverse gender board signify a statistically significant impact of financial constraints on carbon emissions. These results are also economically significant, as one standard deviation increase in financial constraints is associated with a 3.340% increase in carbon emissions at the firm level.

Some implicit and explicit factors like corporate emissions policy and culture may condition the relationship of financial constraints with carbon emissions. Therefore, it would be worthwhile to consider these factors for future research. In addition, it is beneficial to identify the thresholds and/or quantiles at which financial constraints may significantly make a difference in enhancing carbon emissions.

The findings offer policy implications for investment in stakeholder engagement for capital acquisitions, thereby effectively enforcing environmental innovation and leading to a reduction in carbon emissions.

This study integrated governance and environment-oriented variables in the model to empirically examine the role of financial constraints on the carbon emissions of the firms in the USA over and above what has already been documented in the earlier literature.

With more cities aiming to achieve climate neutrality, identifying the funding to support these plans is essential. The purpose of this paper is to exploit the present of a structured green bonds framework in Sweden to investigate the typology of abatement projects Swedish municipalities invested in and understand their effectiveness.

Marginal abatement cost curves of the green bond measures are constructed by using the financial and abatement data provided by municipalities on an annual basis.

The results highlight the economic competitiveness of clean energy production, measured in abatement potential per unit of currency, even when compared to other emerging technologies that have attracted the interest of policymakers. A comparison with previous studies on the cost efficiency of carbon capture storage reveals that clean energy projects, especially wind energy production, can contribute to the reduction of emissions in a more efficient way. The Swedish carbon tax is a good incentive tool for investments in clean energy projects.

The improvement concerning previous applications is twofold: the authors expand the financial considerations to include the whole life-cycle costs, and the authors consider all the greenhouse gases. This research constitutes a prime in using financial and environmental data produced by local governments to assess the effectiveness of their environmental measures.

This study aims to examine the relationship between foreign finance, economic growth and CO₂ to investigate if the environmental Kuznets curve (EKC) exists as an empirical evidence in 32 selected Organization for Economic Co-operation and Development (OECD) countries.

This study used quantitative analysis to test two main hypotheses: H1 is the U-shape relationship between foreign finance and environment, and H2 is the N-shaped association between economic growth and environment. In doing so, this study used panel data techniques. The panel set contained 32 countries over the period from 1990 to 2015, with 27 observations for each country. This study applied a panel OLS estimator via fixed-effects control to address heterogeneity and mitigate endogeneity. Generalized method of moments (GMM) with fixed effects-instrumental variables (FE-IV) and diagnostic tests were also used.

The results showed that foreign finance and environmental quality have an inverted U-shaped association. The three proxies’ foreign investment, foreign assets and remittance in the first stages contribute significantly to CO₂ emissions, but after the threshold point is reached, these proxies become “environmentally friendly” by their contribution to reducing CO₂ emissions. Also, a non-linear relationship denotes that foreign investment in OECD countries enhances the importance, as a proxy of foreign finance has greater environmental quality than foreign assets. Additionally, empirical results show that remittances received is linked to the highest polluted levels until a threshold point is reached, at which point it then helps reduce CO₂ emissions. The GMM and FE-IV results provide robust evidence on inverse U-shaped relationship, while the N-shaped relationship explains that economic growth produces more CO₂ emissions at the first phase of growth, but the quadratic term confirms this effect is negative after a specific level of GDP is reached. Then, this economic growth makes the environment deteriorate. These results are robust even after controlling for the omitted variable issue. The IV-FE results indicate an N-shaped relationship in the OECD countries.

Most studies have used different economic indicators as proxies to show the effects of these indicators on the environment, but they are flawed and outdated regarding the large social challenges facing contemporary, socio-financial economic systems. To overcome these disadvantages, the social, institutional and environmental aspects of economic development should also be considered. Hence, this study aims to explain this issue as a relationship with several proxies in regard to environmental, foreign finance and economic aspects.

This paper uses updated data sets for analyzing the relationship between foreign finance and economic growth as a new proxy for pollution. Also, this study simulates the financial and environmental future to show their effect on investments in different OECD countries. While this study enhances the literature by establishing an innovative control during analysis, this will increase to add value. This study is among the few studies that empirically investigate the non-linear relationship between finance and environmental degradation.

The aim of this article is to research on forestry green total factor productivity and explore the impact of financial support on forestry green total factor productivity.

The methods used in this study are super efficiency SBM model of undesired output and empirical model. SBM model is a kind of Data Envelopment Analysis (DEA). The SBM model with non-expected outputs (slacks-based measure) can be used to deal with the problem of efficiency measurement with multiple input and output variables and can be used to analyze the efficiency of green development of forestry economy.

First, the overall green total factor productivity of the authors’ country's forestry has shown a trend of first decline and then an increase from 2008 to 2018, and there are significant spatiotemporal differences; second, financial support has a significant positive impact on forestry green total factor productivity; third, environmental regulation has a significant threshold effect in the process of financial support on forestry green total factor productivity, and the role of financial support shows a trend of first increasing and then decreasing.

Secondly, taking the data of 30 provinces and cities in the authors’ country from 2008 to 2018 as the research object, using the super-efficiency SBM-Malmquist index to measure the country's forestry green total factor productivity and analyze its temporal and spatial changes; finally, a dynamic panel model was established to explore the impact of financial support on forestry green total factors quantitative impact on productivity, and adding environmental regulation as a threshold variable to establish a dynamic threshold regression, and found that financial support has a nonlinear impact on forestry green total factor productivity.

An unreliable supply of grid electricity has a strong negative impact on industrial and commercial profitability as well as on household activities and government services that rely on electricity supply. This unreliable grid electricity could be a result of technical and security factors affecting the grid network. Therefore, this study aims to investigate the effects of technical and security factors on the transmission and distribution of grid electricity in Uganda.

This study used the ordinary least squares (OLS) and autoregressive distributed lag (ARDL) models to examine the effects of technical and security factors on grid electricity reliability in Uganda. The study draws upon secondary time series monthly data sourced from the Uganda Electricity Transmission Company Limited (UETCL) government utility, which transmits electricity to both distributors and grid users. Additionally, data from Umeme Limited, the largest power distribution utility in Uganda, were incorporated into the analysis.

The findings revealed that technical faults, failed grid equipment, system overload and theft and vandalism affected grid electricity reliability in the transmission and distribution subsystems of the Ugandan power grid network. The effect was computed both in terms of frequency and duration of power outages. For instance, the number of power outages was 116 and 2,307 for transmission and distribution subsystems, respectively. In terms of duration, the power outages reported on average were 1,248 h and 5,826 h, respectively, for transmission and distribution subsystems.

This paper investigates the effects of technical and security factors on the transmission and distribution grid electricity reliability, specifically focusing on frequency and duration of power outages, in the Ugandan context. It combines both OLS and ARDL models for analysis and adopts the systems reliability theory in the area of grid electricity reliability research.

This study aims to examine the relationship between financial inclusion, CO₂ emissions and financial sustainability across 17 African countries.

Data were sourced from the World Development Indicators for the period 2004-2021. The study performs the principal component analysis, panel fixed effects model and quantile regression estimations to investigate the relationship between financial inclusion, CO₂ emissions and financial sustainability.

The study finds that an increase in automated teller machine (ATM) penetration rate, savings and credits increases CO₂ emissions. Findings also reveal that financial sustainability reduces financial inclusion, with significant negative effects on the conditional mean of CO₂ emissions and the conditional distribution of CO₂ emissions across quantiles.

This study is beneficial for policymakers, particularly in the age of digitalization and drive for low-carbon emissions, to develop green credits for energy players and investors to take up renewable and green energy projects characterized by high levels of carbon storage and carbon capture. Further, the banking sector’s credits and liquid assets should be used to finance alternative banking energy-related equipment and services, such as solar photovoltaic wireless ATMs, and fewer bank branches.

Based on the hypothesis of the environmental Kuznets curve (EKC), the purpose of this study is to investigate the relationship between environmental pollutants (as measured by CO₂ emissions) and GDP for India, over the period 1980–2012. The presence of an inverted “U” shape relationship is examined while controlling for factors such as the degree of trade openness, foreign direct investment, oil prices, the legal system and industrialization.

To verify whether the EKC follows a linear, quadratic or polynomial form, autoregressive distributed lag (ARDL) bounds testing approach for cointegration with structural breaks is adopted. The annual time series data for carbon emissions (CO₂), economic growth (GDP), industrial development (industrialization), foreign direct investment and trade openness have been obtained from World Development Indicators online database. Crude oil price (international price index) for the period is collected from the International Monetary Fund. Data for total petroleum consumption are collected from the US Energy Information Agency. Data for economic freedom variables are from the Fraser Institute's Economic Freedom Index's online database.

The findings support the existence of inverted U-shaped EKC in the short-run, but not in the long-run. A linear monotonic relationship has also been estimated in select model specifications. Additionally, trade openness has been estimated to reduce emissions in models, which incorporate FDI. Else, where significant, its impact on carbon emissions is adverse. A rise in fuel price leads to reduction in carbon emissions across model specifications. Further, the lower size of government degrades the environment both in the long-run and short-run.

Given the existence of the pollution haven hypothesis, wherein more trade and foreign direct investments cause environmental degradation, the paper proposes formulation of appropriate regulatory mechanisms that are environmentally friendly. Additionally, India's new economic policies, favoring liberalization, privatization and globalization, reinforces the need to strengthen environmental regulations.

Incorporation of economic freedom as measured by the “Size of Government” in the EKC model is unique. “Size of Government” deserves a special mention. The rationale for including this explanatory variable is to understand whether countries with lower government size are more polluting. After all, theory does suggest that goods and services, which have higher social cost vis-à-vis private cost, shall be overproduced in economies that adopt more market-friendly policies, necessitating government intervention. In the study, size of government is measured as per the definition and methodology adopted by Fraser Institute's Economic Freedom of the World Index.