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The purpose of this study is to check the impact of financial development on green technological innovation (GTI).

The sample size includes the 20-year (2001–2020) financial statistics of six Gulf Cooperation Council (GCC) region countries. To check the proposed relationship, this research uses a series of econometric models including fixed effect, fully modified ordinary least square and robust least square models.

The statistical results imply that financial sector development has a direct significant impact on GTI. A developed financial sector can uplift green technological development by offering more loans to industrial sectors and the import of modern technology. The statistical analysis further reveals the positive impact of gross domestic product (GDP), foreign direct investment inflow and trade volume while the negative impact of resources contribution on GTI.

The findings suggest key policy suggestions regarding the role of the financial sector in promoting GTI in the GCC region.

The novelty of this study lies in its examination of the relationship between FD and GTI in the GCC countries, a region with its unique economic and environmental dynamics.

The present study aims to investigate the non-linear relationship between trade and income inequality to address goal 10 of sustainable development goals (SDGs) using the Kuznets Curve (KC) framework for major emerging countries during 1991–2020.

For this purpose, recent econometric techniques, such as Common Correlated Effect (CCE) and Dynamic Common Correlated Effect (DCCE) estimators have been employed to deal with the cross-section dependence (CD) that arises in panel data, while the robustness of the study is checked through Driscoll–Kraay standard errors method.

The empirical results of the study confirm the existence of inverted “U-shaped” relationship between trade and income inequality suggesting evidence for the trade-led KC in the panel of emerging countries. Along with the non-linear model, the threshold value is estimated to be between 3.5 and 4% of gross domestic product (GDP).

The authors' findings support that trade contributes significantly toward reducing income inequality and helps in achieving goal 10 of SDGs. Hence, trade policies appear to be more egalitarian. The results widen the scope for further research and provide insights for regulators and policymakers in modeling trade policies and changing the status quo trade policy framework accordingly.

The present study is a pioneering attempt to examine the non-linear relationship between trade and income inequality under the KC framework in light of the Agenda 2030 for sustainable development. The study also considers other explanatory factors that have an impact on income inequality. Furthermore, the study considers other explanatory factors that have an impact on income inequality, and the attempt to estimate the threshold value for the trade-led KC is novel and interesting.

The modernization of the agro-based industry has encouraged the application of inorganic fertilizers to increase productivity. However, such fertilizer emissions may pose harmful environmental effects in the long run. This study aims to empirically explore the matter by applying the environmental Kuznets curve (EKC) hypothesis in the Indian agro-based industry.

The study builds two models considering nitrous oxide emission levels from inorganic (synthetic) and organic (manure) fertilizers to evaluate the safer option for the environment. The validity of an industry-specific EKC (IEKC) is tested for the models considering time series data from 1975 to 2019. Here, the autoregressive distributed lag model is applied for the 45 years long time series analysis to test the hypothesis with respect to inorganic and organic fertilizers emissions.

The existence of the IEKC is rejected by the inorganic fertilizer emissions model. Its U-shaped curve implies that applying such fertilizers will gradually cause degrading environmental effects. On the other hand, the organic fertilizer emissions model supports the existence of an inverted U-shaped IEKC. It proves that organic fertilizers are a better choice for safeguarding the environment in the long run.

Applying the EKC hypothesis on an industrial level can signify whether an industry worsens the environment in the long run. However, very few studies have explored such an application of the hypothesis in the past. Moreover, the literature could not find any previous study exploring the environmental effects of inorganic and organic fertilizers by analyzing the EKC hypothesis. The hypothesis can offer such insights with simplified empirical assessment.

The study aims to explore the validity of the modern renewable energy-environmental Kuznets curve (REKC) while considering the relevance of financial development in the consumption of modern renewable energy in East Africa Community (EAC). Modern renewable energy in this study includes all other forms of renewable energy except traditional use of biomass. The authors controlled for the effects of urbanization, governance, foreign direct investment (FDI) and trade openness.

Panel data of the five EAC countries of Burundi, Kenya, Rwanda, Tanzania and Uganda for the period 1996–2019 were used. The analysis relied on the use of the autoregressive distributed lag–pooled mean group (ARDL-PMG) model, and the data were sourced from the World Development Indicators (WDI), World Governance Indicators (WGI) and International Energy Agency (IEA).

The REKC hypothesis is supported for modern renewable energy consumption in the EAC region. Financial development positively and significantly affects modern renewable energy consumption, whereas urbanization, FDI and trade openness reduce modern renewable energy consumption. Governance is insignificant.

The concept of the REKC, although explored in other contexts such as aggregate renewable energy and in other regions, has not been used to explain the consumption of modern renewable energy in the EAC.

Faced with contradictory outcomes in empirical studies on the relation between democracy and income inequality, this paper attempts to provide empirical relations between democracy and income inequality. In particular, the authors seek to find if any curvilinear relation exists as in the Kuznets hypothesis.

Given elusiveness in empirical relations, the authors will consider several specifications using different estimation methods such as ordinary least squares (OLS), panel data estimation and performing statistical tests to determine the best specification for the relation between income inequality and democracy. Once the authors choose the specification, then the authors will apply this specification to the different groups of data to find any meaningful implications.

Using the unbalanced panel of 136 countries spanning from 1980 to 2018, the authors found an inverse U-shaped relation, called a political Kuznets curve – income inequality increases first and then decreases later as more democracy is achieved. By quantifying the curve, the authors find that the direct impact of democracy on income inequality is small and that the incremental impact of democracy on income inequality is smaller in a semi-democracy while relatively larger in a full democracy and autocracy.

From the study’s findings, the following policy implications can be considered. First, any change in income inequality caused by democratization should not be concerning as the impact of democracy on income inequality is measured to be very small. Second, the largest factor reducing income inequality is real GDP per capita. Third, the authors find that an impact of government expenditure on income inequality is also inversely U-shaped.

This chapter investigates the social determinants (urbanisation, population, literacy and corruption) of greenhouse gas (GHG) emissions in the top 100 developed and developing emitting countries. The data were collected from central repositories for the different variables explored for the period 2012–2020 in a cross-country analysis. Fixed effects ordinary least squares (OLS) regression was used to analyse the data. The results for all top 100 countries and developing countries show that urbanisation and corruption are significantly positive and negative determinants of GHG emissions, respectively. In addition, literacy is a significant positive determinant of GHG emissions in developing countries but not in the top 100 and developed countries. Population is not significant in the top 100 developed and developing countries. The results for the control variables suggest that primary energy consumption is a positive significant determinant of GHG emissions in the top 100 developed and developing countries. However, gross domestic product (GDP) is not a significant determinant of GHG emissions. The findings have important policy implications.

The main purpose of this study is to investigate the agriculture-induced environmental Kuznets curve (EKC) hypothesis in South Asian economies (SAE).

This study employs econometric techniques, including Westerlund cointegration tests, cross-sectional augmented distributive lag model (CS-ARDL) and Dumitrescu and Hurlin (DH) causality tests to investigate the relationship between renewable and non-renewable energy consumption, agriculture, economic growth, financial development and carbon emissions in SAE from 1990 to 2019.

The CS-ARDL test outcome supports the presence of the agriculture-induced EKC hypothesis in SAE. Additionally, through the application of the DH causality test, the study confirms a unidirectional causality running from renewable energy consumption (REC), fossil fuel consumption (FFC), economic growth (GDP) and squared economic growth (GDP²) to carbon dioxide (CO₂) emissions.

This study proposes that future research should extend comparisons to worldwide intergovernmental bodies, use advanced econometric methodologies for accurate estimates, and investigate incorporating the service or primary sector into the EKC. Such multidimensional studies can inform various methods for mitigating global climate change and ensuring ecological sustainability.

Environmental degradation has been extensively studied in different regions and countries, but SAE face significant constraints in addressing this issue, and comprehensive studies in this area are scarce. This research is pioneering as it is the first study to investigate the applicability of the agriculture-induced EKC in the South Asian region. By filling this gap in the current literature, the study provides valuable insights into major SAE and their environmental challenges.

This purpose of this study is to explore the impact of global trend of economic integration and interconnectedness which has drawn the attention of world economies and their implications on trade inflow. This trajectory has its impact, either positive/negative, on key macroeconomic indicators, to say the least on environmental sustainability, especially emerging economies. To this end, the need to explore the connection between foreign direct investment (FDI) inflow and energy consumption amidst the wave of economic globalisation is timely and pertinent for the case of Turkey.

This study seeks to explore the interaction between the outlined variables in a carbon-income framework for annual time series data from 1970 to 2016. A series of econometrics strategies was used consisting of unit root tests to examine the stationarity properties of the highlighted series. Subsequently, Pesaran’s Bounds testing technique is used to explore the long-run equilibrium relationship between the highlighted variables in conjunction with the Johansen cointegration test. For long-run regression coefficients, Pesaran’s autoregressive distributed lag and dynamic ordinary least squares methodology are used, and innovative accounting approaches are used to explore the responsiveness of each variable on another.

Empirical results validate the pollution haven hypothesis (PHH) in the long run for the case of Turkey. Thus suggesting that FDI inflow induced environmental degradation in Turkey. Additionally, this study observed that renewable energy, on the contrary, improves the quality of the environment. This study also affirms the presence of the environmental Kuznets curve phenomenon, indicating that Turkey, at its early stage of economic trajectory, emphasis is on economic growth rather than environmental quality. This suggests a need for more deliberate action(s) by the government administrators to pursue cleaner FDI inflow and energy technologies and strategies to foster a clean environment in Turkey and a cleaner ecosystem at large.

This study is unique in its choice of variables which is in line with the United Nations Sustainable Development Goals (SDGs) agenda to be achieved by 2030 and is very limited in the extant literature. From the economic perspective, the effect of the PHH is of interest especially to ascertain the extent the interplay among the variables has on the economy of Turkey. The empirical insights on PHH hypothesis have received less documentation in the extant literature especially for emerging economy like Turkey. Thus, this study seeks to revisit this theme for Turkey with aim to presents environmentally sustainable strategies without compromise for economic growth. Thus, this study seeks to revisit this theme.

The study examines the role of natural resources (NRs) and energy consumption in managing the climate crisis in Africa, using annual series data from the World Bank from 1980 to 2019.

The empirical strategy is based on the second-generation panel techniques that account for cross-sectional dependency in the series. Specifically, the empirical evidence is based on the Westerlund (2017) panel cointegration test, panel augmented mean group, common correlated effects mean group and the vector autoregressive (VAR)-vector error correction (VEC) approaches.

Evidence from the panel analysis confirmed the existence of Carbon Kuznets Curve (CKC) U-shaped nexus in Africa, but the country-level results are mixed. Furthermore, results using the VAR-vector correction model indicate possible convergence among the variables across the African countries. NR unidirectionally Granger-causes carbon emissions. The authors suggest the consideration of environmental factors in the utilisation of NRs. Similarly, energy efficiency is crucial to decouple carbon from energy usage.

The study complements the extant literature by assessing the role of NRs and energy consumption in managing climate crisis in Africa.

The eco-innovation is considered one of the possible ways to tackle climate change. However, the conflicting empirical evidence related to the role of eco-innovation on environmental quality becomes a motivation to explore the effect of eco-innovation on environmental degradation proxied by ecological footprint. Besides, it controls economic growth, remittance inflows, trade openness and total energy consumption in the environmental degradation function.

Uses the Augmented Auto Regressive Distributed Lag (AARDL) approach to examine the cointegration relation among the series during the period ranging from 1975 to 2017 for India within the environmental Kuznets curve (EKC) framework.

The result suggests that eco-innovation can mitigate climate change by reducing the ecological footprint. Similarly, economic growth reduces the ecological footprint in the short- and long-run. However, the square of economic growth is positive and significant. Thus, it shows evidence against the conventional EKC hypothesis. The results also reveal that remittance inflows have an insignificant negative role on the ecological footprint, while total energy consumption and trade openness harm the environment by enhancing the ecological footprint.

This study provides important implications for climate change mitigation. Thus, the government should promote eco-innovation to mitigate climate change by offering a favorable legal environment to the firms to adopt the same in their production and consumption activities. It also suggests that initiatives like green strategies should give serious attention while incurring research expenditure.

No prior studies assess the impact of eco-innovation on the ecological footprint for the period of 1975–2017 in India.