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The goal of sustainable economic growth is achievable only when economic growth and development occur without environmental degradation. The Environmental Kuznets Curve (EKC) hypothesis explains the inverted U-shaped association between economic activity and environmental degradation. The primary objective of this study is to empirically test the truth behind the EKC hypothesis. In addition to that, the study is intended to analyze the variation in the shape of the EKC; that is, cross-country variation, as well as variation over time. In order to achieve the stated objectives, the study analyzed a long list of countries (75 countries) for a fairly long period of time (1960–2016, i.e., 57 years). The empirical literature in this area estimated the EKC using some form of a polynomial regression equation. This study also used a similar kind of modeling structure to understand cross-country as well as dynamic variation in the shape of the EKC. In this study, firstly the selected countries are grouped on the basis of the shape of the EKC. Secondly, the dynamic behavior of each parameter in the polynomial equation is analyzed to understand the degree of association between economic activity and environmental degradation. This study suggests a decline in degree of association between the two over time.

The purpose of this paper is to provide a survey of the empirical literature on environmental Kuznets curve (EKC) estimation of carbon dioxide (CO₂) emissions over the period of 1991–2017.

This survey categorizes the studies on the basis of power of income in empirical models of EKC. It has been hypothesized that the EKC shows an inverted U-shaped association between economic growth and CO₂ emissions.

For all the contexts, the results of EKC estimation for CO₂ emissions are inconclusive in nature. The reasons behind this discrepancy can be attributed to the choice of contexts, time period, explanatory variables, and methodological adaptation.

The future studies in this context should not only consider new set of variables (e.g. corruption index, social indicators, political scenario, energy research and development expenditures, foreign capital inflows, happiness, population education structure, public investment toward alternate energy exploration, etc.), but also the data set should be refined, so that the EKC estimation issues raised by Stern (2004) can be addressed.

By far, no study in the literature of ecological economics has focused on the empirical estimation of EKC for CO₂ emissions. This particular context has been used for this study, as CO₂ is one of the highest studied pollutants in the ecological economics, and especially within the EKC hypothesis framework.

This study aims to examine the Environmental Kuznets Curve (EKC) hypothesis in the case of 100 developed and developing nations by taking into account the role of institutional quality (IQ). Using generalized method of moments (GMM) estimators, we find an inverted U-shaped relationship between economic growth and carbon dioxide (CO₂) emissions only in the developed world but not in the developing nations. It is also revealed that control of corruption plays a vital role in reducing CO₂ emissions in high income countries. Furthermore, rule of law is found to have a beneficial effect on the environment in all countries except for low income countries. Overall, our results confirm the importance of IQ in reducing CO₂ emissions. Additionally, foreign direct investment contributes to CO₂ reduction in rich countries while deteriorates the environmental quality in developing nations. Trade openness was shown to exert a positive impact on environmental quality in developing countries. These findings can be of great importance to policy makers of different income groups in designing appropriate economic and environmental policies toward the dual goals of high growth and low pollution.

The purpose of this research is to examine the validity of the agriculture-induced environmental Kuznets curve (EKC) hypothesis with evidence from an autoregressive distributed lag (ARDL) approach with a structural break including real income and energy consumption in the model for Ghana over the period 1980–2014.

The ARDL approach with a structural break was used to analyze the agriculture-induced EKC model which has not been studied in Ghana. The dynamic ordinary least squares (DOLS), canonical cointegration regression (CCR) and fully modified ordinary least squares (FMOLS) econometric methods were further used to validate the robustness of the estimates, and the direction of the relationship between the study variables was also clarified using the Toda–Yamamoto Granger causality test.

The ARDL results revealed that GDP, energy consumption and agricultural value added have significant positive effects on CO₂ emissions, while GDP² reduces CO₂ emissions. The Toda-Yamamoto causality test results show a bidirectional causality running from GDP and energy consumption to CO₂ emissions whereas a unidirectional long-term causality runs from GDP² and agriculture value-added to CO₂ emissions.

This finding validated the presence of the agriculture-induced EKC hypothesis in Ghana in both the short run and long run, and the important role of agriculture and energy consumption in economic growth was confirmed by the respective bidirectional and unidirectional causal relationships between the two variables and GDP. Thus, a reduction in unsustainable agricultural practices is recommended through specific policies to strengthen institutional quality in Ghana for a paradigm shift from rudimentary technology to modern sustainable agrarian technologies.

This study is novel in the EKC literature in Ghana, as no study has yet been done on agriculture-induced EKC in Ghana, and the other EKC studies also failed to account for structural breaks which have been done by this study. This study further includes a causality analysis to examine the direction of the relationship which the few EKC studies in Ghana failed to address. Finally, dynamic ordinary least squares (DOLS), canonical cointegration regression (CCR) and fully modified ordinary least squares (FMOLS) methods are used for robustness check, unlike other studies with single methodologies.

The purpose of this paper is to investigate the validity of the environmental Kuznets curve (EKC) between gross domestic product (GDP) per capita and environmental indicators in the Gulf Cooperation Council (GCC) countries. Additionally, this paper also explores the relationship between health and income levels in the GCC to identify whether higher incomes necessarily affect overall health metrics.

The first part of this paper studies the relationship between GDP per capita and the greenhouse gases (GHGs) – carbon dioxide (CO₂), nitrous oxide (N₂O) and methane (CH₄) (all per capita data). The second part of this paper explores the relationship between GDP per capita and the following health variables: life expectancy, infant mortality and child mortality – for GCC countries during 1980–2012. Unit root tests were conducted, followed by cointegration analysis, leading to Granger causality test and vector error correction model.

GCC states are highly dependent on fossil fuel production and hence depend on hydrocarbons for GDP growth. Most of the GCC states demonstrate lack of the EKC curve. However, there is evidence of U-shaped relationship between environmental pollutants and GDP per capita in kingdoms like Bahrain and Saudi Arabia (KSA). United Arab Emirates (UAE), on the other hand, demonstrates EKC, though not significantly. The study then explores the existence of potential relationship between health and GDP in the GCC, where it has been found that higher incomes have driven a better standard of living resulting in improved health metrics and higher life expectancy rates. Thus, growing incomes have played a positive role by improving health parameters and by offsetting some of the negative impacts from lack of environmental improvement as demonstrated by the absence of EKC in general in GCC.

GHG emissions data are individually and empirically examined for each country in the GCC. Furthermore, the study delves into the environmental problems that lead to health issues, which were initially caused by pollution. The results of the empirical analysis provide strong evidence that GCC countries need to rely less on fossil fuels, as lower productivity due to higher pollution reduces income and economic growth in most countries.

This is a survey paper of the recent literature on the application of semiparametric–econometric advances to testing for functional form of the environmental Kuznets curve (EKC). The EKC postulates that there is an inverted U-shaped relationship between economic growth (typically measured by income) and pollution; that is, as economic growth expands, pollution increases up to a maximum and then starts declining after a threshold level of income. This hypothesized relationship is simple to visualize but has eluded many empirical investigations. A typical application of the EKC uses panel data models, which allows for heterogeneity, serial correlation, heteroskedasticity, data pooling, and smooth coefficients. This vast literature is reviewed in the context of semiparametric model specification tests. Additionally, recent developments in semiparametric econometrics, such as Bayesian methods, generalized time-varying coefficient models, and nonstationary panels are discussed as fruitful areas of future research. The cited literature is fairly complete and should prove useful to applied researchers at large.

The aggregate index and per capita index have different meanings for some countries or regions. CO₂ emissions per capita matters for China because of its huge population. Therefore, this study aims to deepen the understanding of Kuznets curve from the perspective of CO₂ emissions per capita. In this study, mathematical formulas will be derived and verified.

First, this study verified the existing problems with the environmental Kuznets curve (EKC) through multiple regression. Second, this study developed a theoretical derivation with the Solow model and balanced growth and explained the underlying principles of the EKC’s shape. Finally, this study quantitatively analyzed the influencing factors.

The CO₂ emission per capita is related to the per capita GDP, nonfossil energy and total factor productivity (TFP). Empirical results support the EKC hypothesis. When the proportion of nonfossil and TFP increase by 1%, the per capita CO₂ decrease by 0.041 t and 1.79 t, respectively. The growth rate of CO₂ emissions per capita is determined by the difference between the growth rate of output per capita and the sum of efficiency and structural growth rates. To achieve the CO₂ emission intensity target and economic growth target, the growth rate of per capita CO₂ emissions must fall within the range of [−0.92%, 6.1%].

Inspired by the EKC and balanced growth, this study investigated the relationships between China’s environmental variables (empirical analysis) and developed a theoretical background (macro-theoretical derivation) through formula-based derivation, the results of which are universally valuable and provide policymakers with a newly integrated view of emission reduction and balanced development to address the challenges associated with climate change caused by energy.

This study has incorporated competitiveness by considering it a significant factor behind determining as well as moderating industrial value added in the environmental Kuznets curve (EKC) framework. This study aims to explore the moderating role of competitiveness policy in EKC with an aim to promote business led sustainability at national level.

Considering the environmental deterioration aspect of industrialization, this study tests the existence of EKC for SAARC countries using the data from 1996 to 2021 using second-generation static panel data model.

Estimated results have validated that moderating effect is responsible for improving environmental sustainability in SAARC countries. Furthermore, population density is responsible for increasing while trade openness is responsible for decreasing carbon emissions.

Higher industrial activities are a symbol of upward-moving economic growth. But its other impact is in the form of environmental deterioration. However, the relationship between industrialization and environmental quality can be identified through EKC.

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.

This study investigates the existence of the environmental Kuznets curve (EKC) for deforestation for Ghana over the 1962–2018 the time period.

The study employs a time-varying approach, the bootstrap rolling window Granger causality test to achieve its set objectives.

The results from our study reveals an inverted “N” shape EKC for deforestation, implying that deforestation will initially decrease with increases in economic growth up to a certain income threshold and increases with further increases in economic growth beyond this income threshold up to a higher income threshold and then decrease with further increases in economic beyond the higher income threshold.

The results from the study project show that over time economic growth can serve as a natural panacea to cure and mitigate the ills of deforestation that have plagued Ghana's forests over the years.

The results further highlight the important role of strong institutions in fighting the deforestation menace.

The originality of this study lies in its methodology which allows for feedback from deforestation to the economy. This is in contrast to earlier studies on the EKC for deforestation which allowed causality only from deforestation to the economy.