Kuznets Curve Research Articles

The role of agricultural innovations, renewable energy and economic growth in the CO2 emissions of Nepal: an empirical evidence from the environmental Kuznets curve

The role of agricultural innovations, renewable energy and economic growth in the CO2 emissions of Nepal: an empirical evidence from the environmental Kuznets curve

Empirical testing of the environmental Kuznets curve: evidence from 182 countries of the world

Empirical testing of the environmental Kuznets curve: evidence from 182 countries of the world

Unraveling the Environmental Consequences of Trade Openness in South Africa: A Novel Approach Using ARDL Modeling

Abstract Free trade and environmental sustainability are currently top economic and environmental research priorities. While numerous theories connect trade openness with environmental quality, empirical evidence often fails to support these claims. Using data spanning from 1980 to 2020, our study examines the effect of trade openness on CO2 emissions in South Africa. By employing a novel ARDL modeling framework, our analysis confirms the presence of the Environmental Kuznets Curve (EKC) hypothesis in South Africa. Our findings reveal that while GDP square enhances environmental quality, trade openness and economic growth have a degrading effect over time. Additionally, the study identifies that energy consumption, FDI, and value-added activities all contribute to environmental degradation. Findings also highlights the influence of institutional quality on the environment, demonstrating that political stability and control of corruption lead to increased CO2 emissions, while the rule of law reduces CO2 emissions. The research suggested that the potential of green economies should be leveraged in developing renewable energy, sustainable development, the recycling industry, and green financing sectors. A shift in economic activity in this direction will thus foster long-term economic growth and sustainable development.

Impact of human capital and natural resources on environmental quality in South Asia

AbstractThis study examines the importance of human capital and natural resources on environmental quality in South Asia by using panel data that ranges from 1975 to 2021. Advanced cointegration approaches establish the long-term linkages between human capital, natural resources, economic growth, economic growth squared, urban population, industrial value added, and ecological footprint. To explore the long and short-run association among these variables, this study applied the panel autoregressive distributed lags (ARDL) model. The outcome designates that human capital has a negative and significant alliance with environmental quality, whereas economic growth and economic growth square affect environmental quality positively and negatively, confirming the existence of the environmental Kuznets curve (EKC) hypothesis. Urban population growth and natural resources have significant negative associations with environmental pollution, whereas industrial value added increases the pollution levels in South Asia. Lastly, the outcome of the interaction between human capital and natural resource rent on the ecological footprint has a significant positive effect. This study recommends that South Asian nations improve their human capital to promote industrial modernization, expansion of green technology, and energy-efficient habits. Utilizing natural resources also helps South Asian nations maintain a clean ecosystem. Additionally, South Asian nations ought to vigilantly track the negative consequences of industrialization on the atmosphere. Thus, ecological sustainability requires human capital and natural resources.

Natural resources as a double-edged sword towards ecological quality: Can environmental regulations and green human capital rectify the adverse impacts?

Natural resources are the backbone of any economy and the bedrock of ecological health. However, the relentless exploitation of these resources has given rise to ecological degradation. This threatens ecosystem stability, presenting the urgent need to balance natural resource utilization with ecological integrity. Environmental regulations and green human capital are pivotal in striking this balance and progressing towards the Sustainable Development Goals (SDGs). Therefore, this study explores how natural resources impact ecological quality in Ghana from 1990 to 2019 within the environmental Kuznets curve (EKC) framework, considering the role of environmental regulations and green human capital. The study employs the novel dynamic ARDL simulation method, presenting insights that diverge from patterns noted in previous studies. The study’s findings reveal that natural resources intensify ecological quality in the short term but degrade ecological quality over the long term. Environmental regulation reduces ecological harm, while green human capital negatively impacts ecological quality. Environmental regulation and green human capital undesirably and beneficially impact how natural resources relate to ecological quality, with the undesirable effects occurring in the short term and the beneficial effects emerging over the long term. Further, a U-shaped relationship is observed between economic growth and ecological pollution in the short term, which transforms into an inverted U-shaped relationship in the long term, thus validating the EKC hypothesis in Ghana. The study concludes by recommending the implementation and enforcement of environmental regulations as a pathway toward achieving ecological quality and SDGs, particularly SDG 13, SDG 12, and SDG 7.

National wealth, cultural moderators and pollution mortality: a panel analysis of 170 countries

Global concerns have arisen due to pollution-related mortality, and scholars studying the Environmental Kuznets Curve (EKC) have explored the impact of economic growth on carbon emissions, yielding conflicting findings. Considering these opposing perspectives on whether wealth exacerbates or mitigates the negative consequences of environmental pollution, we aim to assess the influence of economic growth on pollution-related mortality and investigate whether national culture moderates its impact. To gain insights into the effects of economic growth on pollution-related mortality, we utilized panel data covering 170 countries over a span of 23 years (1996–2017). Initially, we examined the relationship between GDP per capita and pollution-related mortality, finding support for the theory of a curvilinear correlation but not for the concept of a bell-shaped curve. Upon introducing cultural moderators, the curve shifts in different directions along various dimensions. High power distance and masculinity cultures are associated with increased pollution-related mortality, whereas individualist and long-term orientation cultures are linked to reduced pollution-related mortality. The directions of these moderators align with both linear and nonlinear analyses, except for uncertainty avoidance. This study makes significant contributions to the critical issue of pollution-related mortality, extending beyond traditional sustainability analyses. Additionally, it provides a robust examination of the intertwining of economic wealth and culture, challenging the dominance of either type of logic. Lastly, our study draws attention to policy-driven solutions.

Higher education’s impact on CO2 mitigation: MENA insights with consideration for unemployment, economic growth, and globalization

Higher education’s impact on CO2 mitigation: MENA insights with consideration for unemployment, economic growth, and globalization

Have Agricultural Land-Use Carbon Emissions in China Peaked? An Analysis Based on Decoupling Theory and Spatial EKC Model

Assessing the emission-peaking process of agricultural land use provides valuable insights for mitigating global warming. This study calculated agricultural land-use carbon emissions (ALUCEs) in China from 2000 to 2020 and explored the peaking process based on quantitative criteria. Further, we applied the Tapio decoupling index and environmental Kuznets curve (EKC) model to discuss the robustness of the peaking process. The main conclusions are as follows: (1) From 2000 to 2020, China’s average ALUCEs were 368.1 Mt C-eq (1349.7 CO2-eq), peaking at 396.9 Mt C-eq (1455.3 Mt CO2-eq) in 2015 before plateauing. Emissions from agricultural materials and soil management had entered the declining period, while those from rice cultivation were in the peaking period, those from straw burning were still rising, and those from livestock breeding remained at the plateauing phase. (2) The provinces of Beijing, Tianjin, and nine others saw a decline in ALUCEs, while Hainan, Guizhou, and another nine provinces observed plateauing, and Ningxia, Qinghai, and six other provinces experienced peaking. (3) Decoupling analysis confirmed that emission-peaking states remained stable even with agricultural growth. Instead of an inverted U-shaped relationship, we found an N-shaped relationship between ALUCEs and agricultural GDP. The spatial EKC model indicated that the peaking process had spillover effects between provinces. It is recommended that China accelerate ALUCE mitigation based on the source and phase of emissions, considering the peaking process and magnitude.

Re-examining the Environmental Kuznets Curve in MENA Countries: Is There Any Difference Using Ecological Footprint and CO2 Emissions?

Re-examining the Environmental Kuznets Curve in MENA Countries: Is There Any Difference Using Ecological Footprint and CO2 Emissions?

Does macroprudential policy matter for corporate green innovation? The role of financing constraints and public environmental concerns

Green development ideas are gradually being incorporated into macroprudential policy frameworks, which can be of great significance for enterprises’ green development. Most studies focus on the macroeconomic impact of macroprudential policies (MPPs). However, the extent to which MPPs affect corporate green innovation (GI) at the corporate level remains unclear. Based on 12,280 firm-year records from China's A-Share Listed Companies spanning 2011–2020, combined with Environmental Kuznets Curve (EKC) hypothesis, we discover a firm tendency to promote GI under loosening MPPs, which is then curtailed after reaching a certain threshold. The impact is primarily channelled through public environmental concerns and financing constraints, as evidenced by an inverted U-shaped relationship. Additionally, MPPs are more likely to influence corporate GI in regions with high green finance development. Furthermore, we observed a consistent superiority of strategic over substantive GI, with green process innovation being the least impacted. Our results highlight the importance of rational design of MPPs not only at the macro level but also as a priority at the corporate level, as such a policy loosening and tightening will affect the GI activities of corporations.

Reinvestigating the EKC hypothesis: Does renewable energy in power generation reduce carbon emissions and ecological footprint?

For a developing nation such as Malaysia with a significant reliance on fossil fuels for electricity, understanding the environmental consequences of this dependency is crucial. Thus, this study utilizes the Autoregressive Distributed Lag (ARDL) method to explore the impact of electricity intensity (EINT), renewable energy in electricity generation (ERE), and gross domestic product (GDP) on Malaysia's environmental quality, from 1985 to 2020. By using carbon emissions (CO2 emissions) and ecological footprint (EF) as proxies, the study finds a significant long-run impact of these factors on environmental degradation. Notably, the study also observed an inverted U-shaped relationship between GDP and environmental degradation, validating the existence of Environmental Kuznets Curve (EKC) hypothesis. The findings also imply that while electricity intensity is associated with increased emissions, the use of renewable energy (RE) sources for electricity generation may contribute to emission reduction. But the results for both variables show reversal signs on EF. The study's adoption of the fully ordinary least square (FMOLS) method reinforces the same results, thus, justifying the cointegrating relationship between studied variables. Drawing from these outcomes, the study advocates for a comprehensive approach to renewable energy management, emphasizing both its utilization and waste in order to improve ecological footprint. Moreover, the pressing need to enact legislation on energy efficiency and conservation is crucial in ensuring decoupling and securing sustainable development in Malaysia.

Sustainable Impact of Green Building on the Eco-Economic Efficiency of the Construction Industry: Evidence from China

Addressing the global warming challenge, the carbon emissions reduction potential of green building (GB) is garnering increasing attention. However, the extent to which GB can impact the eco-economic efficiency (EE) of the construction industry remains unclear. To fill this gap, based on panel data for 30 regions of China from 2003 to 2018, in this study, a comprehensive analysis of the EE and sustainable impact of GB is conducted using a super slacks-based measure (SBM-DEA), panel vector autoregression (PVAR) and threshold models. The findings reflect that only about 10% of provinces have achieved EE effectiveness, with pure technical effectiveness being a significant driving force behind this. The average comprehensive, pure technical, and scale EE show a 62.23%, 46.42%, and 31.91% improvement potential regarding the efficiency frontier. The EE in the Eastern Region is relatively high, while the Western Region surpassed the Central Region in regards to EE in the areas of scale and pure technical efficiency. EE is significantly reduced in the current period (year) when it is subject to the positive impact of a standard deviation from the existing economic level. This impact was the strongest in period 1, then gradually disappeared until period 6, aligning with the Kuznets curve’s theoretical assumption. GB awareness negatively impacted the current period, but is expected to gradually show a positive effect after period 2. The urbanization, green building awareness, and green building coverage make a very small contribution to the EE, accounting for 8.6%, 1.6%, and 9%, respectively, with early EE and economic level identified as the primary variables affecting the current EE. The impact of GB on EE exhibits a threshold effect, with the ecological effect of GB significant only in cities with economic levels higher than 11.063. This research contributes to the existing knowledge of the eco-economic mechanism of GB and provides insights for government policies, promoting the sustainable development of the GB market.

The symmetric and asymmetric effect of financial development on ecological footprint in South Africa: ARDL and NARDL approach

Introduction: The literature on the finance–emission nexus offers conflicting conclusions. This study resolves this inconsistency by investigating the symmetric and asymmetric effect of financial development on ecological footprint in South Africa, using the Environmental Kuznets Curve framework as a guide. Given the coexistence of ecological deficits and world-class financial development systems in South Africa, it is essential to explore and evaluate potential solutions to mitigating these deficits. Our empirical analysis contributes to the body of literature on the impact of financial development and ecological footprint by using a comprehensive measure of financial development and disaggregates it into its sub-indices to provide a nuanced analysis.Method: This study employs the linear auto regressive distribution lag and nonlinear auto regressive distribution lag techniques to explore the complex interactions of financial development and ecological footprint.Results and Discussion: The findings of this research indicate that financial markets and institutions seem to have varying effects on the ecological footprint. Financial market indices promote environmental quality, while financial institutions exacerbate environmental quality. These results call for policymakers to craft a watertight process that will encourage both financial markets and institutions to allocate capital to projects that are pro-environmental.

Unveiling the Influence of Climate and Technology on Forest Efficiency: Evidence from Chinese Provinces

The objective of this study is to examine the impact of climate and technology on forest efficiency (FE) in China’s provinces from 2002 to 2020. First, the study used SBM-data envelopment analysis (SBM-DEA) to estimate Chinese provinces’ FE using multidimensional forest inputs and outputs. The climate influence is assessed using temperature, precipitation, sunlight hours, and carbon dioxide levels in the second phase. A climate index was created using principal component analysis (PCA) for a complete estimation. In addition to prior research, we analyze the technology impact through two technological indicators: (i) research and development, and (ii) investment in forests. Furthermore, we explore the non-linear influence of economic development on both FE and climate quality. The regression study by CupFM and CupBC found that temperature and precipitation increase FE, whereas sunlight hours and carbon emissions decrease it. The positive association observed between Climate Index1, and the negative relationship noted for Climate Index2, suggests that forests positively influence climate conditions, signifying that an improvement in FE leads to an improvement in climate quality. Technology boosts forest productivity and climatic quality. The environmental Kuznets curve shows an inverted U-shape relationship between economic development and FE. Similarly, climate and economic development have an inverted U-shaped EKC relationship. Urbanization reduces FE due to human growth and activity. Our findings are important for forest management, climate change, and sustainable development policymakers and scholars.

Intelligence and its effects on environmental decline: A worldwide analysis

The research investigates the relationship between intelligence quotient (IQ) and environmental degradation, aiming to understand how cognitive abilities influence environmental outcomes across different nations and time periods. The objective is to examine the impact of intelligence quotient (IQ) on environmental indicators such as carbon emissions, ecological demand, and the Environmental Kuznets Curve (EKC), seeking insights to inform environmental policy and stewardship. The study utilizes statistical techniques including Ordinary Least Squares (OLS), Two Stage Least Squares (2SLS), and Iteratively Weighted Least Squares (IWLS) to analyze data from 147 nations over the years 2000–2017. These methods are applied to explore the relationship between IQ and environmental metrics while considering other relevant variables. The findings reveal unexpected positive associations between human intelligence quotient and carbon emissions, as well as ecological demand, challenging conventional notions of "delay discounting." Additionally, variations in the Environmental Kuznets Curve (EKC) hypothesis are identified across different pollutants, highlighting the roles of governance and international commitments in mitigating emissions. The study concludes by advocating for the adoption of a "delay discounting culture" to address environmental challenges effectively. It underscores the complex interactions between intelligence, governance, and population dynamics in shaping environmental outcomes, emphasizing the need for targeted policies to achieve sustainability objectives.

Exploring how economic growth, renewable energy, internet usage, and mineral rents influence CO2 emissions: A panel quantile regression analysis for 27 OECD countries

This study aims to investigate the impacts of renewable energy consumption, internet usage, mineral rent, and economic growth on CO2 emissions across 27 OECD nations between 2001 and 2020. We employ a panel quantile regression technique to discover the heterogeneous effects of these variables for the various quantile levels of environmental destruction. The panel quantile regression approach found the Environmental Kuznets curve dominated countries in which CO2 emissions were low. Additionally, the negative relationship between renewable energy consumption and CO2 emissions yielded in the paper suggests the potential benefits of incentivizing and investing in renewable sources. Internet usage demonstrates a negative impact on CO2 emissions, showcasing the role of digital technologies in promoting sustainability. Accordingly, internet use improves environmental quality due to more efficient, sustainable, and eco-friendly practices, which increase productivity. However, a positive association between mineral rents and environmental deterioration emphasizes the necessity of strategic policies to balance economic benefits with environmental preservation. Our study provides policymakers with valuable insights into tailoring effective strategies for sustainable development, renewable energy adoption, digitalization, and natural resource utilization while addressing environmental degradation.

Trade openness, human capital, natural resource, and carbon emission nexus: a CS-ARDL assessment for Central Asian economies.

There is a call for global efforts to preserve the ecological systems that can sustain economies and people's lives. However, carbon emission (CEM) threatens the sustainability of humanity and ecological systems. This analysis looked into the influence of energy use (ERU), human capital (HCI), trade openness (TOP), natural resource (NRR), population, and economic growth (ENG) on CEM. The paper gathered panel data from the Central Asia region from 1990 to 2020. The CS-ARDL was applied to establish the long-term interaction among the indicators. The paper's findings indicated the presence of the environmental Kuznets curve (EKC) in the Central Asia regions. Also, the empirical evidence highlighted that energy use, natural resources, and trade openness cause higher levels of CEM. However, the research verified that CEM can be improved through human capital and urban population growth. The study also found that HCI moderates the interaction between NRR and CEM. The causality assessment indicated a one-way interplay between ENG, ERU, NRR, and CEM. The study proposes that to support ecological stability in these regions, policy-makers should concentrate on developing human capital, investing in renewable energy sources, and utilizing contemporary technologies to harness natural resources in the economies of Central Asia.

Environmental Kuznets curve of carbon emissions from China’s forest products industry and decomposition of factors influencing carbon emissions

Carbon emissions from China’s forest products industry were considered based on the data of 2001-2020. Then a carbon emissions Kuznets curve was constructed to judge the relationship between the economic development level and carbon emissions. The logarithmic mean Divisia index (LMDI) was used to analyze the influencing factors of carbon emissions. The carbon emissions from China’s forest products industry showed a trend of rapid growth in the early stage and slow decline in the later stage, increasing from 19.46 million tonnes in 2001 to 54.18 million tonnes in 2020. Consumption of raw coal was the main reason for the increase in carbon emissions. There was an inverted-U relationship between the economic development level and carbon emissions, and the industry output value of CNY 3306.56 billion was the theoretical inflection point. The current economic development level of the industry was in the left-half part of the inverted “U” shape, indicating that carbon emissions from this industry will continue to increase with the increase of industrial output. Economic development was the key factor driving the increase of carbon emissions in the forest products industry, while the energy intensity was the key factor inhibiting the growth of carbon emissions.

Empirical analysis of the relationship between economic growth and environmental pollution based on VAR model: A case study of Hubei Province China

In this paper, the industrial three wastes from 1992 to 2018 in Hubei Province were collected as environmental indicators, and the per capita GDP was used as economic indicators. The study of Kuznets curve showed that industrial wastewater gradually decreased with economic growth, showing an inverted N shape; Both industrial emissions and solid waste will increase with the growth of per capita GDP, industrial waste gas shows a linear relationship, and industrial solids show an inverted U relationship. Then through the VAR model research, it is found that the response of industrial “three wastes” to per capita GDP growth in Hubei Province is positive in the short term. The long-term response of economic development in Hubei province to industrial waste gas and industrial solid waste discharge is positive and decreasing, but the short-term response to industrial wastewater discharge is negative. The variance decomposition analysis reveals that the primary environmental determinants influencing the current economic growth trajectory of Hubei Province are industrial wastewater, industrial waste gas, and industrial solid waste. Fluctuations in economic growth within Hubei Province demonstrate a stronger correlation with variations in emissions of industrial wastewater and industrial solid waste, while exerting comparatively less influence on changes in emissions of industrial waste gas.

Addressing the Environmental Kuznets Curve in the West African Countries: Exploring the Roles of FDI, Corruption, and Renewable Energy

Addressing the Environmental Kuznets Curve in the West African Countries: Exploring the Roles of FDI, Corruption, and Renewable Energy