EKC Model Research Articles

Does renewable energy proactively contribute to mitigating carbon emissions in major fossil fuels consuming countries?

The success of global climate initiatives (SDG-13, COP28) heavily depends on the actions of major fossil fuels consuming countries, as their continued reliance on these energy sources greatly impedes progress towards global climate objectives. Transitioning from the dominance of fossil fuels to the expansion of renewable energy is crucial for ensuring Sustainable Development Goals (SDGs) and Conference on Parties (COP) objectives under UN climate change initiatives, as well as for achieving environmental sustainability. This study investigates the proactive role of renewable energy in enhancing environmental sustainability and evaluates the impact of fossil fuel consumption, real gross domestic product (RGDP), square of RGDP, and patents on carbon emissions in major fossil fuels consuming countries from 1990 to 2020 after considering and disregarding the EKC model. Two-way additive and interactive fixed effect models demonstrate a statistically significant negative effect of renewable energy on carbon emissions. A method of moments quantile regression endorses the asymmetric negative effects of renewable energy across different quantiles of CO2 emissions. According to the quantile regression, a low CO2 emitting country's environmental quality is largely sensitive to the consumption of renewable energy. Also, after considering heterogeneity, cross-sectional dependence and endogeneity issues, the effect of renewable energy remains unchanged. On the contrary, unlike renewable energy, fossil fuel consumption, real GDP, square of real GDP, and patents have positive effects in most cases, worsening environmental quality by increasing CO2 levels. Therefore, based on these findings, our study emphasizes pivotal policy implications aimed at fostering a better environment in major fossil fuels consuming countries.

The effects of green finance on the carbon decoupling of marine fishery: analysis based on Tapio method and EKC model

The effects of green finance on the carbon decoupling of marine fishery: analysis based on Tapio method and EKC model

Relationships between economic development and resident environmental behavior and participation in areas with different economic and similar natural and cultural conditions

Economic development level (EDL) cannot completely explain environmental behavior and participation (EBP) patterns as many other factors affect environmental performances, and the conflict of ‘Maslow’s Hierarchy Needs model’ or ‘Affluence hypothesis’ and ‘Challenge-response Model’ hypothesis has been continuously discussed. In the present study, a standardized two-dimensional array (STDA) model is employed to deliberate on the EDL-EBP relationship in different sub-groups with the highest ($21389.08) and the lowest ($5216.41) average capita GDPs in Guangdong Province, China. This is the first attempt to investigate the relationships between the regional EDL represented by capita GDP and public environmental behaviors represented by actual resident’s resource consumption, pollution emission and environmental participation in areas with similar natural and cultural condition, and an Environmental Effort Indicator (EEI) is established based on the STDA model. The results show that (1) the STDA model is applicable in distinguishing resident’s EBPs of 20 prefecture-level cities (PLCs) of Guangdong Province with rather different EDLs; (2) the relationship of EDL-EBP is not liner pattern and is behavior- and region-specific; (3) public participation plays an important role that is most decisive to the EEI; (4) the V-shaped EDL-EEI relationships can be explained each other with the EKC model. The formation of resident’s good environmental habits would be a long-term process and environmental education is a key way to accelerate the process and to maintain sustainable developments of the nature and human society.

Renewable energy, economic freedom and economic policy uncertainty: New evidence from a dynamic panelthreshold analysis for the G-7 and BRIC countries.

This study aims to demonstrate the impact of renewable energy consumption (REC) on environmental degradation using the EKC hypothesis testing for the BRIC and G-7 countries. Two EKC models were created and tested, with Model 2 including REC and other independent variables such as economic freedom (EF) and economic policy uncertainty (EPU), which affect the level of renewable energy consumption and CO2 emissions. Empirical findings indicate that the EKC hypothesis is verified faster in the REC-EF-EPU-based EKC model (Model 2) than in the EF-EPU-based EKC model (Model 1) for G-7 countries since the turning point takes place earlier in Model 2 than in Model 1 with REC. This suggests that renewable energy consumption accelerates the reduction of CO2 emissions. Moreover, this earlier turning point results in lower environmental cleaning costs, less time vesting, and saving resources and money for G-7 countries. However, the study found no evidence supporting the EKC hypothesis for the BRIC countries.

Unveiling the nexus between marine energy consumption, seaborne trade, and greenhouse gases emissions from international shipping.

As a result of the globalization of production processes and the expansion of international trade, both water-based trade and the use of marine energy are expanding quickly. Marine energy consumption is rapidly increasing as a result of globalization. Despite being ignored for many decades, reducing marine emissions is today a top priority among European nations. Thus, the present study contributes to the existing literature by investigating the nexus between marine energy consumption, seaborne trade, and GHG emissions by employing time series data for eight Northern European nations from 2005 to 2017. The extended EKC model and three proxy variables for seaborne trade (i.e., container throughput, liner shipping connectivity index, and trade openness) are used to investigate the nexus between these variables. FMOLS and DOLS methods have been employed to control the problems of endogeneity and serial correlation. Only in Denmark, Norway, and Sweden did the data corroborate an inverted U-shaped relationship (the EKC curve) between maritime GHG emissions and economic development. The increase in energy utilization across all nations directly increased marine GHG emissions; however, the adverse effect of energy consumption on the environment is severe in Denmark, Norway, and Sweden. Container throughput, linear shipping connectivity index, and trade openness exhibit a positive impact on marine GHG emissions. The impact of seaborne proxy variables is severe in Denmark and Sweden. In order to have a robust assessment and to confirm the validity and uniformity of the results, Driscoll-Kraay standard errors (DKSE) and robust standard error (RSE) regression techniques are being employed.

Environment and female entrepreneurship in Southeast Asia: investigation of the environmental Kuznets curve hypothesis

This paper examines the relationship between female entrepreneurship and environmental implications in ASEAN economies. While economic growth and affluence benefit society, they come at the cost of environmental degradation, particularly rising carbon dioxide levels and ecosystem concerns. Women entrepreneurs in Southeast Asia can potentially support their families and contribute to societal development by starting their own businesses. Their ventures provide fresh perspectives on societal challenges and enable active participation and contribution to creative endeavors, leading to economic and social empowerment with ripple effects on families and communities. To assess the environmental consequences of women’s entrepreneurial activities, the study applies the bias-corrected method of moments and tests the Environmental Kuznets Curve hypothesis across ten ASEAN nations from 1980 to 2021. Results show cross-sectional dependence in all variables and confirm a long-term relationship within the EKC model. The fixed-effects estimator with bias correction is deemed the most suitable model. Findings indicate that GDPpc leads to decreased emissions, while the square of GDPpc contributes to increased emissions; however, the cubic term of GDPpc leads to decreased CO2 emissions, supporting the “inverted N” curve distribution of emissions across ASEAN nations proposed by the EKC theory. Additionally, the study reveals that higher percentages of female entrepreneurs are associated with increased carbon dioxide emissions, potentially due to increased efforts to support and develop female entrepreneurs. Conversely, a reduction in the gender gap in marriage, divorce, remarriage, and domestic violence leads to a shift away from entrepreneurial activities among women, positively impacting the environment.

A step towards a sustainable environment in top Asian countries: the role of higher education and technology innovation

The present study aims to examine a step toward a sustainable environment in top Asian Countries by incorporating the role of higher education and technology innovation. The sample data were collected from (1995 to 2019). However, the most-suited methodological approach i.e., the CS-ARDL technique is used to assess the long-run and short impact of these variables on each other; in addition, the modern theory of the EKC model is applied in the study to enhance the credibility of the results. As per the short-run estimation, determinants of higher education, GDP2, and technology innovation are negatively associated with the environment (CO2 emission). Although the long-run results of CS-ARDL signify that technology innovation (GIN) represents a −0.312∗∗∗ coefficient value which indicates a negative and significant relationship with the environment, whereas, HE & GDP shows a positive association with the environment (CO2 emission) having the coefficient values of 0.249∗∗∗ and 0.437∗∗∗, respectively. While the factor of GDP2 is negative in the long-run and positive in the short run, thus the EKC model is supported under this theoretical framework. Based on these explorations, the relevant implications are prescribed by the authors to get a sustainable environment in these top Asian countries.

Is growth of the financial sector relevant for mitigating CO2 emissions in Bangladesh? The moderation role of the financial sector within the EKC model

Is growth of the financial sector relevant for mitigating CO2 emissions in Bangladesh? The moderation role of the financial sector within the EKC model

The AHP (1-9 Value Scale) Level Method to Analyze the Development of Logistics under the Perspective of Low-Carbon Environmental Protection: Taking Shandong Province, China, as an Example

Reducing the total carbon emissions of the logistics industry is one of the basic requirements for the development of a low-carbon economy. Based on the AHP analytic hierarchy process and the 1-9 value scaling method, an evaluation index system for the low-carbon development of the logistics industry is constructed. At present, the development of low-carbon logistics requires the combination of low-carbon technology and low-carbon management to ensure the integrity and dynamics of low-carbon logistics control. The results of this study show that in the AHP index analysis of the development of logistics industry in Shandong Province, compared with 13 evaluation indexes of low-carbon logistics and traditional logistics, low-carbon logistics is significantly better than traditional logistics. Among them, the implementation of low-carbon logistics policy system has increased the energy utilization rate to 88.72%, the recovery rate of warehousing and logistics waste to 92.11%, and other relevant indicators have also been improved and optimized to varying degrees. Based on the EKC model curve, the total carbon emissions from 2015 to 2019 showed a downward trend month by month. The future development of low-carbon logistics mainly starts with reducing the total carbon emission of logistics transportation and improving energy utilization. Aiming at the main influencing factors of the development of low-carbon logistics, this paper puts forward specific measures for the development of low-carbon logistics, in order to promote the development of low-carbon logistics.

An Empirical Analysis of Jiangxi Province’s Financial Development, Economic Growth, and Environmental Pollution

Since the reform and opening up in 1978, the economic development in China has experienced a rapid growth stage. Statistics show that annual GDP has grown at an average rate of nearly 10%, and the annual per capita GDP growth rate has also approached 9%. With the rapid economic growth, the problem of environmental pollution across the country has become increasingly serious, and the environmental quality has been deteriorating, which has attracted the attention of many parties in the whole society. The relationship between economic growth and environmental quality has become a hot issue in various fields. First of all, this article introduces basic concepts such as economic development, environmental quality, environmental Kuznets curve, and the relationship between economic development and environmental quality. Afterwards, it analyzes the current situation of Jiangxi Province’s economy and environment from the aspects of Jiangxi Province’s economic aggregate, industrial structure, development mode, overall law of environmental quality, and industrial waste release. Secondly, this study constructs the evaluation index system of the economic and environmental relationship in Jiangxi Province and uses the principal component analysis method to screen the primary economic and environmental indicators, providing evaluation criteria for the establishment of the economic development and environmental quality relationship model of Jiangxi Province. Third, the relationship between the main economic environment indicators after the principal component analysis is simulated, and the EKC model of Jiangxi Province is established. The research results show that the environmental Kuznets curve in Jiangxi Province is not all the typical inverted U shape in developed countries, that is, environmental pollution does not necessarily show a trend of first rising and then falling with the increase of per capita income, but it appears as N-shaped, half of the inverted U shape, and even repeated fluctuations.

Dynamic Economic Analysis between Renewable Energy, Carbon Dioxide Emissions, Trade and GDP based on VECM Granger test and Wavelet Analysis

In this study, we explored the dynamic economic relationship between Taiwan’s GDP growth, renewable energy consumption, foreign trade openness, and CO2 emissions from 1965 to 2016. Our analysis is based on using updated data to test the existence of Taiwan's EKC model and discuss the causal relationship between CO2 emissions and variables such as GDP growth, renewable energy consumption, and foreign trade opening. We used multicollinearity analysis to test the stationarity of the quadratic form of the EKC model, ADF and KPSS techniques, and Johansen and Juselius cointegration tests and found that there is a long-term equilibrium. By using VECM Granger causality test and wavelet coherence analysis, we further explored the causal relationship between CO2 emissions and other related variables, and found that there is a two-way causal relationship between carbon dioxide emissions and renewable energy consumption in the short term. In addition, from the wavelet correlation analysis of GDP growth and CO2 emissions, it can be seen that 1992 was a turning point in Taiwan’s economic development.

The Environmental Kuznets Curve Hypothesis in Industrialized Countries: A Second Generation Econometric Approach

This study contributes to the analysis of the Environmental Kuznets hypothesis (EKC) for 31 industrialized countries during 1980-2019 using long-term static and dynamic panel data methods. According to Pesaran's CD tests, the CSD issue is present in all variables. The EKC model had a long-run relationship, according to the results of the second-generation Pesaran CIPS unit roots and Westerlund tests. The estimation results of the static model (MG) and dynamic models (CS-DL and CS-ARDL) reached the same conclusion as the reliability of the EKC hypothesis, implying that environmental pollution and economic growth are linked in an inverted N-letter shape.

To Transition to a Green Economy: Understanding World CO2 Greenhouse Gas Solutions to Climate Change

The importance of shifting to a green economy is clearly established within the UN Social Development Goal (SDG) 13. SDG 13 focuses on combating climate change and its impacts; the UN reports that over 197 parties have signed the UN document. However, the green economy definition is so broad that it encompasses all 17 SDGs. A feasible approach in this paper is to limit our discussion to CO2, which accounts for almost 75% of greenhouse gases. Methane, nitrous oxide (NOx), and fluorinated gases account for 14%, 8%, and 1% respectively. Thus, we use world data from the World Development Indicators to examine the main sources of CO2 from 1960 to 2014. We find the persistence of CO2 over the years, which indicates that most countries have failed to limit the output of CO2 and other greenhouse gases. The conclusions drawn are stronger within an econometric model relating CO2 to GDP by employing an Environmental Kuznets (EKC) model for each region of the world. NOx emissions are also discussed later in the paper as another application of the EKC model.

The effects of energy-intensive meat production on CO2 emissions: evidence from extended environmental Kuznets framework.

This study documents the positive relationship between meat production and CO2 emissions by utilizing the environmental Kuznets framework. Relationships between energy consumption, economic growth, meat production, and the levels of CO2 are tested using 6 different variables (CO2 emissions, GDP, energy consumption, forest area, total meat, and total livestock). Data for the study is related to the G7 countries and covers the period between 1961 and 2016. The analysis of the data is then conducted using a panel threshold model. Moreover, the extended EKC model does not only consider the income as the state variable but also examines the nonlinear structure inherited in other explanatory variables as a state variable. In this way, we have seen the nonlinear effects of other variables' evolution over time on carbon emission. The overall results indicate that the production of meat significantly increases CO2 emissions.

The Effectiveness of Environmental Spending in China and the Environmental Kuznets Curve

The aim of this study is to determine whether recent environmental spending in China has enabled it to reduce its emissions of greenhouse gases in the context of an Environmental Kuznets Curve-based model and promote sustainable economic development. Following the Paris Agreement in 2015, there has been a coordinated effort to reduce the consumption of fossil fuels and prevent the excessive warming of the climate. The study uses annual regional data across China and a dynamic panel data approach for estimating an EKC model which includes measures of the increased use of fossil fuels and the spending across China to reduce environmental damage. The results suggest that the policies have been effective in controlling emissions across a variety of pollutants and that the EKC tends to hold in China but varies according to the pollutant. This suggests that these policies should be continued and where possible, extended.

The impact of socio-economic institutional change on agricultural carbon dioxide emission reduction in China

With the change of social economic system and the rapid growth of agricultural economy in China, the amount of agricultural energy consumption and carbon dioxide emissions has increased dramatically. Based on the estimation of agricultural carbon dioxide emissions from 1991 to 2018 in China, this paper uses EKC model to analyze economic growth and agricultural carbon dioxide emissions. The Kaya method is used to decompose the factors affecting agricultural carbon dioxide emissions. The experimental results show that there is a co-integration relationship between economic growth and the total intensity of agricultural carbon emissions, and between economic growth and the intensity of carbon emissions caused by five types of carbon sources: fertilizer, pesticide, agricultural film, agricultural diesel oil and tillage. Economic growth is the main driving factor of agricultural carbon dioxide emissions. In addition, technological progress has a strong role in promoting carbon emission reduction, but it has a certain randomness. However, the impact of energy consumption structure and population size on carbon emissions is not obvious.

Interpretation of Economic Growth and Water Pollution Intsity Based on EKC model

Based on the extended Environmental Kuznets model (EKC) and the spatial econometric method, this paper analyzes the emission intensity data of water pollution of Chinese provinces and cities from 2004 to 2018 to identify the key factors that could result in water pollution by different periods of time and by different regions as well as to initiate discussions over potential policies to be taken in the future. The results have two implications: on the one hand, water pollution is highly spatially correlated among different Chinese regions and the economic growth indicators such as GDP per capita and the number of lights show an inverted U-shaped nonlinear relationship with the intensity of water pollution emissions. As water pollution demonstrates both leakage effect and spillover effect, it is important to strengthen the implementation strategy featuring comprehensive planning and joint prevention and control. This paper also locates the performance of each region on the EKC curve. As demonstrated in the results, Shanghai, Beijing and Tianjin have become the first ones to manage to cross the inflection point and maintain at this level. Zhejiang, Jiangsu, Shandong and other eastern coastal areas are situated in the peak of the EKC curve, with enormous emission reduction pressure. Most of the provinces in the central region are located at the left side of the peak, and are suffering from serious water pollution resulted from rapid economic growth. Meanwhile, the intensity of water pollution in the western region of China is increasing rapidly. It is integral to seize the opportunity of supply-side reform to speed up the industrial restructuring, and try not to repeat the old lesson of treatment after pollution. In conclusion, it is suggested that governments at all levels should formulate and customize their policies based on their location on the EKC curve, so as to achieve positive dynamics between economic growth and water pollution control.

An Application of Quadratic EKC model: Energy Use, Economic Development, and Environmental Quality for Thailand

This study examines the validation the relationship of environmental and energy for Thailand. Further this study examined the impact of economic growth, non-renewable and renewable energy and FDI on environment, with the help of time series data from 1990 to 2018 with ecological damage indicator, i.e., emission of carbon dioxide (CO2). This study applied Autoregressive (ARDL) Distributed Lag model for testing the cointegration in the model. In the long run, the results of this study confirm the existence of cointegration in the model. However, the negative effect of growth on the environment confirms the existence of the Kuznets Environmental Curve (EKC), which means that economic growth harms Thailand’s environment. Renewable energy and foreign direct investment are the key aspects that reduce environmental degradation in Thailand during the study period. Therefore, the government must redouble its efforts to reduce carbon dioxide CO2 emissions, perhaps through regulatory intervention or mandatory renewable energy applications for individual household and industrial segments. For example, the manufacturing sectors, iron, and steel must prioritize, reducing the high non-renewable energy consumption for those which are renewable. The government must introduce specific measures and campaigns for environmental protection for future generations as well as introduce taxes for polluters. Another relevant recommendation is to create an industry that relies on low energy consumption compared to high productivity levels.

Spatial effects of carbon emission intensity and regional development in China.

Due to the imbalance of technological level and industrial structure in regional economic development, the same carbon source can bring differentiated carbon emission levels in different regions, thus making the carbon emission show significant regional differences. In order to explore the regional differences in China's provincial carbon emission intensity and the effect of relevant influencing factors, this paper combines EKC model and STIRPAT model to conduct research. Using carbon emission intensity and other influencing factors of China's 30 provinces ranging from 2005 to 2017 to construct a panel data, the authors use exploratory spatial data analysis and Spatial Durbin Model to study the spatial effect of carbon emission intensity in China's provincial regions and the impact of different development factors on carbon emission intensity. The results show that from 2005 to 2017, China's carbon emission intensity gradually declined from east to west and from south to north. The inter-provincial carbon emission intensity of China presents an agglomeration effect in space, and the agglomeration effect gradually weakens with time. In addition, reducing energy intensity can reduce carbon emission intensity to a large extent. By optimizing industrial structure, increasing the degree of foreign trade and promoting financial development, carbon emission intensity can also be inhibited. Therefore, reducing the energy intensity of various industries and establishing inter-regional carbon emission cooperation mechanism will be effective to control the carbon emission intensity.

The use of ecological footprint in estimating the Environmental Kuznets Curve hypothesis for BRICST by considering cross-section dependence and heterogeneity

A vast body of literature estimates the impact of economic growth on environmental degradation in the framework of EKC model. Typical empirical studies proxy environmental degradation with CO2 emissions; however, this indicator does not consider the complex nature of environmental degradation. To fulfill this omission, ecological footprint that tracks the use of multiple categories of productive surface areas is used as proxy for the environment. Moreover, studies that do not consider issues of heterogeneity and cross-sectional dependence may not produce reliable outcomes. Hence, the present study re-investigates the validity of the EKC hypothesis for BRICST (Brazil, Russia, India, China, South Africa, Turkey) by using ecological footprint and considering the mentioned issues in the estimation process. Based on the annual data covering the period of 1980–2014, excluding Russia due to data unavailability, empirical results show that the EKC hypothesis is not valid, and energy intensity and energy structure are important determinants of environmental degradation. In line with the empirical outputs, possible policy suggestions are discussed in the present study.