Environmental degradation, energy consumption and sustainable development: Accounting for the role of economic complexities with evidence from World Bank income clusters

Can we live within environmental limits and still reduce poverty? Degrowth or decoupling?

The report discusses the serious environmental issues Indonesia's growing economy and rising energy use have brought about. In addition to examining government initiatives to lessen these impacts through sustainable development regulations, the goals include evaluating the connection between economic indicators and environmental results. The research employs a mixed-approaches strategy, combining quantitative and qualitative methods. The quantitative analysis, which employs time series data from 1991 to 2020, focuses on carbon dioxide emissions per capita as the dependent variable and GDP and energy consumption per capita as independent variables. Multiple linear regression using Ordinary Least Squares (OLS) evaluates these correlations. A thorough grasp of the relationship between economic growth, energy consumption, and environmental deterioration is provided by qualitative analysis, which entails a review of the literature to investigate government initiatives addressing environmental concerns. The study results show a substantial positive correlation between Indonesia's carbon dioxide (CO₂) emissions, energy consumption, and economic development. The analysis indicates that the ongoing economic activities driven by fossil fuel consumption will exacerbate environmental degradation without significant intervention, necessitating effective government policies for sustainable development and emission reduction. The study concludes that economic growth and energy consumption significantly contribute to Indonesia's environmental degradation, particularly through increased carbon dioxide (CO₂) emissions. It recommends that the government strengthen policies promoting sustainable energy use, increase investment in renewable energy technologies, and implement stricter regulations on industrial emissions. Additionally, fostering public awareness and education on environmental sustainability is crucial for effective long-term solutions.

Summary Cities, contributing more than 75% of global carbon emissions, are at the heart of climate change mitigation. Given cities' heterogeneity, they need specific low-carbon roadmaps instead of one-size-fits-all approaches. Here, we present the most detailed and up-to-date accounts of CO2 emissions for 294 cities in China and examine the extent to which their economic growth was decoupled from emissions. Results show that from 2005 to 2015, only 11% of cities exhibited strong decoupling, whereas 65.6% showed weak decoupling, and 23.4% showed no decoupling. We attribute the economic-emission decoupling in cities to several socioeconomic factors (i.e., structure and size of the economy, emission intensity, and population size) and find that the decline in emission intensity via improvement in production and carbon efficiency (e.g., decarbonizing the energy mix via building a renewable energy system) is the most important one. The experience and status quo of carbon emissions and emission-GDP (gross domestic product) decoupling in Chinese cities may have implications for other developing economies to design low-carbon development pathways.

• Improving environmental quality through reducing emissions is the central pillar of climate change mitigation and achieving sustainable development goals. • The empirical findings reveal that economic growth, energy use, urbanization, and reduced agricultural productivity increase CO 2 emissions in Bangladesh. • Several unit root tests (ADF, DF-GLS, and P-P), cointegration test (ARDL bounds test, Johansen cointegration test, and Engle-Granger cointegration test), and cointegration models (DOLS, FMOLS, CCR) have been utilized to confirm the accuracy of the results. • The findings of the study offer policymakers more detailed and helpful information for establishing successful policies in the areas of low-carbon economies, renewable energy, sustainable urban development, and climate-smart agriculture that would reduce emissions in Bangladesh. Greenhouse gases (GHGs) emissions, notably carbon dioxide (CO 2 ) emissions are causing global climate change, which poses enormous hazards to human life, the environment, development, and sustainability. Bangladesh is predominantly an agricultural country experiencing continuous economic growth and rapid urbanization which is causing higher energy consumption and CO 2 emissions. The present study empirically explores the nexus between economic growth, energy use, urbanization, agricultural productivity, and CO 2 emissions in Bangladesh. Time series data from 1972 to 2018 were utilized by employing the Dynamic Ordinary Least Squares (DOLS) approach. The Autoregressive Distributed Lag (ARDL) bounds test revealed evidence of cointegration among the variables in the long run which has been verified by the Johansen cointegration test and Engle-Granger cointegration test. The empirical findings reveal that economic growth, energy use, urbanization, and reduced agricultural productivity increase CO 2 emissions in Bangladesh. The estimated results are robust to alternative estimators such as fully modified least squares (FMOLS), and canonical cointegrating regression (CCR). In addition, the pairwise Granger causality test is utilized to capture the causal linkage between the variables. This study adds to the current body of knowledge by shining light on the factors that contribute to environmental degradation in Bangladesh. This article put forward policy recommendations aimed at sustainable development by establishing strong regulatory policy instruments to reduce environmental degradation.

Effectively addressing today’s energy challenges requires advanced technologies along with policies that influence economic markets while advancing the public good.

Causal Relationship between Energy Consumption and GDP Growth Revisited: A Dynamic Panel Data Approach

Causal relationship between energy consumption and GDP growth revisited: A dynamic panel data approach

• The research tries to identify heterogeneity in carbon dioxide emissions, energy use, and GDP growth paths among BRICS nations and further explores using a technique of cointegration between the long-run relationship of these variables. • The current study has used theoretical, empirical and traditional approaches of literature review to find out the research gap. These exploratory literature reviews are identified through keyword searches and using text analytics. Text analytics is an artificial intelligence technique for doing a literature review. Text analytics means a systematic approach to analyzing and extracting information from unstructured text data, formed the cornerstone of the analytical process. • The study employs secondary data obtained from World Development Indicators and panel data analysis to examine the interplay of the variables over the period 2009-2022. The analysis utilizes some of the following variables, that is, CO2 emissions per capita in metric tons, GDP per capita, and energy consumption per capita in oil equivalent. The techniques that will be utilized include those associated with the literature review (text analytics techniques) and other panel data models used for the data analysis such as Pooled Ordinary Least Squares (OLS), Breusch-Pagan Lagrange Multiplier (BP) test, Random Effects Model (REM), Fixed Effects Model (FEM), and Hausman test. The study also applies the first-generation panel unit root test known as IPS to determine data stationarity, cross-sectional dependency, serial correlation, heteroscedasticity, Pedroni cointegration tests, and the Dumitrescu-Hurlin Granger causality test to check causality. • The findings are that there is no heterogeneity in the dispersion of CO2 emissions, energy consumption, and GDP growth across the BRICS countries. The cointegration tests further reveal the long-run relationship between these variables. This study looks finally for interlinkages between CO2 emissions, economic growth, and energy consumption for BRICS countries. Using an approach with panel data analysis, it contributes to ongoing policy debates on sustainable development and offers guidelines to policymakers in terms of reaching an expedient balance between economic growth and the preservation of the environment. The BRICS nations are now undergoing rapid economic growth, which has led to apprehensions over the increase in CO2 emissions and energy consumption. The research tries to identify heterogeneity in carbon dioxide emissions, energy use, and GDP growth paths among BRICS nations and further explores using a technique of cointegration between the long-run relationship of these variables. The study employs secondary data obtained from World Development Indicators and panel data analysis to examine the interplay of the variables over the period 2009-2022. The analysis utilizes some of the following variables, that is, CO2 emissions per capita in metric tons, GDP per capita, and energy consumption per capita in oil equivalent. The techniques that will be utilized include those associated with the literature review (text analytics techniques) and other panel data models used for the data analysis, such as Pooled Ordinary Least Squares (OLS), Breusch-Pagan Lagrange Multiplier (BP) test, Random Effects Model (REM), Fixed Effects Model (FEM), and Hausman test. The study also applies the first-generation panel unit root test known as IPS to determine data stationarity, cross-sectional dependency, serial correlation, heteroscedasticity, Pedroni cointegration tests, and the Dumitrescu-Hurlin Granger causality test to check causality. The findings are that there is no heterogeneity in the dispersion of CO2 emissions, energy consumption, and GDP growth across the BRICS countries. The cointegration tests further reveal the long-run relationship between these variables. This study finally looks for interlinkages between CO2 emissions, economic growth, and energy consumption for BRICS countries. Using an approach with panel data analysis, it contributes to ongoing policy debates on sustainable development and offers guidelines to policymakers in terms of reaching an expedient balance between economic growth and the preservation of the environment.

One of the primary difficulties we have recently is environmental degradation. The deterioration of the environment was visible in the rise in carbon dioxide emissions, which has a detrimental impact on various life matters. A variety of factors caused this growth. Inappropriate human behaviors caused the majority of them. This study aimed to ascertain how energy consumption and economic growth with its components in the Czech Republic, affected CO2 emissions. The relationship between CO2 emissions, economic growth, agriculture, and energy consumption was studied using econometric analysis, specifically the Johansen, Vector Error Correction (VEC) Model, and granger causality. The findings revealed that all variables are cointegrated. Economic growth, agricultural, and energy consumption output are all positively correlated with CO2 emissions. There is a unidirectional Granger Causality between economic growth, and Agriculture towards carbon dioxide emissions. A unidirectional Granger Causality agriculture towards economic growth, and energy consumption. In addition, there is no Granger Causality between energy consumption and CO2 emissions, and economic growth. This is the first study to use the most recent data to empirically evaluate the environmental impact of economic growth and energy use in the Czech Republic. This study includes pertinent advice for reducing emission ns and supporting the environment by increasing renewable energy sources and adhering to the Czech Ministry of Environment’s strategy.

Air pollution, global greenhouse gases (GHG), water pollution and water resources degradation are among the most serious environmental concerns that encounter the Qatar country. In nowadays, it is commonly known that the effects of environment degradation exceed its direct negative impacts on climate changes to cover its impacts on Human health, nation livelihood and cultural integrity. So, we advocate that understanding and determining factors explaining environmental degradation remain an important question of research. Moreover, by determining factors that explain environment degradation, policymakers, researchers and international institutions can help on recommending the adequate economic policies that can improve the environment quality and the live standing of inhabitants. In the empirical literature, the Environmental Kuznets Curve (EKC) is the most powerful tool used to investigate the relationship between environment degradation and some macroeconomics and financial variables. Following the EKC hypothesis, the relationship between economic growth and environment degradation is inverted-U shaped. From the economic perspective, this means that initially economic growth increases environment degradation and then declines it after a threshold point of income per capita. More specifically, at initial level of economic growth, an increase in income is linked with an increase in energy consumption that raises environment degradation. After reaching a critical level of income, the spending on environment protection is increased, and hence environment degradation tend to decrease. From an econometrical or statistical perspectives, the EKC hypothesis have been firstly tested using the basic EKC equation which relies the environment degradation proxy to the real GDP and to a nonlinear term of the real GDP (the squared real GDP). If the EKC hypothesis holds then the real GDP and the squared real GDP have respectively a positive and negative signs. This EKC hypothesis has been firstly introduced by Kuznets (1955) when examining the relationship between economic growth and income inequality which shows that this relationship is inverted U-shaped. Grossman and Krueger (1995) are the first to examine this relationship between environment degradation and economic growth in their seminal paper published on the Quarterly Journal of Economics. They found that this relationship is inverted U-shaped which validates the EKC hypothesis. Empirically, until now no consensus has been reached about the true nature of the relation between real GDP and environment degradation. Evidence for the EKC hypothesis is very mixed. Overall, the results seem to depend in many factors including the specification, the pollutants and the econometrics technique used. First, empirical studies show that the results in term of positive and negative relationships as well as in term of magnitude differ significantly for the same country depend on the specification studied, linear, quadratic or cubic. Moreover, the inclusion of other factors in the right hand of the regression such as urbanization, trade openness, financial development and political stability have a significant impact on the magnitude of the income per capita variables coefficients. Second, the results differ significantly following the environment degradation proxy used. For instance, Horvath (1997) and Holtz-Eakin and Selden (1995) suggest that the use of global pollutants leads to continuously rise the levels of environment degradation or to a high levels of income per capita turning point, see also Esteve and Tamarit (2011). Third, the results also seem to depend in the econometric approach employed. In this paper, we investigate the case of the Qatar economy for several reasons. First, Qatar 2030 vision has given a high importance to questions related to air pollution, climate change and their impacts on economic sustainability. Second, the rapid increase of economic growth of the Qatar economy in the last two decades has been accompanied with an increase in energy consumption, urbanization and international trade. These factors are among the most important factors largely used in theoretical and empirical literature to explain environment degradation. Third, following the world health organization (WHO), local air pollution levels in Qatar has frequently exceeded recommended levels and are more time higher than the international standards. In fact, compared to the WHO's standards for PM10 for the 24-hour average and for the annual average concentration of 50 ug/m 3 and 20 ug/m 3 the Qatar's national air quality standards are far from these values. For instance, the values for PM10 is around 150 ug/m 3 for 24 hours average concentration and to 50 ug/m 3 for the annual average concentration. The data set used in this paper consists on macroeconomics and financial data, including CO 2 emissions, ecological foot print, real GDP per capita, energy use, urbanization, financial development and openness trade, to investigate the EKC hypothesis for the Qatar economy. All the dataset except the ecological foot print variable are collected from the world Bank's development indicators (WDI). The ecological footprint data is obtained from the National Footprint Accounts (NFAs) of the Global Footprint Network. This variable is employed as second proxy of environment quality measures. This data set used is a quarterly data and covers the period 1975Q1 to 2007Q4 for variables used for ecological footprint equation and covers the periods 1980Q1 to 2010Q4 for the CO 2 emissions equations variables. This paper contributes to the empirical literature of the EKC hypothesis in many ways. First, to our knowledge this paper is the first to consider the case of the Qatar economy as a single country to test the EKC hypothesis as well as the different directions of causality between variables. Second, in addition to the CO 2 emissions largely employed in the empirical literature, in this paper we employ also the ecological footprint as a new proxy of environmental degradation. Third, we use recent development of cointegration approach with structural breaks which is also rarely used for the case of EKC hypothesis. As tests of cointegration with shifts in the cointegration vector, we use the Gregory and Hansen (1996), Hatemi-J (2008) and to investigate the causal relationship between all variables using standard Granger causality tests. Fourth, to our knowledge this paper is the first study that uses Markov Switching Equilibrium Correction Model with shifts in both the intercept and the income per capita coefficient for the long run relationship between environment degradation and its key determinants. The empirical findings of this paper are useful for Qatari policymakers and especially for the ministry of environment of the Qatar government. Moreover, economic implications and economic policy are proposed and discussed. [1] P.O.Box: 2713-Doha-Qatar. Email: lcharfeddine@qu.edu.qa. Office: (+974) 4403-7764(+974) 4403-7764, Fax: (+974) 4403-5081. 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The dampening effect of geopolitical risk and economic policy uncertainty in the linkage between economic complexity and environmental degradation in the G-20

Global climate change caused by Greenhouse Gases (GHGs), particularly carbon dioxide (CO2) emissions, poses incomparable threats to the environment, development and sustainability. Vietnam is experiencing continuous economic growth and agricultural advancement, which causes higher energy consumption and CO2 emissions. Understanding Vietnam’s sensitivity to climate change is becoming more crucial for governments trying to reconcile climate change mitigation and sustainable development. Analyzing pollution-development trade-offs can help minimize environmental degradation in Vietnam. Therefore, the present study empirically investigated the nexus between economic growth, energy use, agricultural added value and CO2 emissions in Vietnam. To investigate the short-run and long-run relationships between the variables, this study employed the autoregressive distributed lag (ARDL) technique and the Vector Error Correction Model (VECM) using the time series data from 1984 to 2020 for Vietnam. The empirical findings indicated that economic growth and energy use trigger environmental degradation by increasing CO2 emissions, whereas enhancing agricultural added value improves Vietnam’s environmental quality by reducing CO2 emissions in both the long-run and short-run. The estimated results are robust compared with alternative estimators such as dynamic ordinary least squares (DOLS), fully modified least squares (FMOLS), and canonical cointegrating regression (CCR). This research contributes to the existing literature by shedding light on the potential of agricultural added value to reduce emissions in Vietnam and provides policy recommendations in areas of low-carbon economy, promoting renewable energy, and sustainable agriculture that can reduce CO2 emissions in Vietnam.

Exploring the nexuses between nuclear energy, renewable energy, and carbon dioxide emissions: The role of economic complexity in the G7 countries

This study aims to analyze the influence of energy consumption, economic growth, and trade openness on carbon emissions in Indonesia. The research issue arises from the significant increase in Indonesia's carbon emissions over the past two decades, which has contributed to climate change, environmental degradation, and various sustainability challenges. As one of the developing countries with rapid economic growth, Indonesia faces the dual challenge of maintaining economic expansion while reducing environmental pressure. To address this issue, the study applies a quantitative approach using the Partial Adjustment Model (PAM) regression technique to examine the dynamic relationship between the selected variables. The analysis is based on annual time series data from 2003 to 2023, obtained from credible sources such as Statistics Indonesia (BPS), the World Bank, and the International Energy Agency (IEA). The findings reveal that energy consumption has a negative and statistically significant effect on carbon emissions, indicating an improvement in energy efficiency and a gradual transition towards renewable energy sources. Meanwhile, economic growth has a positive and significant impact on carbon emissions, suggesting that Indonesia's economic activities remain highly dependent on fossil fuels. In contrast, trade openness shows a positive but insignificant effect on carbon emissions. Overall, the study underscores the urgent need for integrated policies promoting green energy transition, sustainable trade, and low-carbon economic strategies to achieve environmentally responsible and sustainable long-term growth in Indonesia. Keywords: Carbon Emissions, Energy Consumption, Trade Openness, Economic Growth, PAM

Developing countries are constantly facing the problem of environmental degradation. Environmental degradation is caused by the consumption of non-renewable energy for economic growth, but the consequences of environmental degradation cannot be ignored. The main purpose of this study is to investigate the relationship between three variables (i.e., energy use greenization, CO2 emission, and economic growth) in the case of China using simultaneous equation modeling techniques and data for the period 2000–2018. The results indicate that (1) there is a long-term equilibrium relationship between energy use greenization, carbon emissions, and economic growth in China. Energy use greenization not only reduces carbon dioxide emissions but also promotes sustainable economic growth in China. (2) Carbon emissions and economic growth have promoted energy use greenization, indicating that the pressures of environmental climate and economic transformation in China have forced energy use greenization to a certain extent. (3) The contribution rate of energy use greenization to economic growth shows an inverted U-shaped trend that rises first and then decreases subsequently, while carbon emissions have a relatively large contribution rate to green energy use and economic growth. These results have far-reaching policy directions for the environmental sustainability goals of the Chinese economy.