Testing the agriculture-induced Environmental Kuznets Curve with moderation effect of human capital and renewable energy: insights from BRICS economies.

The surge in economic growth and increased agricultural output can augment societal well-being whilst proliferating environmental stressors. So, the study tests the validity of the "agriculture-induced Environmental Kuznets Curve hypothesis" (AEKC) by assessing the varied environmental proxies that have yet to be accounted for earlier in the case of BRICS economies. Furthermore, most studies have utilised "first-generation econometric approaches" as the "cross-sectional dependency" has not been deemed in estimation. On account of this, the research employed "second-generation CIPS and CADF unit root test", "Westerlund cointegration test", "fully modified ordinary least square" (FMOLS) and "dynamic ordinary least square" (DOLS) to test the validity of AEKC in "BRICS countries" for 30 years. A positive association between agriculture and "ecological footprint" has been found which evidences the presence of an "inverted U-shaped AEKC" in BRICS nations. Another finding shows that the favourable impact of agriculture towards climate change can be moderated by illustrating the interaction effect of "human capital" and "renewable energy" with "agriculture". Lastly, the investigation brings forth the policy repercussions and acumens for the BRICS governments and policymakers in halting climate change by using renewable energy in agriculture and building human capital.

Examining the dynamic impact of carbon emissions, renewable energy and economic growth on healthcare expenditure in Asian countries.

This study aims to examine the impact of renewable energy, carbon emissions, and economic growth on healthcare spending in 36 Asian countries during 2000-2019. Fully Modified Ordinary Least Square (FMOLS) and Dynamic Ordinary Least Square (DOLS) models have been applied to the panel data for 36 Asian countries. The study's findings show that CO2 emissions in Asia increased due to public and private health spending, with the commercial health sector having a larger negative influence on CO2 emissions than the public sector. According to FMOLS and DOLS findings, carbon emissions and GDP are positively related to health spending, indicating that high economic growth through energy-intensive production processes leads to increased carbon emissions, but on the contrary, renewable energy consumption has decreased healthcare expenditure. This study advocates new policies to reduce carbon emissions and hospitalisation without jeopardising national economic growth. In order to achieve sustainable health services and an environmentally friendly future in Asia, health administrators must raise state and private healthcare spending while implementing an effective cost-service and energy-efficient management plan.

Catalyzing sustainable development: Exploring the interplay between access to clean water, sanitation, renewable energy and electricity services in shaping China's energy, economic growth, and environmental landscape.

The Sustainable Development Goals (SDGs) reflect the shift in global economic conversation toward inclusive growth. The growth can promote inclusivity and widespread sharing of its advancements by concentrating on four key dimensions. (a) Equality of opportunity, (b) sharing prosperity, (3) environmental sustainability/climate adaptation, and (4) macroeconomic stability. We used the Kao cointegration test to study how certain variables are connected over a long period. The relationship between CO2 and GDP per capita, renewable energy and tourism, improved water and sanitation, and access to power all have a positive feedback effect on each other. Based on FMOLS's findings, a 1 % increase in Inclusive growth leads to a 0.342 % (Model 1) and 0.258 % (Model 3) increase in CO2 emissions. An increase of 1 percent in energy consumption per person resulted in a rise of 1.343 % in CO2 emissions in Case 1, 0.524 % in Case 2, and 0.618 % in Case 3. Increasing the tourism sector's proportion of total exports by just one percent will reduce CO2 emissions by 0.221 % (case 1) and 0.234 % (case 3). Based on CCR findings, a 1 % improvement in inclusive growth leads to a 0.403.

Does the individual effect of resource rents imperative in the attainment of environmental sustainability? Evidence of Southeast Asian economies.

This study investigates the impact of natural resource exploitation on environmental sustainability in Southeast Asian economies, while testing the Environmental Kuznets Curve (EKC) inverted U-shaped hypothesis, a model which suggests an initial increase in environmental degradation with economic growth followed by a decrease at a certain level of income. Utilizing World Development Indicators data from 1995 to 2018, the research dissects the long-term influence of various resource rents, namely coal, oil, and forest. The research highlights the indispensable role of renewable energy in maintaining ecological balance. Results indicate that while coal rent exacerbates environmental degradation, forest and oil rents prove eco-friendly, although this is only confirmed in fully modified OLS estimation. The study underscores the importance of forest rents in achieving environmental sustainability. Renewable energy emerges as vital for promoting sustainable low-carbon practices. In line with the EKC hypothesis, the study finds that economic growth initially increases carbon emissions, but eventually reduces them. It calls for appropriate measures to manage resource exploitation, ensure renewable energy availability, alleviate energy poverty, and curb deforestation, thereby mitigating ecological damage.

How to lead on carbon neutrality through sustainable development: A perspective on renewable energy, Information and Communication Technology (ICT), and logistics networks.

In the face of intensifying climate change-induced environmental problems, understanding the causal relationship between carbon dioxide (CO2) emissions and socioeconomic factors is crucial for achieving sustainable development. This study investigates how the causal relationships between renewable energy, information and communication technology (ICT), logistics networks, economic growth, industrialization, and energy intensity impact sustainable development using a panel dataset drawn from 104 countries and covering 2006 to 2019. Methodologically, panel unit root, panel co-integration, and Granger causality tests are employed as robust econometric techniques. The results of the panel unit root and co-integration tests confirm the stationarity of the variables and reveal significant long-term relationships among them throughout the empirical analysis period. Notably, the panel FMOLS and DOLS estimates indicate a positive effect of RE and ICT on reducing CO2 emissions, whereas GDP and energy intensity have a negative impact on CO2 emissions reduction. Moreover, the pairwise Granger causality test findings indicate bidirectional causal relationships between RE and CO2, IND and CO2, ICT and RE, IND and RE, GDP and ICT, as well as IND and ICT. The study recommends providing policy support, including for technological development and innovation, towards establishing a system that fosters sustainable development.

Russia-Ukraine war impacts on climate initiatives and sustainable development objectives in top European gas importers.

Russia holds the position of being the third largest global producer of oil and plays a significant role in the supply of oil and gas to Europe. The ongoing war conflict has the potential to impede the bilateral and multilateral relations between Russia and Europe. The ramifications of this event will have notable reverberations for environmental endeavors in Europe. The aforementioned premise forms the basis of our investigation, wherein we scrutinize the correlation among oil price, coal price, gas price, economic growth, and coal consumption, while taking into account the ramifications of the Russian-Ukrainian conflict. We adopted fully "modified ordinary least square (FMOLS), dynamic ordinary least square (DOLS), and canonical cointegration regression (CCR)" econometric techniques to gauge the nexus between factors of interest in the top 4 European Russian gas importer economies (Poland, Netherland, Hungry, and Germany). The empirical outcomes reveal substantial negative impact of economic growth and coal price elasticity on the coal consumption. On the contrary, oil and gas price elasticities depict significant positive influence on the coal consumption. Hence, this study concludes that a rise in oil and gas prices leads to an increase in coal consumption, which in turn negatively impacts environmental quality. Furthermore, the occurrence of war has the potential to impede the utilization of coal resources in Netherlands and Hungary. On the other hand, the impact of war is noteworthy and constructive in Poland and Germany. Thus, war results ecological imbalance in Poland and Germany in particular. Governments, decision-makers, stakeholders, and environmentalists must develop a long-term plan that calls for a paradigm shift away from gas, oil, and coal usage and toward more environmentally benign renewable energy sources.

Does information and communication technologies affect economic complexity?

Information and communication technology (ICT) and economic complexity are two concepts that have been extensively used in the recent literature. However, studies linking these two concepts are still at a premature stage and few existing studies have focussed on the role of the internet in a short-term context. Indeed, ICT measures the percentage of the population with access to the internet while economic complexity quantifies the set of productive capabilities and know-how embedded in the production process. This study aims to examine for the first time the long-term effect of ICT (quality and quantity) on economic complexity in a large panel of 112 countries over the period 1986-2017. The detailed analysis explores the long run and directional relationships using the homogeneity test, the cross-sectional dependence test, stationary tests in the presence of cross-sectional dependence, the panel cointegration test, dynamic OLS (DOLS), fully modified OLS (FMOLS), and the Granger panel causality test. The study finds long-run relationships between ICT, economic complexity, per capita GDP, government spending, and natural resources. Cointegration regression shows that the quality and especially the quantity of ICT, economic growth, and government spending have a positive and significant effect on economic complexity in the long run. Similarly, the results show that natural resource rent significantly impedes economic complexity. Finally, the results of the Granger causality test confirm the existence of a bidirectional relationship between ICT and economic complexity. Supplementary Information: The online version contains supplementary material available at 10.1007/s43546-023-00467-8.

The Environmental Philips Curve from a gender perspective: empirical evidence from India.

The trade-off between environmental degradation and unemployment has been recently termed as Environmental Philips Curve (EPC). This research attempts to investigate the presence of EPC in the Indian context utilizing time series data for the period 1990-2019. Besides contributing to the meagre empirical literature on this issue, the present study makes a novel contribution by introducing a gender dimension to this investigation. In particular, this study investigates whether the nexus between environmental degradation and unemployment is different for men and women. We examine the presence of the EPC by estimating a model that considers growth in CO2 emission as a function of economic growth, trade openness, and gender segregated unemployment rates. Our findings based on autoregressive distributed lag, fully modified ordinary least squares, and dynamic ordinary least squares estimators generate robust evidence for a negative impact of male unemployment rate on growth in CO2 emission that validates the existence of the Environmental Philips Curve for the male unemployment rate. However, there is no trade-off between environmental quality and women's employment. In fact, the results point to a favourable effect of reduction in female unemployment on environmental quality. The results of the Block Exogeneity test indicate a unidirectional causality from male unemployment rate to environmental degradation. However, a bidirectional causal relationship exists between female unemployment and environmental degradation. The existence of a trade-off between environmental quality and male employment suggests that India is yet to find viable technologies that can curtail pollution without compromising its livelihood. An optimistic conclusion emanating from our findings is the existence of a virtuous cycle between female employment and environmental quality. An integrated approach to improve environmental quality and increase women's economic activity may facilitate a speedy realization of sustainable development goals for India as both the goals complement and reinforce each other.

Do anthropogenic and natural factors elevate the haze pollution in the South Asian countries? Evidence from long-term cointegration and VECM causality estimation.

Anthropogenic and natural factors lead to substantial environmental degradation. This shift is aligned with the country's overall development, resulting in high demand for energy resources and a dramatic shift in human activities that contribute to haze pollution. Some of the countries in the South Asian region are ranked between one and twenty on the list of countries with the highest levels of PM2.5 pollution. The member countries have taken many steps to tackle global warming, but concern about haze pollution was found limited. Moreover, very little research was conducted on haze pollution, which led us to conduct this research in this region. This study used the panel data from 1998 to 2018 and a set of econometric models like long-term cointegrating relationship, fully modified ordinary least squares, and vector error-correction model Granger causality tests to examine the major drivers like anthropogenic and natural factors that might elevate haze pollution. Furthermore, our empirical results depict that (1) there is a long-term cointegrating relation between haze and the factors studied. (2) Energy consumption, urbanisation, and economic growth are the primary drivers of environmental degradation. (3) Rainfall has the most substantial influence on reducing haze pollution. The study concluded that (a) if the countries continue to develop at the same pace, all factors studied will continue to drive haze pollution to rise. (b) A decrease in PM2.5 pollution requires improvements in regional rainfall through vegetation, reducing reliance on fossil fuel-based energy sources, and increasing environmental education. (c) Slowing down the drive for urbanisation would not be cost-effective in reducing haze pollution in the region in the short run. Thus, reducing haze by adjusting the factors studied would not be easy in the short run and require the careful adoption of long-term policies.

What does the EKC theory leave behind? A state-of-the-art review and assessment of export diversification-augmented models.

Over the past three decades, researchers have extensively examined the environmental Kuznets curve (EKC) hypothesis. Despite their early focus on the ecological impacts of anthropogenic development, associated conclusions differ and often conflict. In this study, we conducted a state-of-the-art review of this topic and shed light on the methodological challenges that the literature attempted to overcome so far. Since China is going through structural economic changes and environmental reforms, we relied on this illustrative case and developed an augmented-EKC framework to investigate whether this hypothesis holds between export product diversification and environmental pollution, stratifying by carbon energy content: renewable (Model 1) and fossil energy (Model 2). Quarterly data are collected over the most available and recent period (i.e., 1990Q1-2018Q4) and computed by applying the Quadratic Match-Sum Method (QMS) on annual series. Besides, per capita income and foreign direct investments are included as additional factors to the baseline models specifications. The empirical analysis comprises the Clemente-Montanes-Reyes unit root test with structural break and additive outlier, the autoregressive distributed lag (ARDL) bounds test for cointegration, the Granger causality test, and dynamic (DOLS) and fully modified OLS (FMOLS) estimators, followed by robustness checks confirming the stability of the coefficients exhibited in the two autoregressive settings. For both models, empirical results failed to support the existence of an inverted-U-shaped relationship among export product diversification and carbon release from fuel combustion in China. Also, as income grows, low-carbon resources seem improving export diversification and vice versa. Related findings are thought to bring robust inferences able to complement the existing literature and open a fruitful research direction.

Globalization toward environmental sustainability and electricity consumption to environmental degradation: does EKC inverted U-shaped hypothesis exist between squared economic growth and CO2 emissions in top globalized economies.

The study inspects the inverted U shape of the environmental Kuznets curve (EKC) hypothesis following the influence of economic growth on CO2 emissions and the reaction of electricity consumption and globalization toward CO2 emissions in top globalized economies. This study has taken the data of the top 9 globalized countries from 1990 to 2019 while adopting fully modified ordinary least squares and dynamic ordinary least squares panel cointegration approaches to determine the long run effects and Dumitrescu and Hurlin panel causality for the directions of the causality among the variables. According to the long-term findings of the research, economic growth and electricity consumption substantially contribute to CO2 secretions. On the other hand, the squared growth and globalization mitigate CO2 emissions and contribute to environmental sustainability. However, the inverse influence of squared growth on CO2 emissions shows the presence of the inverted U shape of the EKC hypothesis. Furthermore, Dumitrescu and Hurlin causality measures have shown the bi-directional causality of electricity consumption and economic growth with CO2 emissions and globalization with economic growth. At the same time, unidirectional causality exists from globalization to CO2 emissions, economic growth to electricity consumption, and electricity consumption to globalization. The study recommends long-term globalization and sustainable development projects to ensure environmental sustainability in these globalized economies.

Analyzing the role of meteorological parameters and CO2 emissions towards crop production: empirical evidence from South Asian countries.

It is need of the hour to investigate the impacts of climate parameters on agricultural production in a developing region of South Asia. Therefore, this work attempts to explore the climatic indicators on agricultural production for selected South Asian countries over the annual data of 1961-2016. This study estimates the impacts of rainfall, temperature, rural population, land under cereal production, and CO2 emissions (ECO2) on agricultural production. For empirical analysis, we applied second-generation unit root tests. After examining the order of integration of time series, we check for the co-integration among the variables. Before the co-integration test, we check for cross-section dependence among the variables. CD and LM tests confirm the existence of cross-section dependence. Afterward, we apply the Westerlund co-integration test to confirm the strong association among the variables. Further, we applied two methods for long-run coefficients of independent variables. Dynamic ordinary least square (DOLS) and fully modified ordinary least square (FMOLS) tests were applied to cross-check the findings. Our findings show that rural population and rainfall are negatively associated with agricultural production. Moreover, temperature, land area under cereal production, and ECO2 are positively associated with agricultural production. Our findings shed light on some important policy implications for South Asian countries.

How does economic complexity affect ecological footprint in G-7 economies: the role of renewable and non-renewable energy consumptions and testing EKC hypothesis.

The discussion concerning whether and how economic complexity (ECI) affects ecological footprint (EFP) has gained researchers' consideration, while there are slight empirical evidence to support the subject matter. In the support of theoretical argument, this study provides empirical evidence by investigating the impact of ECI on EFP along with the role of disaggregated energy consumptions by using a panel dataset of G-7 economies between 1996 and 2019. To this end, we applied panel techniques of Fully-Modify OLS and Dynamic-OLS models for cointegration analysis. The results obtained from Fully-Modify OLS and Dynamic-OLS models reveal that ECI deteriorates environmental quality by increasing EFP, while renewable energy reduces ecological pollution by decreasing EFP. In addition, the increasing demand for non-renewable energy and economic growth both degrades environmental quality in G-7 countries. More interestingly, the non-linear (ECI2) relationship between ECI and EFP confirms a U-shaped association (EKC hypothesis), which suggests that after achieving a certain threshold level, economic complexity mitigates environmental degradation in G-7 economies. The empirical results also suggest that other control variables such as population growth, inflation rate, foreign direct investment, and total trade intensity lead to environmental degradation by increasing ecological footprint. Based on empirical results, the following important policy implications are drawn; first, G-7 economies should speed up the level of economic complexity along with renewable energy consumption to protect environmental quality and maintain sustainable growth and development. Secondly, the governments of G-7 countries should introduce greener technologies and promote production that are environmental friendly for drastic reduction in environmental unsustainability.

What causes environmental degradation in Pakistan? Embossing the role of fossil fuel energy consumption in the view of ecological footprint.

For decades, environmental degradation has become a universal challenge, and for sustainable environment quality, a true and broader proxy is vital. Pakistan is an ecological deficient country in the world, being the sixth-largest economy (population-wise). This study investigates the prime sources of environmental degradation through ecological footprint in Pakistan. The yearly time-series data spanning 1972 to 2020 is utilized for a set of regressors as fossil fuel energy consumption, trade openness, arable land, industrial share to GDP, economic growth, and population growth. We use various econometric techniques, the bounds test, ARDL (short and long run) model, FMOLS, and Granger causality test. Bounds test confirms the existence of cointegration among variables included in our model. The ARDL estimates suggest that fossil fuel energy consumption, trade openness, and population growth are the leading factors affecting the environment. Fossil fuel consumption and population growth significantly damage the environment in the short and long run. Contrasting to that, trade openness is substantial to the environment quality. The FMOLS approves the robustness of the cointegrating findings. Moreover, a unidirectional causal relationship from economic growth to the ecological footprint (GDP → EFP). And also, the ecological footprint of arable land (EFP → AL) is witnessed. At the same time, bidirectional causality is found between growth rate and fossil energy consumption (GDP ↔ FEC). Lastly, we recommend some policy options to improve environmental quality in Pakistan.

A district-level analysis for measuring the effects of climate change on production of agricultural crops, i.e., wheat and paddy: evidence from India.

The present study aims to examine the impact of climate change on wheat and rice yield in Punjab, India, during 1981-2017. The study employs fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), and pooled mean group (PMG) approaches. The Pedroni cointegration has established a long-run relationship of climate variables with rice and wheat crops. FMOLS and DOLS models show that minimum temperature has a positive effect on both wheat and rice. In contrast, the maximum temperature is found to be negatively contributing to both crops. Rainfall has a significant adverse impact on the production of wheat. In the study period, seasonal rainfall has been found detrimental for the production of wheat and rice crops, indicating that excess rainfall proved counterproductive. Moreover, the Dumitrescu-Hurlin causality test has revealed a unidirectional causality running from minimum temperature, rainfall, and maximum temperature for rice and wheat production. The findings of the study suggest that the government should invest in developing stress-tolerant varieties of wheat and rice, managing crop residuals to curb other environmental effects, and sustaining natural resources for ensuring food security.

Biomass energy consumption and its impacts on ecological footprints: analyzing the role of globalization and natural resources in the framework of EKC in SAARC countries.

Research scholars have diverted their attention towards the effect of biomass energy use on ecological footprints. Although recent research has investigated this association, the link between ecological footprints and biomass energy consumption has not provided consistent results. Therefore, this research attempts to fill the gap by examining the ecological footprints-biomass energy consumption nexus in the context of environmental Kuznets curve over the period of 1990-2016 in South Asian Association for Regional Corporation (SAARC) countries. Moreover, this work incorporates globalization, natural resources, and economic growth (GDP) for empirical analysis. In doing empirical analysis, we applied some econometric analysis to deal with the issue of cross-sectional dependence in the data. The outcomes of fully modified ordinary least squares and dynamic ordinary least squares estimations show that biomass energy consumption increases ecological footprints in SAARC countries. Moreover, globalization and GDP are also increasing ecological footprints. Environmental Kuznets curve cannot be validated in estimated countries. The Dumitrescu-Hurlin causality test confirms one-way causality from biomass energy usage to ecological footprints. On the base of empirical results, several policy implications are suggested for SAARC countries.

Climate change and major crop production: evidence from Pakistan.

Climatic changes are posing serious threats to crop production and food insecurity across the globe. This study explores the dynamic relationship between changing annual temperature and production of major crops such as wheat, rice, bajra, jowar, maize, barley, gram, sugar cane, mastered oil, and cotton in Pakistan from 2000 to 2019 through an eclectic production model. The estimated result of panel econometric analysis revealed a significant negative effect of rising temperature on selected crop production in the long run with an insignificant impact in the short run. Among other explanatory variables, the area under cultivation and fertilizer input have significant positive effects in both the long run and the short run. Improved quality seeds revealed insignificant effects and urging authorities to enhance quality research to develop climate change resilient crops. This study urges Pakistan to improve agriculture technology along with adopting other greenhouse gas mitigation, such as forestation and clean energy, and water conservation policies.

Does energy innovation play a role in achieving sustainable development goals in BRICS countries?

It is widely discussed that greenhouse gases (GHGs) are the main culprit behind global warming. The conventional energy sources (oil, coal, and gas) mainly realize GHGs in the atmosphere. Due to this, the world's countries are switching towards clean energy sources and investing more in projects related to innovation in the energy sector. Thus, this study investigates the role of energy innovation in combating GHGs emissions by taking the environmental Kuznets curve for BRICS economies. The FMOLS and DOLS estimators are employed throughout 1996-2016. The findings documented that energy innovation plays an important role in mitigating GHGs emissions. Moreover, the result strongly approves the EKC hypothesis for BRICS countries in the significance of energy innovation. Finally, it is recommended that expanding the public budget in energy R&D expenditures can help to reduce GHG emissions and promote sustainable growth in BRICS countries.

Role of political risk to achieve carbon neutrality: Evidence from Brazil.

The current research assesses the impact of political risk on carbon dioxide (CO2) emissions in Brazil while controlling the role of financial development, GDP growth, trade openness, and technological innovation. In doing so, the quarterly dataset from 1990 to 2018 is utilized with Bayer and Hanck cointegration, dynamic ordinary least square (DOLS) and canonical correlation regression (CCR), and frequency-domain causality tests. The cointegration test revealed a long-run association amongst the variables of interest. Furthermore, the outcomes from the DOLS and CCR revealed that increasing financial development, technological innovation, trade openness, and real growth increase CO2 emissions while a better political environment reduces environmental pollution.

Study on the long-term impact of economic globalization and population aging on CO2 emissions in OECD countries.

Both economic globalization and population aging have given rise to changes in environmental quality, but the research that integrates these two crucial factors into the same environment policy framework is still a blank. Therefore, using panel data of the Organization for Economic Cooperation and Development (OECD) over the period 1971-2016, this study examines the long-term impact of economic globalization and population aging on CO2 emissions. First, second-generation panel regression approaches are employed to verify the panel data, including unit root tests, cointegration tests and causality tests. Next, Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) are respectively used for empirical analysis of the long-term impact between variables. The augmented mean group (AMG) is also applied to ascertain the robustness results of the estimation coefficients. Finally, using Dumitrescu and Hurlin non-causality test to examine the causal associations between variables to avoid the contingency of the results. The overall results show that economic globalization and population aging decrease the long-term CO2 emissions. The inverted U-shaped relationship between economic growth and environmental pollution confirms the effectiveness of the Environmental Kuznets Curve (EKC) in OECD countries. In addition, unidirectional causal relationships have been found from economic globalization and population aging to CO2 emissions in this study. Policy suggestions in response to these findings are discussed.