Augmented Mean Group Estimator Research Articles

Financial efficiency and CO2 emission in BRICS. Dose digital economy development matter?

When it comes to the environmental costs, environmental economists have tried to study the effects of the foreign direct investment-growth nexus, but they have ignored the crucial role that financial development and technical innovation play. Massive increases in energy consumption have contributed to environmental degradation in the BRICS nations, which have experienced rapid IND due to their robust economies. This study uses data from 1990 to 2021 to examine the relationship between carbon emissions in BRICS member nations and factors such as FDI, technological innovation, and economic growth. Within the panel nations, the results confirm a high cross-sectional reliance. The BRICS countries' financial development, technological innovation, and foreign direct investment all have a negative and statistically significant long-run association with CO2 emissions, according to the Augmented Mean Group (AMG) estimator. On the other hand, economic growth, TI, IND, and energy use all have positive and statistically significant associations with carbon emissions. This study's researchers choose to use the Dumitrescu and Hurlin panel causality test to look at the other way around. Economic growth (EG), Digital economic growth (DEG), Financial efficiency (FE), CO2 emissions (CO2), Industrialization (IND), Technological Innovation (TI), Foreign direct investment (FDI) and Inflation are all identified as having a bidirectional long-run causative relationship. In contrast, a unidirectional causal relationship is observed between FDI and CO2 emissions. To entice high-quality FDI, the BRICS member nations must advance their industries, financial institutions, and technological innovation. In addition, these nations need immediate legislative solutions because IND is a major cause of environmental damage.

Does natural resources matter? Nexus among renewable energy policies, technological innovation, environmental protection, and economic growth

The objective of this study is to examine the relationship among different sources of renewable energy, role of technology, environment protection and economic growth. This study uses panel annual data set of selected BRICS countries from 1997 to 2019. This study uses the Augmented Mean Group (AMG) estimator, a second-generation estimator that takes slope homogeneity and cross-sectional dependence into consideration. For robustness, the Pooled Mean Group (PMG) estimator has also been utilized. The findings show that the use of renewable energy will rise as income inequality declines. The results of the analysis demonstrate a one-way causal association between income inequality and REC. This finding confirms that a reduction in income inequality will have a major impact on the adoption of renewable energy sources.

Are Human Development and Innovativeness Levels Good Predictors of the Competitiveness of Nations? A Panel Data Approach

Nations must adapt to the changing and developing world to sustain and develop their competitiveness. Human development and innovation are the two key concepts to increase the competitiveness of a nation. This study aims to examine the relationship between the Human Development Index (HDI), Global Innovation Index (GII), and Global Competitiveness Index (GCI) across different income groups from 2010 to 2019. The main objective is to identify potential variations in these relationships based on the income level of the countries involved. Panel data analyses using Common Correlated Effects Mean Group (CCEMG) and Augmented Mean Group (AMG) estimators are conducted to examine the relationships. Additionally, Pairwise Dumitrescu Hurlin Panel Causality Tests are conducted to examine the causal relationships between variables. The results show that HDI has a significant positive effect on GCI in each income group. Improving human development such as raising living standards and providing equal education opportunities for every member of society can contribute to a country’s competitiveness. Moreover, it is found that the effect of GII on GCI varies by income group. Specifically, the results indicate that the effect of GII on GCI is not supported for upper-middle-income countries. Therefore, while developing strategies to increase competitiveness through innovation, it is important to consider the income group of a nation. The findings of this study may assist policymakers, researchers, academics, and politicians to enhance their perspectives and formulate strategic and effective recommendations for action.

Assessing factors influencing renewable energy deployment and the role of natural resources in MENA countries

Governments worldwide are deploying renewable sources as a part of an imperative agenda to overcome the detrimental impacts of climate change and environmental degradation. Although renewable energy contains several benefits, very few researchers have worked on the determinants of renewable energy deployment and the role of natural resources in the Middle East and North Africa (MENA) countries. This research contributes to the prior literature by examining the influence of financial growth, governance, environmental quality, and economic development in MENA countries from 1990 to 2020. For empirical estimation, this study employs the latest econometric approaches: cross-sectional autoregressive distributed lag (CS-ARDL), augmented mean group (AMG), and Westerlund & Edgerton's cointegration. Furthermore, the cross-sectional augmented Im-Pesaran-Shin (CIPS) and cross-sectional augmented Dickey-Fuller (CADF) panel unit root tests are employed to check the stationarity level among variables. The empirical outcome demonstrates that governance, financial growth, the interaction term between financial growth and governance, carbon emissions, and economic development significantly and directly influence renewable energy deployment in MENA countries. As a further step, robustness is checked by employing the AMG estimator. The findings from the AMG estimator verify the robustness of the study's outcomes. Thus, the empirical and robustness results make it clear that all the aforementioned variables play a significant role in renewable energy deployment in the sampled region. The policy consequences of the major efforts are laid out as well coherently and consistently.

Revisiting long-run dynamics between financial inclusion and economic growth in developing nations: evidence from CS-ARDL approach

PurposeThis study aims to analyze the long-run dynamic relationship between financial inclusion and economic growth for developing nations.Design/methodology/approachThis study develops a comprehensive financial inclusion index based on the UNDP methodology for 53 developing nations. The authors use second-generation unit root tests, cointegration techniques and an advanced dynamic common correlated effects estimator model called cross-sectional augmented autoregressive distributed lags (CS-ARDL) to examine long-run dynamics among variables.FindingsThe tests confirm the presence of slope-heterogeneity and cross-sectional dependency. The second-generation panel unit root tests show the chosen variables are stationary at first difference. The bootstrap Westerlund cointegration result shows the variables are cointegrated in the long run. The CS-ARDL estimates conclude that financial inclusion positively enhances gross domestic product per capita in selected developing countries. The robustness check through augmented mean group estimation validates the findings.Originality/valueThe study makes three important contributions: first, it constructs a comprehensive financial inclusion index using 10 variables for a panel of 53 developing nations; second, the potential cross-section dependence and slope heterogeneity of panel data have been accounted for by applying the second-generation unit root tests; third, the study uses the dynamic common correlated effects estimator model (CS-ARDL) to examine long-run dynamics among variables.

Financial development and renewable energy deployment in sub-Saharan African countries

Purpose The underdevelopment of the financial sector could be one of the barriers to the deployment of renewable energies in developing countries. The purpose of this paper is therefore to analyse the effect of financial development in the deployment of renewable energies in sub-Saharan African countries. Design/methodology/approach The empirical analysis is based on a production approach and a cross-sectionally augmented autoregressive distributive lag error correction model estimate for 25 sub-Saharan African countries over the period 1990–2018. The augmented mean group (AMG) and common correlated effects mean group (CCEMG) estimators were used for the robustness analysis. Findings Two results emerge: financial development contributes positively to renewable energy deployment in sub-Saharan African countries in the short and long run; and fossil fuel dependence impedes significantly renewable energy deployment in the short and long run. The robustness analyses using the AMG and CCEMG methods confirm these results. Practical implications These results suggest the need for policies to support and strengthen the development of the financial sector to improve its ability to effectively finance investments in renewable energy technologies. Originality The originality of this paper lies in the fact that the analysis is based on a renewable energy production approach. Indeed, the level of renewable energy deployment is measured by the production and not the consumption of renewable energy, unlike other previous work. In addition, this research uses recent econometric estimation techniques that overcome the problems of cross-sectional dependence and slope heterogeneity.

Driving industrial and economic growth in Central and Eastern Europe: The role of electricity infrastructure and renewable energy

Balancing environmental objectives with energy security poses a significant challenge for Central and Eastern European (CEE) economies undergoing substantial energy sector reforms, particularly in the electricity sector. Apart from implementing market principles, improving electricity infrastructure and increasing the use of renewable energy sources (RES) are crucial for fostering industrial and overall economic growth. This study analyzes a panel of 15 Central and Eastern European economies (CEE) from 1995 to 2021. It employs various analytical techniques such as cross-sectional dependency testing, unit root testing, cointegration analysis, and the Augmented Mean Group (AMG) estimator. The results indicate that inefficient electricity infrastructure negatively impacts GDP and industry value-added (IVA) growth rates, regardless of control variables. Conversely, electricity generated from RES positively affects GDP and IVA growth rates in fully developed models. However, increased RES-generated electricity in models without control variables adversely affects IVA growth rates. These findings, coupled with the specific characteristics of CEE economies, lead to policy recommendations for sustainable economic and energy development.

Inquiring the impact of rural-urban migration, construction sector, and agriculture irrigated land on environmental degradation: insights from urbanized Asian countries.

The present study investigates the influence of rural-urban migration, construction sector share, and agriculture-irrigated land on environmental quality in urbanized Asian nations. For analysis, panel data from seven highly urbanized economies from 1996 to 2020 is utilized. The study employed an augmented mean group (AMG) estimator to find short and long-run results. The empirical discoveries depict that rural-urban migration increases energy demand in urbanized areas and significantly contributes to deteriorating environmental quality. The findings also reveal that the expansion of construction sectors is a significant source of high cement production, which also increases carbon emissions and environmental pollution by increasing the concentration of particulate matter in the atmosphere. The findings also exposed the role of agriculture-irrigated land, contributing to carbon emissions in urbanized Asian economies. The study also investigated the impact of the square term of irrigated agricultural land on environmental deterioration, revealing that adding agricultural land will further intensify environmental degradation by increasing carbon emissions in the atmosphere. A policy framework to reduce environmental damage in Asian economies caused by rural-to-urban migration, the building industry, and irrigated agricultural land was recommended based on the study's findings.

How economic policy uncertainty and geopolitical risk affect environmental pollution: does renewable energy consumption matter?

Climate change traps heat, affecting various species in previously dry areas. Climate change brought on by emissions of greenhouse gases exacerbates problems such as severe storms, earthquakes, epidemics, and food distribution. The group of developed and developing countries, the world's biggest carbon emitters and most significant economies, is expertly planning to lessen its environmental challenges and contribute to achieving Sustainable Development Goals 7 and 13 set by the United Nations. This study uses the novel econometric methodologies of the dynamic ordinary least square (DOLS) estimator, the augmented mean group (AMG) estimator, and the fully modified ordinary least square (FMOLS) estimate to examine the influence of economic policy uncertainty, renewable energy consumption, geopolitical risk, non-renewable energy consumption, and economic growth on ecological footprint from 2000 to 2021. The results reveal that the variables are co-integrated; REC reduces carbon emissions, EPU, geopolitical risk, and economic growth contribute to increasing carbon emissions, while urbanization improves carbon emission. Finally, the results suggest that the developed and developing economies can progress toward SDGs 7 and 13 by using renewable energy, lowering the geopolitical risk, effectively handling policy uncertainty, and reducing urbanization.

Education and Economic Growth: Evidence from the EUROMED Countries

The Mediterranean Strategy on Education for Sustainable Development (MSESD) Report reveals that the Mediterranean is an exceptional eco-region not only due to its geographical characteristics, but also its heterogeneous economic structure, in which education is regarded as a key driver of sustainable development. Given this importance, this study attempts to investigate the impact of education as a channel for human capital accumulation on two different growth concepts in a panel group of eight Euro-Mediterranean Partnership (EUROMED) countries. We utilize an endogenous growth model using annual observations spanning from 2000 to 2017 by employing the Augmented Mean Group (AMG) estimator. Empirical results obtained from the Augmented Mean Group estimator indicate a positive impact of education, regardless of the growth proxy. In addition, empirical findings reveal that the impact of education on inclusive growth is five times higher than that on output growth. We also find that capital is the main driver of growth while inclusive growth is primarily triggered by education. One of the main policy implications raised in this study is that education reforms that attempt to improve educational quality will assist policymakers to achieve sustainable development goals. Extensive policy discussions related to the experiential findings are also provided.

Does technological progress make OECD countries greener? New evidence from panel CS-ARDL

PurposeThis paper aims to examine the impact of information and telecommunication technologies (ICT-proxied by mobile phone subscription and Internet usage) on carbon dioxide (CO2) emissions in the Organization for Economic Cooperation and Development (OECD) countries from 1990 to 2018.Design/methodology/approachThe Cross-section Autoregressive Distributed Lag (CS-ARDL) model is employed to address the potential cross-section dependence problem. Common Correlated Effects Mean Group (CCEMG) and Augmented Mean Group (AMG) estimators are used to test for robustness of results.FindingsResults reveal contrasting effects of mobile phone subscription and Internet usage on CO2 emissions. While mobile phone penetration helps mitigate CO2 emissions, Internet usage tends to increase the emissions. Findings show that renewable energy is beneficial to the environment while economic growth is harmful to the environment. The effects of financial development and trade openness seem negligible.Practical implicationsThis study offers practical implications for policymakers. As different proxies of ICT could have contradictory impact on CO2, governments should be cautious against utilizing ICT to mitigate CO2. Findings point to the benefits of renewable energy in alleviating CO2 emissions. Therefore, governments are strongly advised to implement policies facilitating renewable energy consumption.Originality/valuePrevious studies ignored the problem of cross-section dependence which could lead to biased results and cause misleading inferences. This study aims to fill this void in the literature.

Links among population aging, economic globalization, per capita CO2 emission, and economic growth, evidence from East Asian countries.

Population aging, economic globalization, and economic growth simultaneously cause changes in environmental quality, but so far no studies have integrated these key factors into the same environmental policy framework. Thus, this study uses the more robust Westerlund cointegration test and the augmented mean group (AMG) estimator (robust to cross-sectional dependence (CD), heterogeneity, and endogeneity) to estimate the long-term relationship between population aging, economic globalization, economic growth, and per capita carbon emissions in East Asian countries during the period 1975-2018. The analysis results reflect that population aging significantly reduces the long-term per capita carbon emissions of specific East Asian countries. However, energy generation and economic globalization make significant contributions to long-run per capita carbon emissions. Moreover, the impact of economic growth on long-term per capita carbon emissions is significantly positive, while the impact of square of economic growth on long-run per capita carbon emissions is significantly negative, thus validating the inverted U-shaped environmental Kuznets curve (EKC) hypothesis for specific East Asian countries. The results of the causality test indicated a two-way causality between energy generation and per capita carbon dioxide emission, supporting the feedback hypothesis. There is also a two-way causal relationship between aging population and per capita carbon dioxide emission. Policy recommendations are discussed in response to the empirical findings of this study.

Nonlinear effects of urbanization routes (proportion of small cities, and proportion of large cities) on environmental degradation, evidence from China, India, Indonesia, the United States, and Brazil

The dynamic stochastic effects regressions on population, affluence, and technology model used in this study reveals the nonlinear effects of urbanization routes on CO2 emissions in China, India, Indonesia, the United States, and Brazil during 1970–2020, using dynamic seemingly unrelated regression, dynamic ordinary least square, and fully modified ordinary least square techniques. The empirical analysis shows that urbanization and the proportion of small cities contribute significantly to CO2 emissions, while the square of urbanization and the square of the proportion of small cities significantly reduce CO2 emissions, thus supporting the inverted U-shaped relationship for the selected countries. However, the effect of the proportion of large cities significantly reduces CO2 emissions, while the square of the proportion of large cities significantly promotes CO2 emissions, supporting a U-shaped relationship for specific countries. Gross domestic product, industrial development, and transport infrastructure contribute significantly to carbon emissions, while renewable energy generation significantly reduces carbon emissions. The country-level augmented mean group estimator in the analysis supports an inverted U-shaped relationship between urbanization and carbon emissions and a U-shaped relationship between the proportion of large cities and carbon emissions in all selected countries. There is also an inverted U-shaped relationship between the proportion of small cities and carbon emissions in China, India, Indonesia, and Brazil. The causality test results acknowledge bidirectional causality between urbanization and carbon dioxide emissions; between urbanization squared and carbon dioxide emissions; between the proportion of the largest cities and carbon dioxide emissions, and between renewable energy and carbon dioxide emissions. This study recommends renewable energy options, green urban infrastructure, and digital technologies to improve the environmental quality of urban areas. [Formula: see text]

The asymmetric effect of renewable and non-renewable energy on carbon emissions in OECD: new evidence from non-linear panel ARDL model

The level of economic income, population density and sources of energy supply is critical in assessing environmental quality. Recent empirical studies paid limited attention to the role of renewable (RE) and fossil energy (NRE) supply in carbon pollution regarding the Environmental Kuznets Hypothesis (EKC). Therefore, this study investigates the asymmetric relationships between carbon emissions and energy sources on the one hand and the environmental Kuznets hypothesis on the other hand for OECD countries, comprising countries with significant renewable energy supplies. The study includes the annual data from 1990 to 2021 and performs panel non-linear ARDL regression. The empirical results clearly show that RE and NRE have asymmetric effects on emissions in the long run but not in the short run. Both positive and negative shocks in RE reduce CO2 emissions in OECD economies, while asymmetric shocks in NRE substantially increase them. Increasing RE supply is clearly effective in reducing emissions. However, unlike most previous studies, this study shows that RE does not significantly reduce CO2 emissions in OECD countries. The error correction term (ect.) in the NARDL model is negative and significant. The magnitude of the term indicates that the system will return to long-term equilibrium about 4.2 years after any shock. Furthermore, we show that the EKC Hypothesis is supported in OECD countries. The turning point of the EKC is at $4085.77 per capita. Besides, regression with Driscoll-Kraay standard errors and Augmented Mean Group (AMG) estimator approach were used for robustness checks. The findings from the robustness check are consistent with the NARDL findings. Policies based on the promotion of a low-carbon and sustainable green environment should place greater emphasis on renewable resources even in OECD countries. Moreover, while many studies in the literature address asymmetric effects and EKC as energy consumption or utilisation, the novelty of this study is that it approaches the issue regarding energy supply with asymmetric effects for RE and NRE.

Exploring the impact of natural resources and energy transition on CO2 intensity in China.

As reported at the 26th UN Climate Change Conference (COP26), worsening climate situation has led to frequent extreme weather events around the world. The main cause of climate change is carbon emissions from human activities. While realizing rapid economic development, China has become the world's largest energy consumer and carbon emitter. To achieve the goal of carbon neutrality by 2060, it should reasonably use natural resources (NR) and promote energy transition (ET). In this study based on panel data on 30 Chinese provinces from 2004 to 2020, second generation panel unit root tests were performed after validating slope heterogeneity and cross-sectional dependency. Mean group (MG) estimation and error correction model were used to empirically test the impact of natural resources and energy transition on CO2 intensity (CI). The results show that natural resources exerted adverse effects on CI, whereas ET, economic growth and technological innovation were beneficial to CI. Analysis of heterogeneity indicates that natural resources exerted the greatest impact on CI in central China, followed by west China. Its impact in east China was positive but did not pass significance test. West China achieved the best result in carbon reduction through ET, followed by central China and east China. The robustness of the results was checked with augmented mean group (AMG) estimation. Our policy suggestions are to urge reasonable development and utilization of natural resources, accelerate ET to replace fossil fuels with renewable energy, and implement differentiated policies on natural resources and ET based on regional characteristics.

Renewable energy, forest cover, export diversification, and ecological footprint: a machine learning application in moderating eco-innovations on agriculture in the BRICS-T economies.

The United Nations Climate Change Conference (COP26) recommended that the member nations enhance their technological progression and structural transformation to mitigate the problems of climate change. The BRICS-T countries consisting of Brazil, Russia, India, China, South Africa, and Turkey agreed to implement COP26's policy suggestions. These countries accounted for 40% of global greenhouse gas emissions in 2017, thus posing severe threats to the global environment. The current study explores the role of renewable energy, forest depletion, eco-innovations, and export diversification in impacting the ecological footprint for those BRICS-T countries. We further examine the moderating effect of eco-innovations on agriculture on the BRICS-T nations. The study contributes to the existing literature by providing newer empirical insights on how eco-innovations and export diversification, along with renewable energy, forest cover, and agriculture, affecting the ecological footprint in the BRICS-T nations. It utilizes novel empirical methods like parametric and non-parametric techniques to derive the short-run and long-run empirical results. The empirical findings based on the augmented mean group and the kernel regularized least square methods document that economic growth, agriculture value added, and forest depletion increase the ecological footprint. In contrast, renewable energy and eco-innovations decrease the level of ecological footprint. In the long run, a 1% rise in GDP leads to a rise in the ecological footprint by 0.64% using the augmented mean group (AMG) estimation. The mean marginal effects are - 0.27%, 0.29%, and 0.17% for renewable energy; agriculture and forest cover, respectively, using the kernel-based regularized least square methods. The study suggests that policies designed for controlling the ecological footprints focus on the use of energy efficient technologies, particularly in the agricultural sector.

Heterogenous influence of productive capacities pillars and natural resources on ecological sustainability in developing Belt and Road host countries

Global climate change and environmental pollution force humanity to create new sustainable growth models. Growth policy relies heavily on the pillars of sectoral productivity: resource efficiency and sustainable resource management. This research adds to the determination of the impact of the numerous productive capacity indices (PCI) and natural resources on the ecological sustainability of emerging Belt and Road host nations from 2000 to 2018. The study utilized the system generalized method of moments (Sys-GMM) and the Feasible generalized least squares (FGLS) estimators to analyze the association among the variables. The empirical findings suggest that cumulative PCI and technological innovation have a promising impact on emissions reduction, while natural resources positively derive emissions. Manifestly, sub-indicators of PCI offer heterogeneous outcomes. Productive capacities in human capital, ICT, energy, and governance encourage ecological sustainability, while transport, private sector development, and structural change increase emissions. Augmented Mean Group estimator also validates similar findings. This research suggests improving operational efficiencies and productive capacities leads to better ecological outcomes.

Nexus of institutional quality and technological innovation on renewable energy development: Moderating role of green finance

Around the world, the green economy is seen as a practical way to achieve sustainability. New research using data from the African nations' nexus of institutional quality and technological innovation on renewable energy. This research aims to shed light on how institutional quality spending promotes green technological innovation expansion and institutional quality in the African nations. Therefore, this study examined the effects of technological innovation, established value, renewable energy, vestige oil energy, and financial development on CO2 releases in 24 African nations between 2001 and 2019. A second-generation panel approach was utilized to examine the interdependencies between the variables across time. These methods accounted for heterogeneity and the possible of remaining cross-sectional dependence. Empirical data from the Commonly Correlated Effects Mean Group (CCEMG) estimate and the Augmented Mean Group (AMG) estimator suggests that using eco-friendly technical advancement and renewable energy sources significantly reduces carbon dioxide emissions. But there are several variables linked to rising CO2 emissions, such as improved institutional frameworks, thriving economies, and a preference for fossil fuels over renewable energy. Based on these findings, we concluded that for African countries to achieve their sustainable development objectives, they need to increase their investment in environmentally friendly technological advances and renewable energy sources.

Assessing the effect of the improvement of environmental damage compensation legal system and green finance project on the re-establishment of the ecological environment.

What are the relationships among environmental regulations, green finance, and environmental damages in countries? Existing literature supports the impact of green finance or green innovation on environmental quality, but rare studies query the cointegration among other core variables. We thus utilize the yearly data of 25 Chinese provinces from 2003 to 2021 to empirically examine the relationships among access to clean energy and technology, environmental regulation, renewable green investment, subsidy on green energy, and green finance index in environmental damage compensation via an augmented mean group (AMG) and other estimators. However, the current empirical research also investigates the individual linkage of green finance components with explained variables. Overall, this study confirms the existence of cointegration relationships among these variables. Moreover, the results of AMG suggest that access to clean fuels and technology, environmental regulations, and green finance can inversely affect the explained variable in the long term. Furthermore, environmental regulations and renewable green investment positively affect environmental damages, while a separate proxy of green finance also negatively affects explained variables in the selected provinces with better environmental performance. Our empirical findings offer important policy implications for overall emerging economies to promote subsidies, environmental regulations, and green finance to improve environmental damages compensation.

The role of innovation in environmental-related technologies and institutional quality to drive environmental sustainability

In this study, we examine the long-run effect of environmental-related technological innovation, institutional quality, trade openness, energy consumption, and economic growth on CO2 emissions in APEC countries from 2004 to 2018. Firstly, panel unit root tests were used to explore the stationarity of each data series. The panel unit root test findings showed that all data series are stationary at the first difference. Second, the Westerlund panel cointegration test was used to deal with heterogeneity and cross-sectional dependence. Thirdly, the empirical findings from the augmented mean group (AMG) and common correlated effects mean group (CCEMG) estimators indicate that environmental-related technological innovation and institutional quality destructively affect CO2 emissions. In contrast, trade openness, energy consumption, and economic growth positively impact CO2 emissions. While causality analysis refers to the unidirectional causality runs from trade openness, energy consumption to CO2 emission and bidirectional causality relationships are between technological innovation, institutional quality, GDP, CO2 emission. Based on the findings, we proposed that APEC countries should raise investment in environmental-related technological innovation and improve the quality of the institutional environment to achieve sustainable development targets.