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Determinants of material footprint in OECD countries: The role of green innovation and environmental taxes
Abstract
The economic progress of OECD countries is highly dependent on the use of materials. However, excessive material use may cause OECD countries to deviate from their Sustainable Development Goals (SDGs), particularly SDGs 8 and 12. Therefore, it is an important policy agenda to analyze the determinants of the material footprint (MF) and seek solutions to reduce it. This study examines the impact of green innovation, environmental policy strategy, and environmental taxes on MF for 30 OECD countries from 2000 to 2019 using the cross‐sectional ARDL (CS‐ARDL) approach within the framework of the environmental Kuznets Curve (EKC). The outcomes indicate that the EKC hypothesis is valid for MF. Moreover, the long‐term results indicate that green innovation, environmental policy stringency, and environmental taxes are important policy tools to reduce MF. Therefore, OECD countries should promote green innovation, upsurge environmental taxes, and implement stringent environmental policies to the achievement of SDGs 8 and 12.
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This present research offers fresh insights regarding the causality nexus between environmental regulations and a sustainable environment. Also, this study considered the importance of renewable energy research and development (RERD), technological innovation (TI), and economic growth (GDP). Using the U.S. extended dataset covering the period 1990–2020; this research employed the wavelet methods (wavelet power spectrum and wavelet coherence) to observe the causal connections between mentioned variables based on the time-frequency domain. The empirical results from the wavelet power spectrum asserted that carbon emissions (CO2 ), RERD, and TI are vulnerable during the study period, while GDP and environmental policies are stable. Additionally, the wavelet coherence approach unveils relationships both in-phase and anti-phase. A causal connection is evident between CO2 and other variables. Particularly, a unidirectional causality is found from TI to CO2 emissions, while a bidirectional causal association exists between GDP and CO2 , and environmental policy stringency, and CO2 . Moreover, a bidirectional causality exists between RERD and CO2 , but this association is insignificant. Based on findings, this research suggests enhancing RERD investment, strengthening environmental regulations, and promoting green technological innovation to attain a sustainable environment.
This study analyzes the effect of renewable energy research & development (RRD) and nuclear energy research & development (NRD) expenditures on environmental quality by considering Germany’s goal of achieving carbon neutrality until 2045. Hence, the study uses various environmental indicators (carbon dioxide (CO2) emissions, ecological footprint-EF, and load capacity factor-LCF) to investigate the effects of RRD and NRD on the environmental quality controlling also a gross domestic product (GDP) and test the validity of the environmental Kuznets curve (EKC) and recently proposed load capacity curve (LCC) hypotheses. Also, the study includes yearly data from 1974 to 2018, uses fractional frequency Fourier autoregressive distributive lag (FADL) based FMOLS approach as the main model, and applies FADL based DOLS approach and Fourier wavelet causality test for the robustness. The empirical results reveal that (i) the explanatory variables have a cointegration link with CO2 emissions and EF; (ii) the EKC hypothesis is valid for Germany, while the LCC hypothesis is invalid; (iii) RRD expenditures are effective only in reducing CO2 emissions; (iv) RRD and NRD expenditures have no significant effect on the EF. Considering the results, German policymakers can utilize RRD more effectively and efficiently to improve environmental quality and reduce the EF. In this way, Germany can achieve its carbon neutrality goal until the middle of the century by benefiting from RRD facilities.
This study explores the relationship between the resource productivity and environmental degradation in European Union-27 countries. This study tests this relationship in context of high, moderate, and low material footprint sub-samples; these samples are formed utilizing the expectation-maximization machine learning algorithm. Using the panel data set of EU-27 countries from 2000 to 2020, linear and non-linear autoregressive distributed lag (ARDL) are applied for the symmetric and asymmetric evidence and to test environmental Kuznets curve (EKC), linear ARDL with the quadratic function is included. Results of the symmetric relationship find evidence of resource productivity's impact on the environmental degradation. In full sample of EU-27, both symmetric and asymmetric methods show that the short run and long run increase of resource productivity lower the environmental degradation. Only long run asymmetric relationship in high material footprint sub-samples supports that the resource productivity controls environmental degradation. Results of moderate material footprint sub-sample are mixed. However, low material footprint countries show that resource productivity in long run controls the environmental degradation in symmetry and only positive resource controls productivity in short run in asymmetric relationship. The reason for mixed results is the quadratic nature of sub-samples. EKC hypothesis is validated in moderate and low material footprint sub-samples. This research has many policy implications.
This paper investigates the effect of renewable energy consumption on material consumption, considering the relationship between Material Footrprint and Gross Domestic Product (GDP), and testing the assumptions of the Environmental Kuznets Curve. A STIRPAT variation is used to specify a model relating the Material Footprint to renewable energy consumption and GDP. The effect is tested for the Material Footprint of fossil fuels and for the Material Footprint of the other categories. The analysis is applied to the seven European countries with the highest proportion of renewable energy consumption.
The model estimation shows that the relationship between GDP and Material Footprint follows an inverted N-shaped form, and that the renewable energy favours the reduction of the material consumption of fossil fuels. However, there is a positive effect between the renewable energy consumption and the Material Footprint of the other categories beyond fossil fuels.
These results must be interpreted considering the context, as the development of renewable energy coincides with the effects of the 2008 crisis, which may distort the relation between the variables. To pose dematerialization scenarios, it seems necessary to consider reducing energy consumption even if it comes from renewable sources.
We investigate whether research and development (R&D) and environmental knowledge spillovers aid economies in meeting the targets of the United Nations’ (UN) Sustainable Development Goals (SDGs) for ensuring sustainable consumption and production patterns (SDG12). We do so by utilizing panel data from the European Union, Japan, and USA over the period of 2002–2017 and a production function approach. The results show that whereas R&D, in general, works against meeting the targets set in SDG12, environmental knowledge spillovers facilitate achieving the goal. Additionally, and as expected, the results support the positive effect of control of corruption and resource scarcity but a negative impact of environmental policy stringency for SDG12. The latter result might be due to environmental policies facilitating end-of-the-pipe solutions rather than supporting decreased resource and material use and waste generation. The findings indicate that instead of just supporting all (green and dirty) R&D, policymakers should devise measures that specifically facilitate environmental innovation (not just “any innovation”) and knowledge spillovers stemming from such green technologies, to support sustainable development via innovation.
This paper assesses the nexus between natural resource rent, hydropower energy consumption and ecological footprint for environmental sustainability incorporating with economic performance by using yearly data from 1970 to 2017. To this end, the long run steady-state relationship among investigated variables has been analyzed by using newly established Residual Least Squares (RALS) method and confirmed for Turkish economy. The directions and magnitudes of the effects of these variables on ecological footprint were tested by using Dynamic Ordinary Least Squares (DOLS) technique. The findings, except hydropower energy consumption, reveal statistically significant and positive effects of investigated variables on ecological footprint. Moreover, the inverted U-shaped EKC hypothesis was also affirmed between economic performance and ecological footprint. The causal relationship among these variables were also tested by using VECM Granger causality test The unidirectional Granger causality relationships were found that they are running from ecological footprint, and natural resource rent to economic performance, from natural resources to ecological footprint and from natural resource rent to economic performance in Turkish economy. Additionally, the bidirectional causal relationship has been detected among economic performance and ecological footprint in Turkey. The findings highlight the importance of investigated variables on ecological footprint in Turkey.
Sustainable development depends on decoupling economic growth from resource use. The material footprint indicator accounts for environmental pressure related to a country’s final demand. It measures material use across global supply-chain networks linking production and consumption. For this reason, it has been used as an indicator for two Sustainable Development Goals: 8.4 ‘resource efficiency improvements’ and 12.2 ‘sustainable management of natural resources’. Currently, no reporting facility exists that provides global, detailed and timely information on countries’ material footprints. We present a new collaborative research platform, based on multiregional input–output analysis, that enables countries to regularly produce, update and report detailed global material footprint accounts and monitor progress towards Sustainable Development Goals 8.4 and 12.2. We show that the global material footprint has quadrupled since 1970, driven mainly by emerging economies in the Asia-Pacific region, but with an indication of plateauing since 2014. Capital investments increasingly dominate over household consumption as the main driver. At current trends, absolute decoupling is unlikely to occur over the next few decades. The new collaborative research platform allows to elevate the material footprint to Tier I status in the SDG indicator framework and paves the way to broaden application of the platform to other environmental footprint indicators. Despite the wide acceptance of the role of the material footprint indicator in sustainability, no reporting facility at present provides sufficient information on countries’ material footprints. This study presents a new research platform that regularly provides detailed global material footprint accounts.
The role of a reliable resource consumption measurement is essential for devising a relevant climate policy. The consumption-based material footprint is trade-adjusted domestic resource consumption that presents an accurate picture of the domestic material footprint. Pursuing the same, this study draws asymmetric linkages between infrastructure development, green innovation, and consumption-based material footprint (MF) in the top 11 highly material-consuming countries. Our preliminary findings strictly reject the preposition of data normality and highlight that the observed relationship is quantile-dependent, which may disclose misleading results in previous studies using linear methodologies. In compliance, a novel empirical estimation technique popularized as Method of Moments Quantile Regression is employed that simultaneously deal with non-normality and structural changes in data. The results exhibit that infrastructure development (green innovation) significantly increases (decreases) MF mainly across medium to higher quantiles (medium-higher level of MF). Interestingly, the resource-depleting effect of infrastructure is highest for higher quantiles and lowest for lower quantiles of MF. Economic growth (globalization) increase MF, and their resource-depleting effect is higher (lowest) for lower quantiles and lowest (highest) for higher quantiles. Lastly, population exhibits an inverted-U shape relationship with MF across lower to higher quantiles. These results suggest pertinent policy recommendations.
Despite calls for large-scale reductions in material use and efforts to initiate a “circular economy” that promotes recycling and reuse, a limited decoupling between overall resource extraction and economic growth has been historically found. This is particularly true if resource use is measured with the life-cycle or consumption-based material footprint (MF) indicator that allocates material extraction to final goods and services. However, this indicator treats capital goods as final products rather than part of the production process. In this paper, we introduce the capital-augmented material footprint (CAMF), a new indicator of material use that includes all the materials embedded in capital goods. Results for 49 countries and regions over the period 1995–2015 show that for mineral use, about 50–60% of the total footprint of final consumption is embodied in capital goods, whereas for biomass, the figure is around 10%. The largest increase in material requirements was observed in non-OECD countries and in service sectors in general. More countries achieve relative and absolute decoupling when using the CAMF as indicator of material use. Our results underpin the need for comprehensive indicators when assessing options to decrease the impacts of consumption.
This paper examines the effects of environmental innovation on material usage, using Direct Material Input (DMI) and Raw Material Input (RMI) as indicators of material usage. The analysis is conducted on European Union countries for the years 1990–2012. We utilize the Generalized Method of Moments in a dynamic panel setting. Based on patent data, we construct green knowledge stocks for specific technological domains. We find that the effect of environmental innovation differs between subdomains. Innovation in the areas of energy efficiency, and recycling and reuse is found to reduce material usage. For alternative energy production, transportation, production or processing of goods, and general green innovation no significant effect is found. We observe a distinct reducing effect of some environmental innovation areas when compared with overall innovation. The technology effects are similar for RMI and DMI. The results are discussed from the perspective of literature on the environmental effects of environmental innovation, and literature on decoupling.
According to the Sustainable Development Goals (SDGs), the principal threats to human well-being encompass both non-renewable and renewable energy sources, alongside a mounting environmental deficit, which aligns with the targets of SDG-7 and SDG-13. This study explores how environmental technologies, financial growth, and energy use influence the ecological footprint and green growth in the top-ten countries with the biggest ecological footprint from 1990 to 2019. Environmental innovations, green growth, and renewable energy improve the environment, while financial expansion and the use of non-renewable energy have been shown to be detrimental to the environment. Financial expansion, ecological impact, and non-renewable energy constrain green growth. However, environmental innovation and renewable energy deployment have a cumulative effect on green growth. Moreover, the results of the panel causality approach signpost a bidirectional causal association between environmental innovations, green growth, non-renewable and renewable energy, and ecological foot- print. Nevertheless, it is observed that there exists a unidirectional causal relationship from financial develop- ment to ecological footprint and green growth. Moreover, this paper provides an in-depth evaluation and offers significant policy recommendations, both in a general sense and specifically targeted towards countries with the highest ecological footprints.
Environmental regulations have emerged as a critical policy tool for promoting environmental sustainability worldwide. However, there is a dearth of literature that investigates the impact of environmental regulations on load capacity factor in Asia-Pacific Economic Cooperation (APEC) economies. This study aims to address this gap by examining the role of renewable energy consumption, human capital, and environmental regulations in improving load capacity factor. In doing so, the paper covers 14 APEC economies; applies second generations panel data models (i.e., CUP-FM (continuously updated fully modified) as the base model and CUP-BC (continuously-updated and bias-corrected) for the robustness); and runs data between 1992 and 2018. The empirical findings present that: i) renewable energy consumption and human capital contribute to improving load capacity factor; ii) environmental regulations are not at a level to increase load capacity factor; iii) economic growth and trade openness significantly reduce load capacity factor. Considering empirical outcomes, this study suggests that APEC should tighten environmental regulations to achieve sustainable environment. In addition, this study offers important sustainable environmental policies for APEC within the framework of empirical findings.
The unrelenting surge in global warming in the current era suggests the inevitable need for governments across the globe to embark on policy measures that will help flatten the curve of the surging emissions. Consequently, the concept of carbon neutrality has become a vital policy approach for countries to achieve sustainable development. The present study extends the debates on carbon neutrality by examining the extent to which prominent factors such as natural resource dependence, eco-innovation, and green energy (biofuel and renewable energy) facilitate or hinder strides toward achieving carbon neutral environment in G7 economies. The study considers the additional roles of carbon tax, environmental policy stringency, and financial development in longitudinal data ranging from 1997 to 2019. The verification of the stated hypotheses hinges on a battery of estimators comprising cross-sectional ARDL, common correlated effects mean group, augmented mean group, and panel quantile regression. The empirical findings show that green energy, carbon tax, and environmental policy support the drive towards carbon neutrality by reducing the stock of CO2 emissions. On the other hand, natural resource dependence and financial development hinder the carbon neutrality agenda by escalating the surge in CO2 emissions. Robustness analyses are conducted from the angle of an additional outcome variable and estimation technique of which the results corroborate the empirical regularity of the main findings. Policy implications are derived from the empirical findings.
Digitalization has emerged as a crucial factor in reducing pollution and holds significant potential for facilitating the transition to a low-carbon economy. Nevertheless, the environmental impact of digitalization hinges on the strategies for collaboration with various economic actors and, as a result, their engagement with digitalization. In light of this, the present study seeks to examine the externality effect of digitalization on green innovation, renewable energy, and financial development in relation to environmental sustainability. The analysis employs the System Generalized Method of Moments (SYS-GMM) for 36 OECD countries over the period of 2000–2018. The empirical findings indicate that digitalization, green innovation, renewable energy, and financial development substantially promote environmental sustainability. Moreover, the interaction between digitalization, green innovation, renewable energy utilization, and financial development enhances the ecological footprint-mitigating effect of digitalization. In view of these results, merging digitalization and environmental policies may yield more robust outcomes and improved environmental quality compared to implementing a single policy in isolation.
Given Sweden’s impressive performance on green growth among the European Union countries, this study focuses on examining the responses of green growth, sustainable natural capital, sustainable forest capital, and carbon footprint to environmental-related innovation and material productivity while employing population to control for unobserved forces. By employing the dataset that spans over 1970–2019 alongside using suitable econometric approaches, the short- and long-run relationships alongside the Granger causality evidence are provided. The revelation from the result shows that environmental-related innovation promotes sustainable natural capital (by elasticity of ~ 0.04), promotes sustainable forest capital (by elasticity of ~ 0.13), improves green growth (by elasticity of ~ 0.01), but spur carbon footprint (by elasticity of ~ 0.01) especially in the long run. Importantly, the investigation further reveals that material productivity exhibits an inverted U-shaped relationship with sustainable natural capital, sustainable forest capital, and carbon emission, thus affirming the validity of material productivity Kuznets curve (MPKC) i.e., rise and fall scenario of material productivity. Meanwhile, while population produces desirable carbon emission and green growth outcomes, it hampers both sustainable natural capital and sustainable forest capital especially in the long run. Given these results, relevant and implementable policy guidelines are highlighted for policy makers and other stakeholders in Sweden.
Climate change coupled with environmental degradation is primary concern of the modern society. Natural resource dependence has been widely recognized as a principal stimulator of environmental degradation. However, little is known whether natural resource dependence may take part in environmental sustainability of the most innovative countries via the channel of technological innovation. Against this backdrop, this study aims to explore whether natural resource dependence, transport energy consumption, economic growth, and technological innovation explain ecological footprint of the seven most innovative countries under the environmental Kuznets curve (EKC) framework in the period from 1990 through 2018. This study utilizes both, the patent applications and research, development and demonstration budget as proxies for the technological innovation. By employing panel Method of Moments Quantile Regression (MMQR), this study's outcomes outlined that both transport energy consumption and natural resource dependence significantly increase ecological footprint while technological innovation reduces environmental degradation. Moreover, empirical findings of this study verified the legitimacy of EKC hypothesis. Additionally, natural resource dependence with interactive term of technological innovation provided evidence to reduce the harmful environmental effect of natural resources. The findings are robust to the selection of technological innovation proxy variable. The present empirical outcomes shed new light on the key role of technological innovation in attaining environmental sustainability clearly outlining that the most innovative countries should align the natural resources use, economic growth and transport energy consumption with the Sustainable Development Goals (SDGs).
Over the last few decades, environmental hazards have grown as a result of the increasing ecological pressure exerted by humanity, as calculated by its ecological footprint (EFP). Green technology innovation (GTI), renewable energy consumption (REN) and environmental taxes (ET) now represent the best approaches to attaining sustainable development without harming the environment. In this context, the main objective of this paper is to investigate the effect of GTI, ET, REN, TO and GDP on the EFP in Italy during the period 1994–2019. We employ a novel dynamic simulated ARDL (DYARDL) model to evaluate the short and long-run run connections among the above variables. Our study also utilizes the frequency domain causality (FDC) test to analyze the direction of causality. The results of the study clearly indicate the existence of a long-term cointegration among variables. Further, the results demonstrate that GTI, ET, and REN significantly enhance the quality of the environment by lowering the EFP. However, TO and GDP have a positive significant influence on EFP and degrades the environment. Finally, FDC test results also confirmed that GTI, ET, REN, TR, and GDP granger cause EFP. The results obtained suggest that government and policy makers should promote the investment in green innovation and renewable energy sectors to accomplish the ecological sustainability.
In today's world, environmental concerns are at the forefront of countries' considerations, along with economic priorities. In this context, countries face the challenge of developing and directing their investments in clean energy technologies to achieve the Sustainable Development Goals, particularly affordable and clean energy. Does the development and diffusion of clean energy technologies contribute to improving environmental quality? This study addresses this question by examining the effects of clean energy technologies on sustainable environmental quality as expressed by the load capacity factor (LCF). In this context, the study explores the United States (US), as the largest economy and one of the leading countries investing in clean energy, considering the role of human capital, urbanization, and economic growth. To this end, this paper applies the novel augmented autoregressive distributed lag (ARDL) model to annual data from 1974 to 2018. The long-term empirical results show that (i) Clean energy technologies have no effect on the LCF; (iii) human capital supports environmental quality; (iv) urbanization has an adverse effect on environmental quality; (v) increasing economic growth worsens environmental quality. Overall, the empirical results suggest that while clean energy technologies should support sustainable environmental quality, this is unfortunately not the case in the US. Therefore, the US policymakers need to take improvement actions to ensure that clean energy technologies contribute to sustainable environmental quality and that the community reaps the environmental benefits of human capital.
This study investigates the impacts of nuclear energy consumption on environmental quality from a different perspective by focusing on carbon dioxide (CO2) emissions, ecological footprint, and load capacity factor. In this context, the South Korea case, which is a leading country producing and consuming nuclear energy, is investigated by considering also economic growth, and the 1997 Asian crisis from 1977 to 2018. To this end, the study employs the autoregressive distributed lag (ARDL) approach. Different from previous literature, this study proposes a load capacity curve (LCC) and tests the LCC and environmental Kuznets curve (EKC) hypotheses simultaneously. The analysis results reveal that (i) the LCC and EKC hypotheses are valid in South Korea; (ii) nuclear energy has an improving effect on the environmental quality; (iii) renewable energy does not have a significant long-term impact on the environment; (iv) the 1997 Asian crisis had an increasing effect on the load capacity factor; (v) South Korea has not yet reached the turning point, identified as $55,411, where per capita income improves environmental quality. Overall, the results show the validity of the LCC and EKC hypotheses and prove the positive contribution of nuclear energy to South Korea's green development strategies.
A series of economic parameters may influence material footprints (resource consumption). The efficacy of a country’s infrastructure for generating commodities is one of the most essential of these elements. This study contributes to determining the influence of productive capacities on trade-adjusted resource consumption in China. Using a bootstrapping autoregressive distributed lag (BARDL) model, it examines the co-integration relationship between China’s material footprints (MF), productive capacity index (PCI), and economic growth from Q1-2000 to Q4-2018. The results exhibit that if PCI rises by one percent, long-term resource consumption falls by 0.298 percent while economic growth rises by 0.316 percent. In the short run, a one percent improvement in production efficiency has a comparable effect on economic growth (0.175%) and resource conservation (0.123%). Long-term resource consumption grew as per capita income rises. Moreover, the results do not support the resource-based Environmental Kuznets Curve hypothesis. Long-term estimates suggest that productive capacities have a significant impact on lowering material footprints, adding validity to the notion. The findings show stronger impacts in the long run than in the short run, consistent with the long-run transmission of economic and environmental implications, with significant convergence towards long-run equilibrium. This result implies that efficient resource management can be obtained by improving productive capacities.
Green innovation and resource efficiency have been addressed as two essential drivers in achieving sustainable economic growth in developing countries. The primary purpose of this research is to evaluate the relationship between green innovation, resource efficiency, and sustainable economic growth in E7 (China, Indonesia, Mexico, Russian Federation, Turkey, Brazil, and India) by the Generalized Method of Moments (GMM) technique from 2010 to 2021. The results confirm that green innovation and resource efficiency positively and significantly impact green economic growth in the countries examined. In addition, the estimation results depict the negative impact of the labor force on green economic growth, while the coefficient of FDI (Foreign Direct Investment) is not statistically significant. The recommended practical policies by this research are developing green FDI, promoting green financing tools, and enhancing green job creation through SMEs (Small and Medium Enterprises).
This study analyzes comprehensively the role of green technology, environmental taxes, and green energy toward a sustainable environment in 5 sovereign Nordic countries by also considering income and population. For this purpose, annual data of Nordic countries from 1995 to 2020 is extracted and the cross-sectional augmented autoregressive distributed lag (CS-ARDL) technique is applied to test short-run and long-run compatibilities of the indicators on carbon dioxide (CO2) emissions. Moreover, Augmented Mean Group (AMG) and Common Correlated Effects Mean Group (CCEMG) approaches are applied for robustness checks. The empirical results reveal that (i) green technology, environmental taxes, and green energy have a negative association with CO2 emissions in the both short-run and long-run; (ii) income and population have a positive association between CO2 emissions in the both short-run and long-run; (iii) AMG and CCEMG approaches report similar findings with the CS-ARDL and validate the robustness in turn. Thus, the empirical results confirm the contributing role of green technology, environmental taxes, and green energy toward a sustainable environment in 5 sovereign Nordic countries. Moreover, policy implications are discussed.
Efficient resource consumption is one of the global challenges of the era to attain economic and environmental sustainability. The high-level consumption of resources has a detrimental effect on the environment. Simultaneously, the low-level resource consumption hindered economic growth; therefore, it is crucial to identify the key factors that can instigate resource conservation without affecting economic and environmental sustainability. This study investigates the role of digital finance and environmental regulation in China as the mitigants of resource consumption. The study applied the “bootstrapping autoregressive distributed lag” (BARDL) approach to investigate the long-run cointegration among digital finance, environmental regulations (environmental taxes), economic growth, and material footprint (proxy of resources consumption) by employing the quarterly data from 2011 to 2020. The preliminary finding through the diagnostic test confirms the normal distribution of the data. Likewise, the unit root tests confirmed the integration order of I (1). The outcomes of the advanced cointegration approach and the dynamic process of BARDL demonstrate that the increase in environmental taxes and digital finance significantly reduced the material footprint. In contrast, the upsurge in economic growth expands the material footprint in the long and short run. It shows that environmental taxes and digital finance work as mitigants while economic growth is the key driver to accelerating resource consumption. Thus, the appropriate policy intervention for these factors can significantly change resource consumption. Hence, China must implement strict regulations to strengthen the environmental tax mechanism and support digital finance to achieve economic and environmental sustainability goals.
This study explores the asymmetric influence of environmental governance, institutional quality, and technological innovations on consumption-based resource footprints for the selected EU economies. It applies the Method of Moments Quantile Regression (MMQR) for nonlinear association among model variables, while fully modified ordinary least square (FMOLS), dynamic ordinary least square (DOLS), and fixed effect ordinary least square (FE-OLS) for panel heterogeneity from 1990 2019. The preliminary evaluations confirm slope heterogeneity, non-stationarity, and panel cointegration. All three estimators (FMOLS, DOLS, and FE-OLS) support the role of technological innovation, environmental governance, and institutional quality in reducing material footprints. Likewise, the MMQR estimations unveil that environmental governance through policy stringency, technological innovations, and institutional quality substantially decreases material footprints across all quantiles (0.10–0.90). More specifically, the findings show that the role of environmental governance, institutional quality, and technological innovations is more substantial at higher quantiles (3rd to 9th) compared to lower quantiles (1st to 3rd). However, economic growth reflects a substantial and direct source of material footprints in all three ranges of quantiles. The empirical findings suggest that environmental governance is imperative for sustainable resource management.
Depleting scarce resources and environmental deterioration are critical issues to address in the contemporary world. Particularly, China has shown exponential growth in infrastructure construction, international trade, and embodied innovation in the last few years. Aggressive infrastructure-led growth and urbanization have created unremitting pressure on China’s resource consumption. Therefore, this study analyzes the asymmetric impact of resource depletion associated with Chinese infrastructure development and urbanization by controlling the effects of green innovation and economic growth from 1990 to 2018. Consumption-based material footprint (MF) is used to quantify resource consumption from domestic activity. This study employ novel Quantile ARDL approach to integrating aromaticity arising from structural changes, policy shifts, financial or economic shocks, and data abnormality confirmed through preliminary tests. The long-run results show that infrastructure development, urbanization, and economic growth significantly contribute to MF. However, these effects substantially varied across lower, medium, and higher quantiles. The positive impact of infrastructure development is highest for higher quantiles of MF, while the impact of urbanization is highest at lower quantiles. Green innovation significantly decreases the MF, mainly at higher quantiles. Besides, the study validates Environmental Kuznets Curve hypothesis in the long run. Similar results are observed in the shorter run; however, their significance and magnitude are substantially lower due to the long-term transmission of model variables. These results offer valuable policy recommendations.
Achieving carbon neutral requires a comprehensive understanding of the effect of different key factors on carbon emissions. To this end, this study investigates the effect of trade openness, human capital, renewable energy and natural resource rent on carbon emissions within the framework of the environmental Kuznets curve (EKC) hypothesis. Second-generation econometric tests, Generalized Method of Moments and Fully Modified Ordinary Least Squares estimator were developed based on the aggregated dataset of 208 countries from 1990 to 2018. The results show that (i) the EKC hypothesis is validated when the effects of trade openness, human capital, renewable energy consumption, and natural resource rents are considered. The relationship between income level and carbon emissions shows an “inverted U-shaped” curve at the global level. Besides, the real GDP per capita corresponding to the EKC turning point is 19,203$. (ii) Renewable energy consumption and human capital have heterogeneous effects on carbon emissions in before- and after-EKC turning points. Specifically, renewable energy consumption has a better emission reduction effect for countries before the EKC turning point, with effects of −0.4754 and −0.2452, respectively; human capital has a better emission reduction effect for countries after the EKC turning point, with effects of −0.5052 and −0.3398, respectively.(iii) the mitigation effect of trade openness on carbon emissions is only effective in countries with weak decoupling after EKC turning points, with a mitigating effect of −0.0615. However, natural resource rents increase carbon emissions in most countries.
Green innovation is one of the latest topics of sustainable development, which has unknown dimensions that can be explored. The main purpose of this paper is to study the green innovation network among 144 countries through the Slacks-based measure of directional distance functions approach for annual data throughout 2017–2021. In addition, the Quadratic Assignment Procedures (QAP) analysis is used to determine the impacts of influencing factors on the green innovation efficiency of the examined sample of countries. The major findings revealed that the global green innovation network is centered in North America, Western Europe, East Asia, and Oceania. The results of the QAP technique confirmed that geographical proximity, good governance, consumption of fossil fuels in transportation, environmental regulation index, energy resources price system, the difference in Gross Domestic Product (GDP) per capita, and pandemic affect the formation of the spatial relationship network of green innovation efficiency. This paper recommends the most important practical implications of increasing the share of development and research in the green energy sector, improving green loans, promoting green financing tools, and prioritizing the digital economy.
Improving resource efficiency and environmental quality is one of the top priorities for both advanced and emerging economies. Climate vulnerability instigates in building and identifying the drivers of resource efficiency. Though there exists literature on the drivers of resource consumption, however, there is a lack of empirical evidence concerning the influence mechanism of fiscal decentralization on consumption-based resource depletion. Therefore, we intend to estimate the direct and indirect effects of composite fiscal decentralization on trade-adjusted resource consumption through institutional quality, human capital, and infrastructure development in selected OECD countries from 1996 to 2017. This study applies a cross-sectional augmented auto-regressive distributed Lag (CS-ARDL) model to address the issues arises from slope heterogeneity and cross-sectional dependency. The direct effects of fiscal decentralization on per capita resource consumption are significantly positive, while indirect effects are significantly negative (positive) through institutional quality and human capital development (infrastructure development). These findings imply that the down-delegation of financial powers in local government increases resource consumption; however, resource decoupling exists if local governments are embodied with higher institutional quality and better human capital. In contrast, the infrastructure growth channel of fiscal decentralization suggests that higher demand for transport and energy infrastructure at the sub-national level increases resource consumption. These results offer valuable policy recommendations.
This research examines the effect of environmental policy stringency on green innovation in renewable energy technology and whether the green innovation response differs with varying degrees of environmental policy. Based on panel data of 33 countries over the period 1990–2015, we show that a stringent environmental policy does encourage green innovation in renewable energy technology, and this impact is more pronounced in OECD countries and high-income countries. More specifically, a stringent non-market-based environmental policy induces more patents in renewable energy generation. The findings also show that a stringent environmental policy yields green innovation for geothermal energy, hydro energy, and marine energy, but not for wind energy and solar energy. Heterogeneity analysis suggests that innovation capacity and environmental pressure enhance the impact of environmental policy stringency on green innovation in the renewable energy field. Finally, the paper presents that clean energy investment plays the role of a mechanism through which environmental policy stringency spurs green innovation in the renewable energy field, offering insights into the influence of environmental policy stringency on green innovation.
Aligning to the 2030 United Nations Sustainable Development Goal (SDGs) 12, we investigate the role of renewable energy in achieving sustainable consumption and production pattern in Africa. This study addresses the question: whether the use of renewable energy helps achieve production and consumption patterns free from environmental degradation? We use panel data on 14 African countries from 2002 to 2014 and a robust econometric approach such as panel corrected standard error (PSCE), instrumental generalized method of moment (IV-GMM), and quantile regressions. We find that (1) renewable energy consumption helped to achieve a consumption and production pattern that is free from environmental degradation; (2) there is a significant positive heterogeneous effect of renewable energy consumption on sustainable consumption and production pattern, but the impact level dropped in the long-run. In light of this, we recommend that African countries invest in green energy to achieve sustainable production and consumption patterns
The purpose of this research is to assess China’s sustainable economic recovery and growth through a comparative analysis of China’s global economy following Covid-19. We use the unit root test and generalized method of moments (GMM) to make inferences. The growth scenario is an important consequence of economic recovery, and the study concludes that increased energy use and rising energy costs need greater funding for the energy industry. Green energy financing is urgently required to offset rising production costs of gas and electricity. It is recommended that both Chinese and global financial institutions, banks and finance ministries, take a prominent role in addressing the crisis. This can be achieved by investing in renewable energy to improve sustainable economic recovery, reduce greenhouse gas (GHG) emissions and accelerate economic recovery. This must be carried out over a long period to achieve the intended results. Strategic development goals (SDGs), such as SDG 7 on clean and cheap energy, and SDG 13 on combating climate change, are urged on all nations in both areas.
This study investigates the role of solar energy, environmental policy stringency (EPS), and climate technology in realizing environmental sustainability in OECD economies from 2001 to 2018. The preliminary findings confirm the issues of slope heterogeneity and cross-sectional dependency; thus, we apply the cross-sectional augmented autoregressive distributed lags (CS-ARDL) model. The overall results indicate that solar energy, EPS, and climate technologies are playing a positive and significant role in encountering environmental issues and ensuring environmental sustainability in the long run, while economic growth is the key driver of environmental degradation. A similar insight is observed in the short run; however, their coefficient size and significance substantially vary. Moreover, the Error Correction Term is significantly negative, implying the convergence towards long-run equilibrium in case of any shock in the short-run. These results are consistent with alternative estimators and suggest the promotion of solar energy, implementation of stringent ecological policies, and climate technologies to achieve inclusive and sustainable growth.
Given the alarming rate of ecological corrosion, countries around the globe are seeking ways of curtailing environmental deficits to attain future sustainability. In this quest for green development, economies are motivated to adopt eco-friendly practices that can assist in the fulfilment of resource conservation and efficiency to achieve green eco-systems. Keeping the importance of the concept in mind, the current study analyzed the influence of renewable energy transition, ecological innovation and environmental policy stringency on the ecological footprint of OECD economies from 1990 to 2017 under the theoretical concepts of the Environmental Kuznets Curve. Applying the advanced Method of Moment Quantile-Regression (MM-QR), the empirical findings reported the negative association of the studied green variables with the ecological footprint across all quantiles while also validating the Kuznets curve in the sampled sample economies. Moreover, the outcomes of heterogeneous panel causality revealed the uni-directional causal link from ecological innovation and renewable energy transition to ecological footprint. On the other hand, economic growth and policy stringency have been found to have feedback causal association with the ecological footprint. The study recommended the formulation of policies to syndicate countries’ economic and financial tools with environmental and technological incentives to promote sustainable business operations and country-wide green awareness.
The main objective of this study is to get the asymmetric effects of environmental policy stringency on CO2 emissions in top emitter's economies named China, USA, India, Russia, and Japan by using non-linear panel ARDL approach. The non-linear model infers that an increase in environmental policy stringency improves the environmental quality by reducing CO2 emissions in the long run. While a negative change in environmental policy stringency is also reducing the CO2 emissions in the long run. Indeed the asymmetric effects between positive and negative change in the environmental policy stringency are also confirmed in magnitude only in the long-run, thus the policymakers should consider positive as well as negative changes while devising the rules and regulations related to the environment. The study suggests that the high polluted economies need to revisit green environmental regulations policies.
After the Paris Climate Conference (Conference of the Paris COP21), emerging countries also start succeeding in carbon neutrality targets. In doing so, environmental sustainability has become a vital concern over the past few decades. To control the pollution from combustion gases and to mitigate the destructive effects of carbon emission on environmental quality, governments and policymakers need to consider the important factors that decrease the net carbon emission level, such as eco-innovation and environmental taxes. The literature on the environmental taxes and eco-innovation to control carbon emission is scant. Therefore, this study fills the knowledge gap by evaluating the dynamic effect of eco-innovation and environmental taxes on the carbon neutrality target in emerging seven (E7) economies from 1995 to 2018 and other control variables. The study uses advanced panel data econometric tools to handle various issues such as cross-section dependence structural break and slope heterogeneity for empirical analysis. The study uses the second-generation panel unit root test, Westerlund's cointegration tests, CS-ARDL long-run and CS-ARDL short-run analysis, AMG, and CCEMG for robustness check. The study's outcomes confirm that eco-innovation and environmental taxes play a major role in carbon abatement and Environmental Kuznet Curve (EKC) presence found in E7 countries.
The Organization for Economic Cooperation and Development (OECD) economies face the challenges of rising energy demand, urbanization, and growing environmental issues (rising ecological footprint and less biodiversity). The primary objective of this article is to explore the role of environmental taxes and economic growth on the growing ecological footprint in 29 OECD economies. The autoregressive distributed lag (ARDL) approach and the related intermediate estimators are used to attain the purpose. The two substitute single equation estimators, DOLS, FMOLS, and fixed effect, are also employed to check the robustness of the ARDL estimator. Empirical results reveal that environmental-related taxes, economic growth, foreign direct investment, energy use, urbanization, renewable energy, and industriali-zation significantly influence the long-term ecological footprint in OECD countries. The dynamics of the studied variables got changed when time is considered. In the short-term, these dynamics are mixed while staying similar in the long-term across the OECD countries. This is attributed to varying levels of renewable energy use and industrialization progress in OECD countries. The empirical conclusions suggest that OECD economies need careful monitoring of environmental regulations for energy usage policies and cleaner production goals.
This paper investigates the intensity of international collaborations in energy-related technologies across OECD and BRIICS countries, by disentangling the role of the distance in environmental policy stringency between countries, controlling for the more traditional measures of technological, social, institutional and geographical distance. In doing so, it distinguishes between the stringency in demand-pull and the stringency in technology-push policy instruments. The analysis relies upon an original dataset, with data on patents and co-patents in climate change and mitigation technologies over the period 1995–2014, with a focus on technologies related to energy generation, transmission or distribution. The results show that the distance in the stringency of environmental policy between countries hinders the intensity of technological collaborations in energy-related technologies and this occurs specifically with reference to demand-pull policy instruments. We also find that while the availability of local technological capabilities positively affects the intensity of international collaborations, if two countries are distant in terms of technological development, the co-patenting activity is hindered. Finally, BRIICS countries display a lower ability to participate in international co-patenting activity, particularly so in collaboration with other BRIICS countries.
As China’s economy is transforming into a new normal stage, the energy industry is becoming increasingly innovation-driven, which is shown particularly in renewable energy. Given that the green innovation transformation is crucially critical during China’s new normal stage, this paper analyzes the direct impact of energy consumption on energy innovation and innovation transformation, and reveals the net effect of green innovation transformation on economic sustainability and energy consumption. Micro and macro empirical evidence are both provided in this paper by implementing two estimation methodologies: fixed effect model and Generalized Method of Moments (GMM) Vector AutoRegression (VAR) approach, respectively. Estimating Chinese micro 153 listed energy companies’ data and macro 30 provincial data from 2009 to 2016, we find that: (1) In terms of energy enterprises’ innovation activity behavior, energy consumption could promote total energy innovation, of which renewable energy innovation is stimulated far more significantly. (2) There is an increasing tendency for energy structure to transform into renewables as the energy consumption increases. (3) The green innovation transformation, instead of total innovation counts, can reduce energy consumption and benefit economic sustainability. Therefore, the structure of innovation transformation plays more significant role than total energy innovation in stimulating economic growth, and alleviating the energy consumption antinomy during China’s new normal stage. In this regard, in order to stimulate green energy transformation, government should implement financing policy, reduce administrative intervention, upgrade energy legal system and improve energy pricing mechanism to encourage more research and development (R&D) activities at the core of renewable energy.
The study employed ecological and material footprint from the consumption perspective as a holistic measure of human pressure on the environment to examine the environment-economic growth nexus. Particularly, Environmental Kuznets curve hypothesis has been tested for the group of thirty-seven Asian countries. These are further analyzed into five Asian sub-regions, namely; West-, Central-, South-, East-and Southeast Asian countries over the period of 1991 to 2017. Panel cointegration, Pooled mean group, dynamic ordinary least square and differenced panel generalized methods of moments have been applied. The analysis reveals a mixture of results for the presence of EKC when using ecological footprint. EKC exists for Central-and East Asian countries, but not in case of West-, South-and Southeast Asian countries. Whereas results support EKC when we used material footprint indicator except central Asia. Energy consumption increases the ecological and material footprint. In addition, overall globalization and urbanization enhances ecological and material footprint. From the outcome of this empirical work, a number of policy recommendations have been discussed.