How does environmental policy stringency influence green innovation for environmental managements?

Exploration and future trends on spatial correlation of green innovation efficiency in strategic emerging industries under the digital economy: A social network analysis

With digital technological change and the increasing frequency of interregional innovation links, the spatial correlation and diversity of strategic emerging industries' green innovation efficiency (SEI-GIE) need to be explored in depth. This paper innovatively constructs the SEI-GIE input-output index system under digital economy. The proposed grey model FINGBM(1,1) with ω-order accumulation and weighted initial value optimization realizes effective prediction of 7 input-output indicators of 30 provinces in China from 2021 to 2025. Super-SBM-DEA, gravity model, and social network analysis are applied to explore spatial network structure's dynamic process of SEI-GIE from 12th to 14th Five-Year-Plan period (2011-2025). Empirical results show that (1) Under the effect of digital economy, the SEI-GIE in China generally shows a U-shaped fluctuation trend, in which the growth trend in the central region is obvious, and the western region shows significant fluctuations. (2) The spatial correlation network of SEI-GIE presents a complex and stable center-periphery circle. Particularly, the overall increase in network efficiency highlights the strong small-world characteristics. (3) Beijing, Shanghai, Zhejiang and Jiangsu have always been in the leading core position, with strong influence and control; And Tianjin's core position in the network will decline. Additionally, Guangxi and Chongqing have great potential, but Guangdong needs to strengthen its radiation effect. (4) Block model shows that plate-I (Beijing, Tianjin) receive spatial spillovers from others, while plates-III,IV have significant spillover effects. This study provides theoretical reference for policymakers from a network perspective to promote development of China's SEI-GIE.

An innovative MGM-BPNN-ARIMA model for China's energy consumption structure forecasting from the perspective of compositional data

Effective forecasting of energy consumption structure is vital for China to reach its "dual carbon" objective. However, little attention has been paid to existing studies on the holistic nature and internal properties of energy consumption structure. Therefore, this paper incorporates the theory of compositional data into the study of energy consumption structure, which not only takes into account the specificity of the internal features of the structure, but also digs deeper into the relative information. Meanwhile, based on the minimization theory of squares of the Aitchison distance in the compositional data, a combined model based on the three single models, namely the metabolism grey model (MGM), back-propagation neural network (BPNN) model, and autoregressive integrated moving average (ARIMA) model, is structured in this paper. The forecast results of the energy consumption structure in 2023-2040 indicate that the future energy consumption structure of China will evolve towards a more diversified pattern, but the proportion of natural gas and non-fossil energy has yet to meet the policy goals set by the government. This paper not only suggests that compositional data from joint prediction models have a high applicability value in the energy sector, but also has some theoretical significance for adapting and improving the energy consumption structure in China.

Exploring the asymmetric effect of fiscal policy instruments in encountering environmental degradation: proposing an SDG framework for India

Asian countries are facing difficulties in attaining sustainable development goals (SDGs), and India is not an exception to it, with environmental degradation being one of the primary issues. Therefore, a policy-level reorientation may be required to address it. From this standpoint, fiscal policy instruments may come in handy towards fully integrating the SDGs into its agenda. The present investigation designs an SDG framework for India that could serve as an example for other Asian nations. This study introduces a new investigation exploring the relationship between fiscal policy instruments and environmental quality in India by examining the environmental Kuznets curve (EKC) hypothesis from 1990 to 2021. A nonlinear autoregressive distributed lag (NARDL) model is applied for empirical examination. The findings indicate that positive and negative shocks in fiscal policy instruments have significant impact on carbon emissions in both the long and short run. The study has also found evidence of an "inverted U-shape" EKC for India. These results are valuable from a policy perspective for India and other Asian countries to address environmental issues. The study has also outlined potential outcomes that may benefit India's fiscal policy in resolving environmental issues and attaining better economic growth. In the end, the study proposes a policy framework that supports SDG 7, SDG 8, SDG 12, SDG 13, and SDG 17 objectives.

How does trade policy uncertainty affect green innovation in the USA and China? A nonlinear perspective

Green innovations are the most critical factor in promoting environmental sustainability worldwide. Trade can speed up the adoption of green innovations by facilitating the transfer of information, skills, and technology. However, trade policy uncertainty can create significant challenges for businesses investing in eco-innovations, leading to increased risk, reduced investment, and slower progress toward sustainable technologies. Recently, a growing number of researchers have shown their interest in finding the factors that can impact green innovations, but none have investigated the influence of trade policy uncertainty on green innovations in the USA and China. In addition, none of the past studies has relied on the nonlinear assumption. This analysis fills these gaps by examining the nonlinear impacts of trade policy uncertainty on eco-innovations in China and the USA over 2000Q1-2021Q4 by employing a nonlinear ARDL model. The finding reveals that a positive shock in trade policy uncertainty results in a decrease in green innovation in the USA and China, while a negative shock in trade policy uncertainty leads to an increase in green innovation in the USA over the long run. The nonlinear models also indicate that a positive shock in trade policy uncertainty harms green innovation in both the USA and China in the short run. The robustness of these results is confirmed by the NQARDL model, which confirms that an upsurge in trade policy uncertainty lowers green innovation in most quantiles in the USA and China in the short and long run. Conversely, negative shocks in trade policy uncertainty stimulate green innovation at most quantiles in both China and the USA, in the short and long run. Thus, policymakers need to consider the potential impact of trade policies on eco-innovations and work to create stable and predictable trade environments that support the growth of renewable technologies and other sustainable solutions.

Energy transition and environmental stability prospects for OECD economies: The prominence role of environmental governance, and economic complexity: Does the geopolitical risk matter?

The global increase in temperature and climate change signals the need for humanity to reduce greenhouse gas emissions and to adopt eco-friendly lifestyles. The 2023 United Nations Climate Change Conference (COP28) in the UAE emphasized this, urging nations to commit to the Paris Agreement and pursue a greener, carbon-free future. In recent decades, climate change has become a critical issue, primarily because of the extensive use of fossil fuels and conventional energy resources. Economic growth has led to an increase in energy consumption and widespread environmental damage. The present study empirically explores whether any changes in environmental governance, economic complexity, geopolitical risk, and the interaction term influence energy transition and environmental stability in OECD economies over the period 1990-2021. Novel econometric methods, including Westerlund co-integration and the Method of Moments Quantile Regression (MMQR), are employed to address complexities such as cross-sectional dependency and panel causality. The key findings from the MMQR technique showed a positive link between environmental governance and economic complexity in driving sustainable energy transitions, thus bolstering environmental resilience in OECD countries. However, economic complexity counterbalances environmental stability. Significantly, geopolitical risk acts as a moderating variable, enhancing the effects of governance and complexity on sustainable energy practices and environmental stability. Based on these insights, this study recommends strategic initiatives, including investment in eco-friendly technologies, to fast-track the shift to clean energy and strengthen environmental resilience in OECD countries. These strategies align with the broader objectives of global sustainable development, offering a path towards a greener and more sustainable future.

Interdependency and causality between green technology innovation and consumption-based carbon emissions in Saudi Arabia: fresh insights from quantile-on-quantile and causality-in-quantiles approaches

In this paper, we examined the asymmetric dynamics and causality of technological progress--proxied by green technology innovation--on both consumption-based carbon (CCO2) and territory-based carbon (TCO2) emissions in Saudi Arabia using quarterly data from 1990Q1 to 2021Q4. Our initial results reject the normality and linearity assumptions of data series and thus emphasize that the observed associations are quantile dependent. We firstly utilized the quantile-on-quantile regression (QQR) approach to draw the interdependency between green technology innovation and both CCO2 and TCO2 emissions. We found a strong emission-mitigating impact of green technology innovation only at (extreme) upper emission levels. We also identified a weak positive effect at (extreme) higher emission quantiles. Furthermore, we found that higher emission levels are linked with lower green technology innovation across all emission quantiles whereas a weak positive effect is perceived at lower and medium emission quantiles. We further utilized linear and nonlinear Granger causality-in- quantiles (GCQ) tests to capture an entire picture of the impact of green technology innovation on both CCO2 and TCO2 emissions. Under linear specifications of the quantile regression model, we found evidence of strong bidirectional causality between carbon emissions and green technology innovation across lower and upper quantiles. However, we found unidirectional causalities from carbon emissions to green technology innovation at medium quantiles of the conditional distribution. Besides, there is no causality at both extreme lower and extreme upper quantiles. Under nonlinear specifications of the quantile regression model, we found a weak unidirectional causality from green technology innovation to carbon emissions at (extreme) lower quantiles. We also found a weak unidirectional causality from carbon emissions to green technology innovation at medium and extreme upper quantiles. Overall, our findings indicate that green technology innovation helps abate both CCO2 and TCO2 emissions in Saudi Arabia. Our study shows policies that target green technology innovation would significantly change carbon emissions.

Repercussions of environmental policy stringency on carbon, energy and non-energy productivity in highly emerging economies: perspective of green growth

Emerging economies have prioritized the enhancement of carbon and energy productivity to uphold environmental integrity. Consequently, the policymakers introduced the environmental policy stringency measure to control emission activities. Accordingly, this study explores the environmental stringency policy's impact on carbon, energy, and non-energy productivity over the period of 1995-2020. This study addresses the impact of environmental policy stringency on quality of life (exposure to environmental risk). Regardless of variation, growing economies have higher carbon productivity. It is worth noting that energy productivity compared to carbon is higher. Based on the findings derived from the CS-ARDL model, it can be concluded that environmental stringency policies significantly positively impact carbon productivity in emerging countries. Economies that implement stringent environmental rules have the potential to enhance both energy and non-energy productivity to a greater extent. Meanwhile, the environmental policy effectively reduces environmental risk exposure and increases the quality of life. Environmental technology is inefficient in promoting emerging economies' environmental productivity. Similarly, trade promotes carbon activities and may involve comparative advantage race, pollution heaven hypothesis possible to exist. This study provides empirical evidence supporting the notion that investing in human capital is crucial in enhancing productivity. The findings suggest a more comprehensive and integrated approach to environmental policy in rising economies. This all-encompassing strategy is considered crucial for making significant gains in carbon productivity and simultaneously promoting sustainable green growth.

Do green financial and non-financial policies achieve the carbon neutrality target?

Due to the pressing need to combat climate change, reaching carbon neutrality-defined as having net-zero greenhouse gas emissions-has elevated to the status of a worldwide priority. While non-financial policies concentrate on regulation and incentives to promote environmentally friendly behavior, green financial policies strive to move investment toward low-carbon and sustainable initiatives. Therefore, the study aims to examine how green financial and non-financial policies affect carbon neutrality in China from 1995 to 2021. For analyzing the linear and nonlinear estimates, the study has employed the autoregressive distributed lag (ARDL) and nonlinear autoregressive distributed lag (NARDL) frameworks. The findings suggest that in the linear framework, green finance policies and environmental policy stringency encourage renewable energy consumption and discourage CO2 emissions. In the nonlinear framework, the positive shocks in the green finance policies and environmental policy stringency increase renewable energy consumption, and the negative shock in both types of policies discourages renewable energy consumption. In the CO2 model, a positive shock in green finance policies and environmental policy stringency reduces CO2 emissions, and a negative change in both these policies is insignificant. Since the positive and negative changes in both these policies significantly and differently impact renewable energy consumption and CO2 emissions; thus, policymakers should take into account positive and negative changes in both these policies while formulating policies for carbon neutrality targets in China.

Investigating the Causality Between Financial Development and Carbon Emissions: A Quantile-Based Analysis

The relationship between financial development and environmental sustainability has received significant attention in academic discourse. This study explores the crucial role of financial development in addressing the challenge of increasing CO2 emissions. Using quantile-on-quantile and nonparametric causality-in-quantile methodologies, this research investigates the impacts and causal links between financial market and institution development and CO2 emissions levels in five major polluting countries from 1990 to 2019. The findings provide strong evidence regarding the impact of financial institutions and financial market development on CO2 emissions, demonstrating the presence of shocks and nonparametric causality from financial institutions and financial market development to CO2 emissions quantiles. However, the effects of financial institution shocks and nonparametric causality are diverse and asymmetric across the sample. Positive and negative shocks are observed in India, while only negative shocks are observed in China, the USA, Russia, and Japan. Moreover, the findings reveal that the influence of financial market development on CO2 emissions varies across countries, with both positive and negative shocks transmitted to CO2 emissions in the USA, Russia, and Japan, indicating higher volatility in these countries compared to China and India, where only negative shocks are observed. Therefore, our recommendation emphasizes the prioritization of environmentally conscious financial products and the enhancement of the financial system's capacity to mitigate positive shocks contributing to increased CO2 emissions. Implementing this strategy requires collective efforts to embrace sustainable financial practices that consider the environmental impact of financial activities.

Environmental management through examining the technical factors of carbon emissions in South Asian economies

COP27 has provided a new direction in overcoming the issue of climate change. In the world of growing environmental degradation and climate change issues, the South Asian economies are playing a vital role in tackling these issues. Still, the literature focuses on industrialized economies while ignoring the newly emerging economies. This study evaluates the technological factors' influence on carbon emission in the four small South Asian economies (Sri Lanka, Bangladesh, Pakistan, and India) from 1989 to 2021. This study found the long-run equilibrium relationship between the variables using second-generation estimating tools. Employing the non-parametric and robust parametric approach, this study found that economic performance and development are substantial emissions drivers. In contrast, energy technology and tech innovation are the region's key environmental sustainability factors. Further, the study found that trade positively yet insignificantly impacts pollution. This study suggests further investment in energy technology and technological innovation to improve the production of energy-efficient products and services in these emerging economies.