The asymmetric influence of environmental-related technological innovation on climate change mitigation: what role do FDI and renewable energy play?

Mitigating environmental pollution in China: Unlocking the potential for high-quality innovation

The nexus between environmental pollution (EP) and technological innovation is crucial for achieving sustainable development. However, existing literature has paid less attention to the new form of high-quality innovation (HI) in environmental management. This paper uses panel data from 31 Chinese provinces from 2008 to 2020, employing the two-stage least squares method to investigate the relationship between HI and EP. The empirical results reveal that HI can effectively reduce the EP, which holds after multiple robustness tests, and this effect is more obvious in southern China. Meanwhile, HI drives clean and efficient energy transition and decreases EP. Moreover, increased environmental regulation weakens the influence of HI on EP. The major contributions of this study are constructing an HI index including innovation, human capital, and government support and examining its influence on EP in China. The findings encourage government to implement policies of innovation-driven transformation, energy conservation and emissions reduction.

Unveiling the power of education, political stability and ICT in shaping technological innovation in BRI nations

Technological innovation is a critical element of economic and environmental sustainability; thus, the promotion of technological innovation in the economy has gained an apex among policy makers. The study's impetus is to measure the effect of investments in information and communication technology (ICT), education, and political stability on technical innovation in BRI countries for 2004-2020. In the process of documenting the empirical nexus through the implementation of novel panel techniques commonly known as Dynamic Seemingly Unrelated Regressions (SUR), continuously updated fully modified" (Cup-FM) and continuously updated bias-corrected (Cup-BC). The results of the slope of heterogeneity, cross-sectional dependency test, and panel cointegration test have revealed the presence of heterogeneity, all the research variables possessed certain common dynamics, and, most importantly presence of long-run association. The study documented the coefficients of ICT, education and Political stability are positive and statistically significant, indicating a contributory effect in fostering technological innovation in BRI nations. The findings emphasize the importance of upholding political stability, directing resources toward education, and fostering an environment that encourages innovation through the integration of information and communication technology (ICT). The study also highlights how critical it is to bring in FDI and use it to your advantage in order to boost tech development and the economy.

Decarbonization through sustainable energy technologies: Asymmetric evidence from 20 most innovative nations across the globe

Since the discharge of carbon is one of the main causes for ongoing global warming issue and change in climate, most nations have committed to decarbonizing their economies at the COP26 summit. Thus, this investigation aims to explore the consequences of innovations in sustainable energy technologies on decarbonization in the 20 most innovative nations across the globe. In assessing the cause-and-effect relationship, we have used “Panel Non-linear Autoregressive Distributed Lag (P-NARDL)” technique. The findings demonstrated that the variables have a lasting relationship. The positive asymmetric shock in the innovations in sustainable energy technologies has a positive influence on the decarbonization of these nations, while the negative asymmetric effect is insignificant. According to the findings, clean energy negatively consequence on carbonization whereas growth in economy is favorably and considerably connected with it. The findings demonstrate that there is bidirectional causation between all variables under investigation, with the exception of the unidirectional causality flows from the usage of sustainable energy technology and emissions of CO2. In a global context, this research suggests that government should identify the roles of new sustainable energy technologies by reforming patenting regulations to rectify the environmental damages.

Changes in environmental degradation parameters in Bangladesh: The role of net savings, natural resource depletion, technological innovation, and democracy

Most researchers consider CO₂ emissions to be the primary indicator of environmental degradation. Similarly, ecological footprint appears to be a significant proxy for environmental degradation in recent research due to its multifaceted impact on the natural environment. With this in mind, this study investigates fluctuations in CO₂ emissions and ecological footprint as indicators of environmental degradation in Bangladesh from 1980 to 2020, and how they are influenced by net savings, natural resource depletion, technological innovation, and democracy. The non-linear ARDL (NARDL)-based asymmetric analysis finds that positive changes in net savings, natural resource depletion, and democracy positively impact both parameters of environmental degradation in the long run. On the other hand, a positive change in technological innovation reduces these parameters in the long run. Likewise, negative changes in net savings and technological innovation reduce environmental degradation. In contrast, negative changes in natural resource depletion and democracy exacerbate these two parameters and degrade environmental quality in the long run. However, there are some variations in the short-run influence of the predictors on the predicted variable. Overall, the findings of this study suggest that policymakers must strategically exploit natural resources, net savings, technology diffusion, and democratic principles to preserve the natural environment in Bangladesh.

Investigating the nexus between trade policy uncertainty and environmental quality in the USA: empirical evidence from aggregate and disaggregate level analysis

Worldwide, environmental sustainability is a hot topic, particularly in industrialized countries due to their higher emission intensity. Environmental conservation and equitable economic growth have been prioritized in economic debate and policy development. Over the past three decades, the USA's emissions of carbon dioxide (CO₂e) have risen exponentially, as trade policy uncertainty (TPU). In this circumstance, this paper aims to contribute to the existing literature by exploring the effect of TPU on environmental quality by controlling the energy consumption, economic growth, and population in the USA over the period 1985M1 to 2022M3 employing the augmented ARDL and NARDL procedures in the presence of structural breaks. From our analysis, the results revealed that TPU affects negatively CO₂e in the residential sector, and negative changes in TPU positively affect CO₂e in the commercial sector both in the long and short run. On the other side, the outcomes show that energy consumption is a crucial key determinant factor in environmental degradation at the aggregate level and in all sectors. Furthermore, our findings clarify that economic growth upsurges the CO₂e at the aggregate level precisely in the industrial and residential sectors. Juxtaposing, in the long run, the results indicate that population growth could make additional pressure on environmental quality at the aggregate level, especially in commercial, power generation, and residential sectors. Accordingly, it is clear from our results that the regulations put in place to encourage Americans to buy locally created goods instead of those imported, especially in light of the high levels of TPU, maybe the best option to decrease the long-term impact of international trade on the environment to achieve sustainable development goals (SDGs).

Analyzing the role of green innovation and public-private partnerships in achieving sustainable development goals: a novel policy framework

The environment's quality is the cornerstone for every country's long-term growth. Pakistan, like other countries, is embracing modern, efficient technologies to build a sustainable environment following the SDGs. In this situation, policymakers and experts have emphasized more on environmental factors. To do this, the study explores the impact of green innovation (GI), public-private partnerships in energy (PPP), energy use (EU), economic development (ED), and power prices (PP) on CO2 emissions in Pakistan from 1980 to 2019. The research uses a novel econometric technique for estimating environmental factors, notably the dynamic autoregressive distributed lag simulations (ARDLS) model and spectral frequency domain causality (SFDC), to examine positive and negative shocks for the prediction of the short-, medium-, and long-run impact of selected determinants, respectively. Additionally, robustness checks were performed using the fully modified OLS (FMOLS), dynamic OLS (DOLS), and canonical cointegrating regression (CCR) estimations. The short and long-term empirical findings indicate that GI lowers emissions; nevertheless, PPP, EU, and ED have a significant impact on emissions in the short run, while the EU increases emissions in the long run. PP, on the other hand, reduces emissions both short and long-term. The FMOLS, DOLS, and CCR estimations indicate significant discoveries. Additionally, the SFDC finding supports the long, medium, and short-term causation theories. This research advocates green innovation for a greener manufacturing process and PPP investment in renewable energy. In addition, the Pakistani government considers these variables while designing a comprehensive protracted environmental plan to meet SDGs 7 and 13.

Can financial globalization and good governance help turning emerging economies carbon neutral? Evidence from members of the BRICS-T

Since turning carbon neutral is regarded as a major macroeconomic agenda worldwide, this study examines whether financial globalization and good governance can help Brazil, Russia, India, China, South Africa, and Turkey in achieving carbon neutrality. Considering the period of analysis from 2000 to 2020 and utilizing robust econometric methods, it is observed that the environmental consequences vary across different components of financial globalization. In particular, the results validate the pollution haven hypothesis by confirming the carbon emission-boosting effect of de facto financial globalization indicators. In contrast, the pollution halo effect hypothesis is verified by the finding of the carbon emission-abating effect of de jure financial globalization indicators. Besides, promoting good governance is evidenced to impose carbon emission-mitigating impact in the long-run. The findings also authenticate the existence of the Environmental Kuznets Curve (EKC) hypothesis for the emerging countries of concern. Finally, for both the short and long runs, it is found that the non-renewable to renewable energy transition contributes to lower discharges of carbon dioxide, while urbanization results in the amplification of the carbon emission figures. Considering these critically important findings, it is necessary for these countries to impose restrictions on the influx of unclean foreign direct investment, facilitate and ease the investment process for foreign investors for investing in environment-friendly projects, promote good governance, and adopt green economic growth and sustainable urbanization policies by developing their respective renewable energy sectors.

Investigating the nexus between carbonization and industrialization under Kaya's identity: findings from novel multivariate quantile on quantile regression approach

Developing nations aim to industrialize and grow sustainably often ignoring the environmental consequences. However, few empirical studies have looked at the influence of industrialization-driven economic transition on carbon footprint in developing nations using a non-parametric approach. In this milieu, on the ground of Kaya's identity and the novel multivariate quantile-on-quantile regression (QQR) (extension of Sim and Zhou's (2015) bivariate QQR model), the present research studies the impact of industrial value-added (IGVA), population, energy intensity, and carbon intensity on CO₂ emissions in India. This study is one of the first in the literature to evaluate the industrialization-carbonization nexus in the context of Kaya's identity for the Indian economy utilizing an innovative multivariate QQR approach, which makes a methodological and empirical addition to the literature. The outcomes of the multivariate QQR technique demonstrate that economic and environmental development requires continual long-run strategies. The empirical findings revealed that there is no authentication that India's carbon emissions increased due to its industrialization, which exhibited that IGVA has a negative and significant connection with CO₂ emissions. In some quantiles, population size positively impacts CO₂ emissions. On the other hand, carbonization in the Indian economy is asymmetrically affected by GDP per capita and energy and carbon intensity. The quantile Granger causality study further supported the aforementioned results. The current analysis also offers policy suggestions for environmentally friendly sustainable economic growth and to achieve the sustainable development goals (SDGs) of India.

Can Renewable Energy and Export Help in Reducing Ecological Footprint of India? Empirical Evidence from Augmented ARDL Co-Integration and Dynamic ARDL Simulations

The objective of this study is to investigate the impact of exports, renewable energy, and industrialization on the ecological footprint (EF) of India over the period spanning from 1970–2017 by employing the newly developed augmented ARDL (A-ARDL) co-integration approach and the novel dynamic ARDL (D-ARDL) technique. The empirical results demonstrate that exports and renewable energy consumption reduce the EF, while industrialization intensifies the EF. More precisely, a 1% increase in export (renewable energy consumption) reduces the EF by 0.05% (0.09%). In addition, the short-run elasticity of the GDP is found to be larger than the long-run elasticity indicating the possibility of the existence of the Environmental Kuznets Curve (EKC) of the EF for India. The study indicates that the income effect and increased policy focus on renewable energy usage can be expected to reduce India’s per capita EF in the long run. Moreover, India’s export sector has been traditionally less energy intensive, which reflects in our findings of export growth leading to a reduction in EF. Based on the empirical findings, this study recommends some policy insights that may assist India to effectively reduce its ecological footprint.