Q56 - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population GrowthReturn

Green finance strategies have been established to direct funding towards green energy initiatives and promote the advancement of green technology for ecological sustainability. Moreover, the progress in green technology has played a significant role in the growth of green energy infrastructure in China. Nevertheless, there have been no prior investigations undertaken in China that specifically examine the impact of green financing and green technology on green energy within an asymmetric quantile framework. Thus, in the current study, a multivariate quantile-on-quantile regression (m-QQR) methodology is used to experimentally examine the link between green energy usage and green financing in China controlling the environmental sustainability index, green technology and economic progress utilizing data from 2000 to 2022. Results of this study confirm that China benefits in terms of rising green energy consumption only at the mid-levels of green investment projects, if more high-cost projects are added beyond this mid-level, the potential of the active projects diminishes and consumption of green energy declines. This study confirms the conservation hypothesis. A reverse relationship emerges between the consumption of green energy and environmental sustainability. Finally, green technology innovation is coupled with green financing for green energy transition. This study posits that the Chinese economy has the potential to experience significant benefits from the adoption of green energy, mostly driven by breakthroughs and the integration of green technology.

In the empirical determination of the factors influencing the clean energy transition, the BRICS economies have initiated various policy reforms, such as increased R&D budgets, improvements in technology and political stability. This study analyses the critical role of political risk and economic growth, natural resources, research and development and technological innovation in the clean energy transition in the period 1990-2022. Using panel econometric approaches, this study confirms the heterogeneity of slopes and cross-sectional dependence. Using linear regression with the heteroscedastic panel-corrected standard error approach, the results show that economic expansion, political risk and the quadratic R&D term significantly enhance the clean energy transition. However, natural resources, conventional technological innovation and research and development expenditures are the leading barriers to a clean energy transition in the region. The robustness of these results is validated by a series of panel regressions. Following the empirical outcomes, this study recommends rapid enhancement of the research and development budget, strengthening of governance and institutions and investment in technological innovation to attain a sustainable transition towards clean energy sources.

This study investigates the asymmetric effects of political stability and corruption on ecological footprint using time series data from 1984 to 2021 for Pakistan. The paper uses the nonlinear autoregressive distributed lag (NARDL) method to get accurate results regarding the positive and negative shocks of political stability. Besides, the NARDL method is utilized to identify the cointegrating link between the parameters, with a particular focus on uncovering asymmetric consequences in the long term. In addition, this research also includes natural resources, urbanization and economic progress in the model. The study results show that (i) political instability in Pakistan reduces environmental quality in both shocks; (ii) control of corruption increases the air quality in the negative shock; (iii) natural resources and urban population positively affect environmental quality; and (iv) economic progress has a favourable effect on environmental worsening. Additionally, the findings of the NARDL estimates and the outcomes of the robustness check are consistent. Particularly noteworthy is the fact that the general policy recommendation highlights the need for policymakers to vigorously synchronize their efforts to contend with the severe environmental degradation and political risk in Pakistan.

The interaction between socioeconomic disparities and environmental degradation, which is highly pertinent to the issue of climate change, has garnered significant scholarly attention globally. Despite the critical importance of climate change in political economy, research into labour markets and environmental policies remains limited in the current literature. Therefore, the present study discusses the implementation of China's low-carbon city pilot policy (LCCPP) as an exogenous policy shock. Utilizing A-share data from listed companies on the Shanghai and Shenzhen stock exchanges spanning the period 2007-2020, we employ a multiperiod difference-in-differences model to scrutinize the influence and mechanisms of LCCPP on employment. Our study reveals a significant increase in employment levels within pilot cities due to LCCPP. The findings remain stable even after the results are subjected to a battery of robustness tests. Mechanistic analysis suggests that the policy substantially increases employment through the scale effect and factor substitution effect. Heterogeneous results demonstrate the policy's substantial promotion of employment levels in pilot cities across state-owned enterprises, the first and second industrial sectors and low-carbon industry enterprises. These research findings support steering China's economic development towards a low-carbon, environmentally sustainable growth transformation. Furthermore, policymakers should encourage the LCCPP to stimulate employment while addressing socioeconomic disparities and environmental concerns simultaneously in political economy.

This study investigates the relationship between economic complexity, globalization, energy consumption patterns and CO₂ emissions in 12 energy-importing emerging economies from 1996 to 2020. Employing panel data analysis, the autoregressive distributed lag (ARDL) model is utilized. The findings reveal a U-shaped relationship between economic complexity and air pollution, supporting the environmental Kuznets curve (EKC) theory. Renewable energy demonstrates a significant ability to reduce CO₂ emissions over the long term, while fossil fuel use exacerbates environmental degradation. Economic globalization is associated with increased CO₂ emissions, contradicting expectations. The short-term results align with the long-term findings, highlighting significant country-specific variations. The policy implications highlight the necessity of promoting renewable energy adoption and reducing reliance on fossil fuels. This research contributes to EKC literature by focusing on energy-importing economies, emphasizing the importance of multidimensional analyses in environmental policy formulation. The study underscores the critical role of renewable energy investment and carbon pricing strategies in mitigating environmental degradation while encouraging sustainable development pathways.

This research covers the literature gap by investigating the factors of economic expansion (GDP), total natural resources (TNRNT), political risk index (PRI) and technological innovation (TI) and their impact on the renewable electricity output (REOT) in the G7 economies, covering the period 1990-2022. The research utilizes novel MMQREG as the primary method, while BSQR is a non-parametric robustness check method. A pairwise Dumitrescu-Hurlin causality test is employed to find out the causal connection between variables. The diagnostic outcomes show that the modelled variables are static after the first difference while long-run equilibrium is also present. Moreover, the outcomes suggest that GDP negatively influences REOT across quantiles while TNRNT and PRI stimulate the use of REOT in G7 economies across quantiles. Moreover, TI positively influences REOT but is inconclusive across quantiles. The robustness check analysis provides similar and valid outcomes. Lowering political risk is also considered important for energy transition in terms of cleaner energy.

Unclean energy consumption stimulates carbon footprint (CF) leading to increased environmental pollution. Renewable energy transition (ETN) can curb the CF; however, political risk can obstruct this process. Hence, this study analyses the connections between economic growth, ETN and CF by considering political risk and financial expansion in a panel of top 10 emitters from 1992 to 2020 using the method of moment quantile regressions (MM-QR). The results elucidate that ETN significantly reduces the CF in the top emitters. Thus, expanding the ETN is beneficial for reducing the CF and promoting sustainable development. Improving the political environment by reducing the political risk (POLR) helps curb the CF. The inverted U-shaped connection between CF and economic growth shows that increased growth can reduce CF if top emitters can continue to promote energy transition and political stability. The positive impact of financial expansion on CF becomes insignificant at higher quantiles. Finally, policy suggestions are discussed.

Green bonds have gained prominence on China's capital market as tools that help to fuel the transition to a climate-resilient economy. Although the issuance volume on the Chinese green bond market has been growing rapidly in recent years, the impact of the green label on bond pricing has not been studied adequately. Therefore, this paper investigates whether this newly developed financial instrument offers investors in China an attractive yield compared to other equivalent conventional bonds. By matching green bonds with their conventional counterparts and subsequently applying a fixed-effects estimation, our empirical results reveal a significant green bond yield premium of 1.8 basis points (bps) on average on the Chinese secondary market. As compared to Climate Bond Initiative (CBI) certified green bonds, we find that investors are more willing to accept lower yields (pay higher prices) to include People's Bank of China (PBOC) certified green bonds into their portfolio management. Thus, we argue that Chinese green investors prefer PBOC certified green bond over CBI certified green bonds on the Chinese market. Driven by pro- environmental preference, investors are also found to be willing to pay a higher price for green bonds issued by environmental, social and governance (ESG) performance-rated issuers. Our results point to some practical implications for investors and policymakers.