Assessing green financing with emission reduction and green economic recovery in emerging economies

The aim of the study is to assess the role of green financing on carbon emission reduction and green economic recovery in emerging economies context. The BCC DEA technique of data envelopment analysis (DEA) is used to examine the nexus among variables by applying small input-output estimation parameters. Researchers found that green financing strategies like government subsidies and tax refunds for green financing are effective in cutting carbon emissions in developing nations. As a result, a panel of data from 2016 to 2020 is employed. Green financing measures assist reduces carbon emissions and prolong the green economic rebound, according to our research. Renewable energy companies had better ranges of total investment efficiency and size efficiency, and their levels of green economic recovery promotion were more than 0.457% percent, with a reduction in carbon emissions of 29.7 percent in developing countries backed by present government subsidies of 16 percent and taxes rebates of 11 percent. Green financing policies have a favorable impact on the green economy's revival. The study's policy implications include that green financing policies be implemented successfully to reduce carbon emissions more efficiently and to make climate change beneficial to countries in order to promote economic recovery over time.

Mechanism analysis of influencing factors on financing efficiency of strategic emerging industries under the "dual carbon" background: evidence from China

In order to deal with severe problems such as environmental pollution and climate change, the Chinese government has proposed the goal of carbon neutrality in 2030 and carbon peak in 2060. Strategic emerging industries have become key areas of high-quality growth of green economy. In order to solve the practical problems of insufficient funds and financing constraints, this paper empirically measures the financing efficiency of strategic emerging industries. Based on the Super Slack-Based Measure model, this paper selects the data analysis of listed companies in Beijing, Tianjin and Hebei from 2011 to 2020. At the same time, this paper systematically combs the index system that affects financing efficiency based on grounded theory. Based on the binary relation and structural level of adjacent matrix and reachable matrix, the explanatory analysis is carried out. On this basis, a systematic GMM model is established to explore the significance of different factors influencing financing efficiency. The research shows that the strategic emerging industry is still in the initial stage, the financing efficiency is not high and the financing output is insufficient. The factors affecting financing efficiency can be divided into 6 dimensions, 20 indicators in total and 5 multipole hierarchical levels. Credit financing, equity financing, financing constraints, technological innovation and government support are the important factors affecting financing efficiency.

Evaluation of financing efficiency of strategic emerging industries in the context of green development: evidence from China

Strategic emerging industries are key areas to transform the traditional industrial model of high pollution, high energy consumption, and high emissions. This paper focuses on the measurement of financing efficiency of strategic emerging industries. On the one hand, in order to overcome the interference of external environment and statistical error existing in the traditional single data envelope model, the SSBM-BOOT five-stage model is proposed. On the other hand, Malmquist index method and Luenberger productivity method are combined to evaluate dynamic efficiency, which select Beijing-Tianjin-Hebei listed companies' data. The results show that (1) external environmental factors play a significant role in financing efficiency. The empirical results of the SSBM-BOOT five-stage model show that environmental factors "raise" the efficiency value of the whole Beijing-Tianjin-Hebei region. (2) Based on the revised data and the overall and decomposition results of SBM-ML index, it can be seen that the regional industry is still in the stage of scale expansion, and the financing efficiency depends on technological innovation that needs to be improved. Finally, the paper puts forward the concrete strategies of creating industrial development environment, promoting technological innovation, and establishing green investment and financing mechanism.

Assessing the impact of green fiscal policies and energy poverty on energy efficiency

This article estimates the ties between green fiscal policies and energy efficiency in COVID-19 era. For this purpose, data envelopment analysis (DEA) approach is considered and applied. The study findings show that green fiscal policies, such as public supports and tax rebates, have significant role in reducing energy poverty of different international countries by advancing energy efficiency. Therefore, a panel data ranging from 2010 to 2020 is used. Our findings indicate that the aggregate degree of green fiscal policies help to decline energy poverty. Renewable energy companies had larger series of net fiscal competence and size efficiency, and their levels of energy efficiency were greater than 0.457%, with the 16% effect of current public supports and 11% effect of taxation rebates supported to diminish energy poverty with 29.7% in different international economies. This is a positive effect by green fiscal policies. The study also presented policy implications suggesting effectively implementing green fiscal policies for more efficient carbon reduction and making climate change supportive for peoples in post COVID-19 period.