Financing Efficiency Evaluation and Influencing Factors of Hydrogen Energy Listed Enterprises in China

Existing studies of financing efficiency concentrate on capital structure and a single external environment or internal management characteristic. Few of the studies include the internal and external financing environments at the same time for hydrogen energy industry financing efficiency. This paper used the data envelopment analysis (DEA) model and the Malmquist index to measure the financing efficiency of 70 hydrogen energy listed enterprises in China from 2014 to 2020 from both static and dynamic perspectives. Then, a tobit model was constructed to explore the influence of external environment and internal factors on the financing efficiency. The contributions of this paper are studying the internal and external financing environments, and integrating financing cost efficiency and capital allocation efficiency into the financing efficiency of hydrogen energy enterprises. The results show that, firstly, the financing efficiency of China’s hydrogen energy listed enterprises showed an upward trend during the years 2014–2020. Secondly, China’s hydrogen energy enterprises mainly gather in the eastern coastal areas, and their financing efficiency is more than that in western areas. Thirdly, the regional economic development level, enterprise scale, financing structure, capital utilization efficiency and profitability have significant effects on the financing efficiency. These results can promote the achievement of “carbon neutrality” in China.

Applying analytic hierarchy process (AHP) to identify decision-making in soybean supply chains: a case of Mato Grosso production

This paper aims to identify and analyze the factors that influence the decision of Mato Grosso’s farmers to produce soybean using the Analytic Hierarchy Process (AHP). We found evidence that decision-making of soybean production is related to rural production aspects such as climate, financing, cost of inputs, and soil quality rather than marketing and logistics. The novelty of this paper is the empirical analysis of the decision-making in agricultural production using AHP. The decision model was created and tested considering 21 farmers and 19 experts linked to the soybean production. Three different scenarios were considered: farmers' view, experts' view, and combined view. Our findings indicate that farmers and experts agree with rural aspects are predominant in the decision to plant soybean. Moreover, logistics have been used as an important flag of soybean competitiveness on international trade by soybean stakeholders in Brazil. However, our results show that logistics impact in the soybean decision-making process is low. Due to data limitation access, this study focuses only on Mato Grosso. However, this study has an exploratory character and presents empirical results that may help to understand soybean production over the country.

The Impact of Climate Change On Financing Cost of Heavy-Pollution Firms in China

We examines the effects of climate change on the financing cost of heavy-pollution firms using firm-level panel data analysis. The empirical results demonstrate that the annual temperature and precipitation changes can significantly promote the financing costs of heavy-pollution firms, the positive impacts of annual temperature and precipitation changes on the financing costs of large, medium and small heavy-pollution firms has shown a gradual weakening trend with an increase of firm size, and the positive effects of annual temperature and precipitation changes on the financing costs of younger and older heavy-pollution firms has shown a decline trend with an increase of firm age. The evidences confirms that the impact of climate change on the financing costs of heavy-pollution firms exhibit a significant firm size and age discrimination of financing behaviors. Government decision-makers have to identify and optimize the transmission effect of climate change response on financing behavior decisions of heavy-pollution industries, financial institutions alleviate financial conflicts and credit discrimination behaviors and optimize the efficiency of financial resource allocation. Firms’ executives correct climate change strategy, optimize the climate- relevant operation, investment and financing activities, and alleviate unfavorable influences of climate changes for heavy-pollution firms.

Construction of new financial e-commerce model for small and medium-sized enterprises financing based on multiple linear logistic regression

This paper expounds on the development prospects of SMEs and E-commerce finance, and illustrates the significance of developing online finance. It also introduces the commonly-used research methods of the two kinds of financial models, such as multiple linear regression method and logistic regression method, and analyzes the reasons for the financing difficulties of SMEs. Currently, the high financing cost is the main reason for the financing difficulties of SMEs. Several reasons are account for the high financing cost. Among them, high financing cost,low-efficiency financial system,long financing cycle and the loan information asymmetry account for 35%, 21%, 19% and25% respectively. In addition, this paper clarifies the advantages and disadvantages of network finance and the necessity of developing online finance.

Construction of a New Financial E-Commerce Model for Small and Medium-Sized Enterprise Financing Based on Multiple Linear Logistic Regression

This paper expounds on the development prospects of SMEs and E-commerce finance, and illustrates the significance of developing online finance. It also introduces the commonly-used research methods of the two kinds of financial models, such as multiple linear regression method and logistic regression method, and analyzes the reasons for the financing difficulties of SMEs. Currently, the high financing cost is the main reason for the financing difficulties of SMEs. Several reasons are account for the high financing cost. Among them, high financing cost,low-efficiency financial system,long financing cycle and the loan information asymmetry account for 35%, 21%, 19% and25% respectively. In addition, this paper clarifies the advantages and disadvantages of network finance and the necessity of developing online finance.

The Empirical Research on the Impact of Pro-Environmental Factors on the Financing Cost of Green Bond

Green bonds are an important part of green finance and a significant financing method for enterprises to make socially responsible investments. This thesis analyzes the impact of pro-environmental factors on the financing cost of green bonds by the data of green bonds issued from 2016 to 2020. The results show that the better the environmental performance of the issuer's region, the lower the financing cost of green bonds, and the third-party certification reduces the financing cost of green bonds. Further research shows that high pollution areas and high pollution industries enhance the punitive role of environmental pollution financing. Regional environmental performance mainly affects the financing cost of green bonds through tax suppression mechanism and credit penalty mechanism, while third-party certification affects the financing cost of green bonds through tax relief mechanism and financing channel mechanism. This paper provides empirical evidence and policy inspiration for reducing the financing cost of issuing green bonds and promoting the perfection of the green bond system.

Can Green Credit Policy Promote Green Innovation Efficiency of Heavily Polluted Industries? Empirical Evidence from the China’s Industry

Green credit policy as an important tool to guide China's sustainable economic development, how to effectively play the function of capital deployment and improve the efficiency of industrial green innovation is an important issue facing the construction of ecological civilization. This paper uses China's Green Credit Guideline introduced in 2012 as a quasi-natural experiment , based on relevant panel data of industries from 2007 to 2018, uses the Super-SBM model including non-expected output to measure the green innovation efficiency of 35 industries in China, and constructs the PSM-DID model to explore how green credit policy impact on the green innovation efficiency of heavily polluted industries, the results show that : green credit policy significantly contributes to green innovation efficiency of heavily polluted industries with a lag. Further study finds that green credit policy pushes heavily polluted industries to improve green innovation efficiency by increasing financing cost and R&D investment; meanwhile, the heterogeneity test shows that the higher the state-owned share of industry, the greater the promoted effect of green credit policy on green innovation efficiency of heavily polluted industries. Finally, in order to accelerate the implementation of green credit policy and promote the green innovation efficiency of heavily polluted industries, relevant countermeasures are proposed from three aspects: banks, enterprises and government.

Research on the Impact of Third-Party Certification on Green Bond Spread of the Green Industry－Considering the Effect of the Nature of Property Rights

Capital is the most basic element of production organization, and green bonds are important financing sources for the green industry. Financingcosts directly affect the steady development of the green industry. In order to verify whether third-party certification can reduce the financing cost of green bonds and whether the nature of property rights has an impact on the reduction, 285 green bonds issued from 2016 to 2019 are taken as samples, and then a hierarchical multiple statistical regression analysis method is adopted to conduct a quantitative study. The results show that third-party certification, as a unique credit enhancement method for green bonds, can significantly reduce green bond spreads. In addition, it isgreater that the effect on non-state-owned enterprises’ green bonds is. Since bond spread isamain part of financing costs, the above means that third-party certification can reduce the financing costs of green bonds, especiallyfor non-state-owned enterprises. In this regard, starting from reducing the cost of green bonds, the paper proposes to improve the green bond evaluation and certification standards as soon as possible, non-state-owned enterprises particularly should actively carry out third-party certification, and the government needs to further increase the implementation of third-party certification as well as strengthen multi-party cooperation.

Financing Advantage of Green Corporate Asset-Backed Securities and its Impact Factors: Evidence in China

As an innovative green financial tool, green corporate asset-backed securities can effectively solve the problems of narrow financing channels and maturity mismatches for green projects, which can help achieve green and low-carbon development, carbon peaking, and carbon neutrality goals. In this paper, we examine the financing cost advantages of green corporate asset-backed securities and the related impact factors through a combination of empirical and case studies. Empirical research based on the propensity score matching method (PSM) shows that China’s green corporate asset-backed securities issuance rates are 36.97°bps lower than traditional corporate asset-backed securities on average. Credit rating, issuance scale, issuance interest rate, issuance period, and green factors have become the main impact factors of green corporate asset-backed securities financing advantages.