Impact of carbon disclosure on debt financing costs

Creditors,such as banks,often use disclosed environmental information to assess a company’s environmental risk and ensure the safety of debt funds.Consequently,carbon disclosures have become an important consideration for creditors when making investments.This study explores the relationship between carbon disclosure and debt financing costs using data on listed companies from 2008 to 2019.The results show that carbon disclosure can reduce the debt financing costs of enterprises,and that this influence is more significant for private companies than for state-owned enterprises.Instrumental variables and Propensity Score Matching(PSM)were used to evaluate the robustness of negative relationships.Furthermore,carbon disclosure has a more significant impact on debt costs with less environmental supervision pressure,weak residents’environmental awareness,and weak product market competition.These findings provide guidance for companies’carbon information disclosure and support the establishment of official carbon disclosure standards.

State-Owned Capital Participation in Private Enterprises:A Perspective of Debt Financing

This study takes debt financing as the entry point and explores the impact of state-owned capital participation in private enterprises from the perspectives of“unarticulated rules”and“articulated rules”.The study finds that state-owned capital participation significantly reduces the debt financing costs of private enterprises and expands the scale of their debt financing.This conclusion remains valid after a series of endogeneity and robustness tests.Further analysis of the mechanism reveals that state-owned capital participation improves the debt financing of private enterprises through multiple channels:Enhancing their social reputation,mitigating the“statistical bias”they face,optimizing their information quality,and reducing the“shareholder-creditor”agency problems.This paper conceptualizes these benefits as the“complementary advantages of heterogeneous shareholders”.This not only constructs a theoretical framework for“reverse mixed-ownership reform”but also better narrates the Chinese story of“mixed-ownership reform”by adopting a more universally applicable theory of equity structure.Additionally,the paper supplements existing research on the macro-and meso-level relationship between the government and the market by exploring the government’s positive role at the micro-level.

DEBT MATURITY STRUCTURE IN PROJECT FINANCING

Based on the concept of debt duration,this paper proposes the elasticity of cash flow.Then,the debt maturity structure in project financing is discussed.The results show that in the project financing structure,the debt maturity structure is closely related with debt capacity.Higher debt ratio requires short term debt,and vise versa.

A GATEWAY TO INTERNATIONAL CAPITAL MARKET——THE WHOLE CONRSE OF THE FIRST FOREIGN DEBT FINANCING FOR POWER PROJECTS IN CHINA

This paper introduces how Longyuan Power Group Company successfully carried out foreign debt financing for Jiangsu's power projects through its overseas financing window-Xiongya (Virgin) Co. Ltd. The entire process of raising funds is revealed with regard to employment of foreign debt financing, selection of funded projects, preparation of project and financing documents, credit rating, roadshow, line of credit, and financing experiences.

Deep Learning for Financial Time Series Prediction:A State-of-the-Art Review of Standalone and HybridModels

Financial time series prediction,whether for classification or regression,has been a heated research topic over the last decade.While traditional machine learning algorithms have experienced mediocre results,deep learning has largely contributed to the elevation of the prediction performance.Currently,the most up-to-date review of advanced machine learning techniques for financial time series prediction is still lacking,making it challenging for finance domain experts and relevant practitioners to determine which model potentially performs better,what techniques and components are involved,and how themodel can be designed and implemented.This review article provides an overview of techniques,components and frameworks for financial time series prediction,with an emphasis on state-of-the-art deep learning models in the literature from2015 to 2023,including standalonemodels like convolutional neural networks(CNN)that are capable of extracting spatial dependencies within data,and long short-term memory(LSTM)that is designed for handling temporal dependencies;and hybrid models integrating CNN,LSTM,attention mechanism(AM)and other techniques.For illustration and comparison purposes,models proposed in recent studies are mapped to relevant elements of a generalized framework comprised of input,output,feature extraction,prediction,and related processes.Among the state-of-the-artmodels,hybrid models like CNNLSTMand CNN-LSTM-AM in general have been reported superior in performance to stand-alone models like the CNN-only model.Some remaining challenges have been discussed,including non-friendliness for finance domain experts,delayed prediction,domain knowledge negligence,lack of standards,and inability of real-time and highfrequency predictions.The principal contributions of this paper are to provide a one-stop guide for both academia and industry to review,compare and summarize technologies and recent advances in this area,to facilitate smooth and informed implementation,and to highlight future research directions.

Manager’s Characteristics, Debt Financing and Firm Value

Based on the behavioral finance theory and the upper echelons theory, this paper employs the data of China's A-share listed companies from 2008 to 2013 as research samples, and empirically tests the effects of managers with different characteristics on debt financing and firm value for enterprises of different ownership nature. Results of this study indicate that the debt financing of the listed companies in China can reduce the agency cost with a positive governance effect that promotes firm value. Male, better educated, short-tenured, and financially experienced managers are more likely to be overconfident and prefer debt financing. Specifically, the manager's age, level of education, and work experience can significantly promote the effect of debt financing on firm value. Compared with SOEs, private enterprises can improve their firm value more significantly through debt financing;the education and work experience of the managers of private enterprises are more positively correlated with debt financing and can more significantly improve firm value through debt financing. This paper's findings suggest that the manager's characteristics and firm ownership nature must be taken into account to reach valid conclusions on the governance effects of debt financing on firm value. Meanwhile, these conclusions help unravel the mechanism and economic implications of debt financing, and contribute to the improvement of the capital structure decisions and human resources management practices of China's listed companies. This study not only enriches the literature and empirical evidence on the correlation between managers' characteristics and firm financing, but indicate that managers' characteristics and firm ownership are important considerations for investigating the governance effects of debt financing on firm value and have a vital impact on the formulation and implementation of firm financing decisions.

Research on the Correlation between Accounting Information Distortion and Corporate Debt Financing

Accounting information plays a key role in economic development. Macroscopically speaking, accounting information isthe basis of macro-decision-making. Microscopically speaking, accounting information is the effective embodiment of enterprise＇smanagement ability and status, and is also the basis for many investors to make reasonable investment decisions. Therefore, it can beseen that the distortion of accounting information will cause negative effects in many aspects. Ringing. Based on this, this paper selectsA-share non-financial listed companies in Shanghai and Shenzhen Stock Exchanges fi＇om 2011 to 2016, analyzes the impact ofaccounting information distortion on corporate debt financing costs, and introduces internal control into the study of the relationshipbetween the tw0. Through empirical analysis, we find that： the effectiveness of internal control and debt financing costs significantlynegative correlation; accounting fraud and accounting manipulation are two indicators of accounting information distortion and corporatedebt financing costs significantly positive correlation; internal control can significantly inhibit the correlation between accountinginformation distortion and debt financing costs.

Research on the Influence of Debt Financing on Corporate Investment--Based on Political Relations Perspective

we have done the research on the influence of debt financing on corporate investment Based on political relations perspective. The results show that the impact of debt financing on corporate investment from the political perspective and confirmed debt financing is more easily lead to inefficient investment under the influence of political relations.

The Impact of Debt Financing on Corporate R ＆ D Investment Behavior in China ——Based on the Empirical Evidence of Listed Companies from 2004 to 2011

Base on panel data of manufacturing and high-tech industry companies which discoursed R ＆ D expenditure in financial statements from 2004 to 2011, this paper studies the relationship between debt financing and corporate R ＆ D expenditure under different grow opportunities by using the robust fixed effects that Daniel Hoechle proposed m 2007. The results show that there is not a ＂increasing first, decreasing later＂ non-linear relationship but a ＂double negative＂ relationship between debt level and corporate R ＆ D expenditure. And the ＂double negative＂ relationship has a different mechanism in different growth companies.

Research on the Impact of Social Credit Improvement on the Debt Financing of Agricultural Enterprises

This study takes China’s A-shares agricultural companies as the research subjects and examines the influence of social credit environment on the debt financing of agricultural enterprises.This study has found that the improvement of social credit environment can significantly increase the debt financing scale of agricultural enterprises.After a placebo test,the replacement of explained variables,and the control of industry fixed effects,the results obtained are still significant.The mechanism test found that the scale of the enterprise has a complete intermediary effect;that is,the social credit environment can increase the scale of external financing of agricultural enterprises by increasing the scale of the enterprise.This article focuses on the impact of informal institutions on corporate debt financing,which is conducive to enriching relevant research on agricultural enterprises and has important practical significance for promoting the development of the agricultural industrial chain as well as“village revitalization.”

The Selection of Financing Methods for Small and Medium Sized Technology Enterprises

Equity financing and debt financing are the main financing methods for small and medium sized enterprises. Based onthe samples of small and medium-sized enterprises listed on the Shenzhen Stock Exchange during 2010 and 2015, we collected theturnover data and studied the influence factors in financing and constraints. The results show that science and technology enterpriseshave different tendency in equity financing in different stages of social development. In the stage of social currency additional, theseenterprises tend to debt finaneing. Besides, those science and teehnology enterprises with better ability in sustainable development andinnovation ability are easier to get equity investment; those enterprises with more enterprise strength and government subsidies seemedmore sueeessfully in obtaining debt investment.

An Instrument Variable Model of the Impact of Financing Decisions on Performance of Small Businesses in Australia＇s Pre-global Financial Crisis

Firm level empirical research on the impact of financing decisions on small business performance is scarce in the Australian context. This study adopts an instrument variable （IV） approach to analyze the impact of financing decisions, in particular, equity or debt are obtained, on the performance of small businesses by using the panel data from Australian Bureau of Statistics （ABS） Business Longitudinal Database （BLD） 2004-2005, 2005-2006, and 2006-2007. Performance variables, i.e., sales and expenditure, are used as dependent variables. Equity and debt obtained are used as independent variables （or known as treatments）. IV includes size of the business, age of the business, number of locations, and industry division etc.. The results from IV modeling outperformed those obtained from OLS （Ordinary Least Squares）. Findings include： （1） financing has significantly positive impacts on the performance of small businesses in Australia; （2） equity and debt financing are used as alternatives, comparatively, equity financing is preferred; （3） capital purchases are largely funded by debt financing, while non-capital purchases and salary expenses are funded by equity financing; and （4） equity financing is more often used by firms with increasing capital purchases and declining non-capital purchases, while debt financing is used by firms with the opposite trends. The paper concludes with a discussion of the limitations of this research and future research＇s directions.

产业政策促进企业创新的传递机制与情境条件——来自沪深A股上市公司的经验证据

近年来,随着中国企业逐渐接近技术创新的前沿,技术追赶的空间被进一步压缩,经济发展和产业政策面临着越来越大的挑战。文章以2008—2021年沪深A股上市公司为样本,考察产业政策对企业创新的影响,并分析了其传递机制和情境条件。实证结果表明,产业政策对企业的创新活动表现出“双重利好”效应,将同时提高被支持行业中企业的创新数量与创新质量。传递机制分析表明,产业政策主要通过抑制企业金融化程度、提高政府补贴力度、降低债务融资成本、带来更多分析师关注等中介因素驱动企业创新水平的提升。情境条件分析发现,产品竞争市场治理、新闻媒体治理、公司治理、研发投入和高管团队研发经验会加强产业政策对企业创新的正向效应。进一步研究表明,发明专利对企业价值有正向影响且该效应具有一定的持续性,而非发明专利对企业价值有负向影响且该效应不具有持续性。研究揭示了产业政策促进企业创新的传递机制与情境条件,为客观评估中国产业政策的经济效应提供了微观依据。

数字金融对地方政府债务的影响研究——基于省级面板数据的实证检验

本文基于2015—2021年中国省级面板数据实证研究数字金融对地方政府债务的影响,发现两者呈现出显著为负的非线性关系,数字金融的发展对地方政府优化自身债务、降低系统性金融风险具有积极作用。采用系统聚类将31个省(区、市)分为发展中、次发达、发达地区三大组别,发现数字金融对地方政府债务的抑制作用在发展中地区表现得最为显著。市场化水平在数字金融抑制地方政府债务过程中具有正向调节作用,特别是当市场化水平跨越一定的门槛值以后,数字金融对地方政府债务的影响显著增强。在此基础上,提出了数字金融背景下分类施策缓解各级地方政府债务问题的相关建议。

不同集中度下供应商稳定性对公司债务融资成本的影响

近年来,上市公司供应商断供事件频发,对公司的经营管理产生了不可忽视的负面影响,引起了社会各界的广泛关注。基于此,从外部利益相关者债权人的视角,收集整理2008—2021年沪深A股804家上市公司2825个年度供应商稳定性数据,实证检验供应商稳定性对公司债务融资成本的影响及其机制。研究发现,供应商稳定性能够显著降低公司的债务融资成本,表明外部债权人更看好供应商关系稳定的公司。调节机制分析表明,较高的供应商集中度会削弱供应商稳定性对债务融资成本的降低效应。在采用替换变量、更换回归模型、赫克曼两步法、倾向得分匹配法进行稳健性检验后,以上结论仍然成立。从作用机制上看,供应商稳定性通过提升供应链效率降低债务融资成本。异质性分析发现,在大规模公司、行业市场竞争程度较强及地区市场化程度较高的公司样本中,供应商稳定性对债务融资成本的降低效应更显著。为更有效降低公司债务融资成本,公司应重视供应商的管理和维护,保持稳定的供应商关系,提高供应链效率;为充分发挥供应商稳定性对公司债务融资成本的降低效应,应将供应商集中度控制在合理水平;应实施差异化供应商管理策略,大规模公司、行业市场竞争较强及地区市场化程度较高的公司要高度重视供应商稳定性的促进作用,着力完善供应商关系管理,促使公司确定更合理的供应商稳定性水平。

数字金融、家庭债务与金融整治——基于P2P网贷风险专项整治的实证研究

基于中国家庭金融调查(CHFS)2013年、2015年、2017年和2019年四期数据,构建Probit模型和固定效应模型分析数字金融对家庭债务的影响,并基于近年来金融整治的一个典型样本——P2P网贷风险专项整治,构建强度DID模型探讨实行金融整治政策能否有效降低家庭债务。研究发现:(1)数字金融的使用显著提高了家庭负债概率和债务水平;(2)金融整治之后,使用数字金融家庭的债务水平出现显著降低;(3)异质性分析显示,金融整治政策对使用数字金融的家庭的债务缓解作用,在中西部地区、贫困家庭和农村家庭中更为显著,在我国打赢脱贫攻坚战和实施乡村振兴战略进程中发挥了有益作用。研究结论对我国规范发展数字金融、防范金融风险、巩固拓展脱贫攻坚成果同乡村振兴有效衔接等方面有着重要的政策启示。

高管团队稳定性、债务融资成本与数字化转型——基于创新效率的调节作用

针对高管团队稳定性、债务融资成本对数字化转型的影响问题,选取2017—2021年中国A股制造业上市企业作为样本进行实证研究。研究表明:高管团队稳定性有利于企业数字化转型;高管团队稳定性有利于降低债务融资成本;债务融资成本在高管团队稳定性对数字化转型的影响过程中发挥中介作用;创新效率正向调节高管团队稳定性对数字化转型的促进作用。异质性分析发现,国有企业的高管团队稳定性对数字化转型的促进效应更强,且网络基础设施建设程度也会对二者关系造成影响。

货币政策不确定性与企业债务成本

降低企业债务融资成本是促进实体经济高质量发展的重要举措。选取2007—2020年A股非金融上市公司数据,系统考察货币政策不确定性对企业债务成本的影响。研究结果表明,货币政策不确定性与企业债务成本显著正相关。影响机制分析发现,债务违约概率是货币政策不确定性影响企业债务成本的中间变量,即货币政策不确定性上升会增加企业债务违约概率,从而导致企业债务成本上升。异质性分析发现,货币政策不确定性对非国有企业、小规模企业及非周期性行业企业债务成本的正向影响更加明显。研究表明降低货币政策不确定性对于缓解企业债务成本压力具有重要作用。

公开发行债券能提高企业创新产出吗?

以2006-2021年我国A股上市公司为样本,探讨了企业首次发行债券如何影响企业的创新水平。研究发现,企业首次公开发行债券能够显著提升企业的创新水平。机制分析结果表明,企业发行债券通过建立替代性融资渠道缓解融资约束,延长整体债务期限,提高信息披露水平这三个路径来提升企业创新水平。进一步研究发现,在控制了企业后续发债行为后,公开发行债券与企业创新的关系仍然存在;相比于公司债,企业首次发行债券种类为中期票据和企业债时,企业创新水平提升更显著;企业首次发行债券时,债券信用评级越高、发行利率越低,对于企业创新水平的提升越显著。研究结论丰富了债券市场经济后果的研究,也为企业创新发展和实现经济高质量发展提供了来自债券市场的建议。

绿色信贷对“两高”企业债务融资规模影响研究

党的十八大以来,我们党领导全国人民坚持以新发展理念为引领,坚定不移走生态优先、绿色发展道路,大力推行经济社会绿色发展转型升级并取得显著成效。在绿色发展进程中,绿色信贷这一金融利器发挥了应有的作用。以2012年《绿色信贷指引》的发布为切入点,选取2009—2022年A股“两高”企业上市公司作为研究样本,将企业异质性和区域异质性纳入绿色信贷政策实施的影响机制;同时加入产权和区域的交乘项进行回归分析。研究表明,绿色信贷在一定程度上降低了“两高”企业的债务融资规模,且对非国有企业与中西部地区企业债务融资水平的牵制更强。