Credit Rating Research Articles

The impact of environmental, social, and governance ratings on corporate innovation: From the perspective of informal institutions

AbstractThe significance of rating events in capital markets has garnered considerable attention from investors, experts, and academics, with third‐party rating agencies being one of the topics. We focus on the impact of environmental, social, and governance (ESG) ratings on corporate innovation and confirm a positive relationship. We also believe that ESG ratings play a governance role as informal institutions in stimulating corporate innovation. The efficacy of ESG ratings in promoting corporate innovation is dependent on a favorable information environment that is devoid of negative influences. We confirm the synergistic effect of ESG ratings with other informal institutions and the substitution effect with formal institutions.

Does environmental credit rating policy improve corporate ESG performance?

AbstractEnvironmental credit evaluation is essential for the establishment of an environmental financial system, but most studies have focused on the impact of green financial instruments such as green credit and green bonds, resulting in insufficient attention to this core aspect. This study examines the impact of environmental credit evaluation on firm ESG performance using a staggered difference‐in‐differences model based on China's environmental credit rating policy. By analyzing data from 2010 to 2020 on 1018 publicly listed firms in high‐pollution industries in China, this study finds that the implementation of the environmental credit rating policy significantly improves ESG performance. This positive impact is realized through enhancing environmental information transparency, strengthening external supervision, and alleviating financing constraints.

Environmental, Social, and Governance (ESG) Outcomes and Municipal Credit Risk

We investigate the association between a wide range of community-level environmental, social, and governance (ESG) outcomes and the credit risk of U.S. municipal finance fixed-income securities. We develop a novel dataset of multiple ESG outcomes for U.S. counties and connect it to a 2001-2020 panel of municipal bonds issued within those counties. Overall, we find supportive evidence that collective increases in community-level ESG factors (i.e., ESG outcomes) are associated with reductions in credit risk for U.S. municipal finance instruments over time. We theorize that these associations arise from variations in investor perceptions and manifested changes in fiscal health over time as a function of changing ESG outcomes. Post hoc analyses leveraging quasi-exogenous shocks to uncertainty, as well as connecting ESG outcomes to various measures of fiscal health at the county-year level, and credit ratings at the bond-year level, help validate this theory. Our research suggests that even socially agnostic investors should investigate the environmental and social performance of a municipality as part of their credit due diligence.

Are credit rating agencies users of government accounting information? Evidence from the sovereign rating process

IMPACT Sovereign governments are regularly evaluated by credit rating agencies (CRAs) that perform an analysis of creditworthiness based on mostly public data. This article shows that the data used by CRAs is mainly drawn from economic and statistical accounts rather than government financial statements. Thus, CRAs cannot be considered users of financial accounting information, at least at the sovereign government level. The evidence also suggests that governmental accounting information is neglected because it lacks the fundamental quality of comparability that CRAs require, given that ratings are ordinal measure of creditworthiness. Unless governments begin producing harmonized financial statements, it is unlikely that CRAs will ever become users of accounting information. Meanwhile, CRAs ground their sovereign rating process on harmonized economic and statistical accounts that are lacking important information on government payables, receivables, contingent liabilities and assets.

Financial Technology and Digital Transformation of Enterprises—A Perspective of Financing Constraints and Credit Rationing

With the rapid development of the Digital economy, the Digital transformation of enterprises has become a new trend, and the effective promotion of the Digitalization of the enterprise is the key to the high-quality development of China’s economy. Through web crawler crawling data of Shanghai and Shenzhen A-share listed companies from 2011 to 2019 to investigate the role of regional FinTech in Digital transformation of enterprises, using text mining methods. The empirical results show that FinTech has a significant positive effect on Digital transformation of enterprises. After robustness tests such as reducing endogenous problems and replacing samples, the conclusions are still robust; Fintech reduces the information asymmetry between financial institutions and enterprises, alleviates the financing constraints of enterprises, and improves the efficiency of credit allocation by accelerating credit approval, thus promoting the Digital transformation of enterprises; In small and medium-sized private enterprises, FinTech has a more obvious effect on promoting enterprises’ Digital transformation; In the more economically backward Middle West, FinTech can also play its role.

So Right It’s Wrong? Right Governments, Far Right Populism, and Investment Risk

Political economy literature documents how financial investors are more partial to right executives than left ones. Right cabinets face lower interest rates, less volatile stock prices and exchange rates, and higher credit ratings than left cabinets, even after accounting for fiscal differences. But does this advantage persist if right governments accommodate far right parties or ideas? I hypothesize that because far right populism can introduce political instability, markets’ evaluation of right executives might deteriorate if they enter coalition with far right parties or adopt their positions. Employing a panel analysis of bond spread data, and a comparative case study of the Netherlands and Sweden, I find that right executives enjoy significantly lower spreads than their left-wing counter-parts, but this advantage disappears if they rule in coalition with the far right or produce overly right-wing manifestos. These findings highlight that right parties may encounter tangible borrowing costs and market rebuke if they accommodate far right populism.

The transmission of targeted monetary policy to bank credit supply

In this paper I estimate the impact of Targeted Longer-Term Refinancing Operations (TLTRO) on the evolution of lending amounts and rates in Slovenia, with a specific focus on distinct effects of TLTRO-I and II. I use a combination of difference-in-differences and instrumental variable approach, which together with detail credit register data enable the identification of supply side effects of the TLTRO policy. The results show a supporting impact of targeted operations on bank loan supply, resulting in higher credit growth and lower rates. I find that the TLTRO-I was supportive through both the quantity and price channels, whereas the TLTRO-II only shows a significant impact on the credit amount. Further, I find the transmission of TLTRO-I was higher through better capitalized banks, whereas both policy waves supported lending to safe and stable firms with higher credit ratings.

Do Credit Rating Agencies Learn from the Options Market?

Do credit rating agencies (CRAs) learn from the options market? We examine this question by exploring the relation between options trading activity and credit rating accuracy. We find that as options trading volume increases, credit ratings become more responsive to expected credit risk and exhibit greater ability to predict future defaults. We also find that CRAs rely more on the options market as a source of ratings-related information when firm default risk is higher, options trading is more informative, manager-provided information is of lower quality, and firm uncertainty is higher. Our results are robust to a number of sensitivity tests, including alternative measures of options trading and credit rating accuracy. We reach similar inferences using various approaches to address endogeneity issues, including difference-in-difference analyses and an instrumental variables approach. Overall, our findings are consistent with the view that CRAs incorporate unique information from the options market into their rating decisions which, in turn, improves credit rating accuracy. This paper was accepted by Brian Bushee, accounting. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.4980 .

Introducing the overall risk scoring as an early warning system

Business performance is a critical field of study, which should be assessed in more than just credit risk in the banking context. However, much previous research takes business performance in the context of credit risk in banking. In this study, risks will be analyzed to measure business performance in an integrated manner within the framework of non-financial sector dynamics. To this end, brainstorming sessions, risk workshops, surveys, and face-to-face interviews were held with representatives of small medium enterprises in 11 different sectors. Through field studies, risks have been identified and assessed in terms of impact and probability, Key Risk Indicators have been determined, and risks have been scored based on financial and non-financial metrics to estimate the Overall Risk Scoring. Moreover, the Overall Risk Scoring model has been tested using Logit Regression and Artificial Neural Networks (ANN), the Naïve Bayes Algorithm, and the C4.5 decision tree model. All methods have statistically verified that the predictive power of the structure of the Overall Risk Scoring is high. Our findings reveal that when business performance is analyzed with non-financial and financial metrics, dynamic and static data, market expectations, and banking needs, the predictive power of the calculated Overall Risk Scoring increases. The created Overall Risk Scoring Model can be used as an early warning system for many objectives by business executives, suppliers, consumers, investors, financial institutions, public bodies, credit rating agencies, and entities like the Credit Guarantee Fund.

Information content of credit rating affirmations

AbstractWe examine the economic determinants and informational effects of credit rating affirmations (i.e., the reiteration of past credit ratings) for a sample of US public firms from 1995 to 2020. We find that credit rating affirmations typically follow major corporate events and changes in firm fundamentals that increase information uncertainty about a firm's creditworthiness, suggesting that affirmations reduce uncertainty. We further document that rating affirmations provide value‐relevant information to equity and debt investors. Using a short‐window event study method, we show that equity investors react positively to rating affirmations and that information uncertainty around affirmations diminishes. These findings are more pronounced for firms with non‐investment‐grade ratings. We further show that our results strengthen for firms with greater pre‐affirmation information uncertainty. Finally, consistent with our information uncertainty reduction results from the stock market, we report that bond yield spreads decrease for affirmed firms. Again, the effect is more pronounced for firms with non‐investment‐grade ratings. In summary, we highlight the significant capital markets' effects of credit rating affirmations, an area that the literature has largely ignored.

Applications of blockchain technologies in artificial electricity market settlement and clearing

Abstract Blockchain technology is demonstrating vast potential in the realm of distributed energy transactions. This article employs the Ethereum platform to architect an energy trading settlement framework. By incorporating whitelists, authorization mechanisms, and dedicated energy tokens, transactions are rendered more secure and reliable, ensuring the openness, transparency, traceability, and immutability of transaction information. The proposed transaction settlement mechanism automatically updates users' energy imbalances and levies corresponding charges, thereby ensuring strict adherence to transaction contracts. Furthermore, during the settlement phase, smart contracts are employed to autonomously evaluate the creditworthiness of transaction parties, with results recorded on the blockchain. As the credit levels of the entities across the entire network increase, the block generation time for distributed energy trading blockchains becomes shorter, with the block generation time predominantly influenced by the credit rating of the highest-rated entity in the network. Hence, through smart contract design based on energy trading, blockchain technology is utilized to enhance the transparency and security of transaction settlement and clearing. Future research could focus on improving blockchain scalability, integrating emerging technologies, to advance the effectiveness and adoption of blockchain-based energy trading systems.

Corporate Credit Ratings Based on Hierarchical Heterogeneous Graph Neural Networks

Corporate Credit Ratings Based on Hierarchical Heterogeneous Graph Neural Networks

ROLE OF THE TOURISM SECTOR IN CARVING OUT A BETTER INDIA

By 2047, India will complete 100 years after its independence. By then, the people of India unitedly dream that India will become a developed country by all means. International rating agencies predicted that India will become the third biggest economy (GDP-wise) in the world by 2030. Although growth has slowed down due to COVID-19, data shows that most sectors are currently in revival and on a booming path. Tourism is one of the vital sectors that significantly contribute to the growth of India by providing jobs and revenue including accumulation of foreign exchange money. Kerala, popularly known as Gods own country, a southern state, with heavy potential in tourism, has a huge role to play in making the dream that India as a Viswa guru, a reality. This study aims to explore the current and future potential of the tourism sector in India and Kerala and to what extent it is capable of propelling the dreams of India to become a nation with an 8.5 trillion Dollar GDP by 2030. It is found that if we can timely resolve all the drawbacks with proper planning and execution, the Tourism sector in India can achieve its goal before the targeted time, which will help the dream of crores of poor and oppressed people to come true, that India will become a developed nation. It is suggested that intense research and development work and the adoption of the best possible technology along with the right marketing campaign help us to accelerate the pace of development and accomplish the target within the minimum possible time. KEYWORDS: Vision 2047, role of Indian Tourism, Kerala Tourism, Developed nation, Growth.

Unraveling ESG Ambiguity, Price Reaction, and Trading Volume

We introduce an asset pricing model that integrates investors’ ESG preferences and their ambiguous attitudes towards firms’ ESG performance, influenced by inconsistent ESG ratings from diverse rating agencies. Our model, considering unregulated ESG reporting and variations in agency assessments, reveals significant dynamics in asset pricing. We discover that stronger belief in high ESG scores among investors increases asset holdings and prices, whereas increased perceived ESG ambiguity negatively impacts these metrics. Crucially, the model demonstrates that the ESG ambiguity attitudes parameter and the degree of perceived ESG ambiguity are inversely related to asset prices. Specifically, we find that heightened perceived ESG ambiguity and a higher ESG ambiguity attitudes parameter are associated with lower asset prices, reflecting in increased trading volumes and widened price differentials. This research offers vital insights into how investors’ preferences and perceptions about ESG influence asset pricing.

Leverage, earnings management and audit industry specialization: the case of Palestinian-listed companies

PurposeThis study explores the relationship between leverage and earnings management in the context of Palestinian-listed companies, while also investigating whether audit industry specialization influences this relationship.Design/methodology/approachThe data used in this study are extracted from public financial reports of 39 firms listed on Palestine Stock Exchange (PEX), spread across the service, insurance, industry and investment sectors, for the time period 2011–2022. A model is developed to test 4 hypotheses about the relationships between long-term and short-term debts, and earnings management, and then to examine the influence of audit industry specialization on these relationships.FindingsThe results depict a significant, negative relationship between long-term debt and earnings management. Whereas the association between short-term debt and earnings management is insignificant. Audit industry specialization is proven to have no influence on the relationships between the independent and the dependent variables. Results are robust for firms that changed their accounting policies and using different audit industry specialization proxies.Originality/valueThe association between leverage and earnings management is a significant research topic, given that previous research identifies credit ratings and debt covenant violations as key factors which motivate earnings management. This paper fills a substantial research gap by examining the relationship between the two variables in the context of Palestinian-listed firms, while emphasizing the distinction between long-term and short-term debts. It also highlights key relationships that have been neglected in this particular context, which adds to the body of literature. Furthermore, the research's findings provide a solid information base that is of great interest to accounting and auditing experts and that may be seriously evaluated to support and advance the PEX sector.

Information processing costs and credit ratings: evidence from investor interactive platforms in China

We examine the impact on bond credit ratings of reduced information processing costs from two investor interactive platforms in China, i.e. ‘Easy Interaction’ and ‘e-Interaction’. These online platforms provide investors with a channel to directly communicate with listed companies and learn much of corporate operations. Replies and explanations from management assist investors in integrating disclosed information and reducing information processing costs. The reduced costs likely impose reputational concerns on credit rating agencies (CRAs), leading to more stringent rating standards and less rating inflation. We find that more interactions result in lower credit ratings of corporate bonds. This effect is more pronounced for bonds rated by global-partnered CRAs and bonds whose issuers have higher information complexity, and less pronounced for bonds whose issuers have official consultation websites. Further analyses show that reduced information processing costs are associated with more information contents in rating downgrades and timelier ratings. Our findings provide evidence for the disciplinary effect of reduced processing costs on CRA behavior.

Exploring the Subprime Crisis

This paper delves into an examination of the three primary interrelated factors that precipitated the subprime mortgage crisis: regulatory deficiencies, policy failures, and dysfunctional innovation. Furthermore, it conducts an analysis of the underlying factors that exacerbated the ramifications of this economic upheaval: the excessive proliferation of securitization, a deficiency in market transparency, inadequate risk management practices within financial institutions, and challenges associated with credit rating agencies. The subprime mortgage crisis has incited extensive discourse across diverse sectors, notably encompassing two pivotal dimensions: firstly, inquiries surrounding the transparency of assets and, secondly, predicaments pertaining to governmental intervention for market stabilization. This article undertakes a comprehensive categorization and in-depth exposition of these discrete issues, proffering meticulous explications corroborated by empirical substantiation. Culminating in its denouement, the article proffers prudent recommendations aimed at preemptively mitigating the advent of future crises. The entire discourse endeavors to maintain an objective and truthful perspective, aiming to explore the fundamental nature of the subprime mortgage crisis rigorously.

CHARACTERIZATION OF THE CHROMIC LUVISOLS PROFILE FROM SC AGROTEHNIC SRL, PAULESTI, PRAHOVA

The credit rating aims to establish the favorability classes of land for different agricultural crops.In this context, the present study aims to quantify the favorability of the Chromic Luvisols from S.C. Agrotehnic Paulesti for arable use. Also, this study has as a main objective a morphological characterization and profile description of Chromic Luvisols.Following the study, it can be concluded that it is presents the same limiting factors as for arable suitability related to the loamy-clay texture, which implies a short interval of soil works and the appearance of the hardpan sub-horizon.

Credit rating agencies during credit crunch

AbstractIn this paper, we study whether credit rating agencies (CRAs), as they claim, follow the rating through‐the‐cycle approach as opposed to a pro‐cyclical approach. In particular, we compare the behavior of CRAs during the credit crunch and normal market conditions. Using the credit rating data by S&P, we find that CRAs assign lower credit ratings to firms during credit crunch relative to normal times. Nevertheless, this result does not necessarily imply that CRAs show an excessively pro‐cyclical behavior if credit crunches have a long‐term fundamental impact on firms. Our further investigation reveals that downgrades during a credit crunch will not be reversed over the subsequent 1–5 years, which supports through‐the‐cycle credit rating.

Bank Credit and Loan Repayment Rates during COVID-19 in Kabale District, Uganda

The study was to investigate the impact of bank credit on loan repayment rates in the Kabale region using Lyamujungu SACCO as the case study. Loan repayment performance at Lyamujungu SACCO has rapidly declined. This study used a cross-sectional survey method to examine, characterize and compare bank credit and loan repayment in Kabale district, using Lyamujungu SACCO as the case study. The sample size for each subject type was determined using the table of Krejcie and Morgan. Out of 150 samples, a sample of 108 people was selected for the study. The researcher used both purported sampling and simple random sampling to select members/clients of SACCO. Based on the results in the table, the null hypothesis for all three variables is rejected, with a significance level of (p = <.000, p = <.040, and p = <.001). This means that there is evidence that the distribution of mean scores for each of the three variables is not the same depending on the borrower's ability to repay. The study concluded that labor productivity growth decreased and therefore, income decreased, investment decreased and affected the borrower's ability to repay loans during the COVID-19 pandemic in Lyamujungu SACCO.