scholarly journals Determinants of Credit Ratings of Russia’s Regions

REGIONOLOGY ◽  
2021 ◽  
Vol 29 (2) ◽  
pp. 355-379
Author(s):  
Anna A. Mikhaylova ◽  
Evgeny N. Timushev
Keyword(s):  
Life Expectancy ◽  
Credit Rating ◽  
Negative Impact ◽  
Positive Impact ◽  
Credit Ratings ◽  
Explanatory Power ◽  
Rating Agencies ◽  
Regional Budget ◽  
Budget Policy ◽  
Policy Measures

Introduction. A credit rating reflects the degree of debt sustainability of the region, but the issue of its factors at the regional level has been under-researched. The article is based on the conducted study and reveals the major factors that influenced the assignment of credit ratings by Russian and international rating agencies to the regions of Russia. Materials and Methods. The methodology of both Russian (ACRA and Expert RA) and foreign (Fitch Ratings, S&P Global Ratings, and Moody's Investors Service) rating agencies were analyzed. Factor and correlation analysis was used to group the factors; their quantitative indicators were selected. Ordinal and multinomial logistic regressions (logits) were used to test the explanatory power of the factors. Results. The negative impact on the rating of the factors of debt, deficit, and the size of the public sector, as well as the positive impact of the size and dynamics of the region’s economy has been corroborated. The negative impact of poverty, as well as the positive impact of life expectancy and the size of capital budget expenditures has been highlighted. Differences in using the indicator of the region’s dependence on subsidies have been revealed: it has been regarded as an insignificant factor by international agencies, but as a negative one by Russian agencies. Discussion and Conclusion. The authors have established that Russian agencies give priority to quantitative budget indicators, while international ones give priority to traditional economic indicators. The identified significance of the indicators of life expectancy and poverty has become a particularly valuable result as it indicates a direct dependence of the credit rating on the quality of life in the region. The results obtained make it possible to formulate regional budget policy measures aimed at reducing credit risk, expanding debt financing, and increasing the effectiveness of budget policy. The results of the study will be useful not only in the practice of public administration, but also in further scientific research, as they open the way to the analysis of the interdependence between the credit rating and countercyclical fiscal policy measures, as well as to clarify the role of other factors in creditworthiness, especially those of an institutional nature.

scholarly journals ESG as a Measure of Credit Ratings

Risks ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 226
Author(s):  
Patrycja Chodnicka-Jaworska
Keyword(s):  
Financial Institutions ◽  
Credit Rating ◽  
Negative Impact ◽  
Credit Ratings ◽  
Stock Exchanges ◽  
Credit Rating Agencies ◽  
Rating Agencies ◽  
Thomson Reuters ◽  
Rating Changes ◽  
The Impact

The aim of this study was to examine the impact of environmental, social, and governance (ESG) measures on credit ratings given to non-financial institutions by the largest credit rating agencies according to economic sector divisions. The hypotheses were as follows: a strong negative impact on non-financial institutions’ credit rating changes will result from ESG risk changes, and the reaction of credit rating changes will vary in different sectors. Panel event models were used to verify these hypotheses. The study used data from the Thomson Reuters Database for the period 2010–2020. The analysis was based on the literature on credit rating determinants and on papers and reports on COVID-19, ESG factors, and their impact on credit rating changes. Linear decomposition was used for the analysis. To verify these hypotheses, long-term issuer credit ratings presented by Moody’s and Fitch for European companies listed on these stock exchanges have been used. In the analyses, financial and non-financial factors were also considered. The results suggested that, within the last year, the methodology presented by credit rating agencies has changed, and ESG factors are one of the basic measures that are used to verify credit rating changes, especially those related to the pandemic.

Uncertain Meanings of Risk

2018 ◽  
Author(s):  
Natalia Besedovsky
Keyword(s):  
Financial Markets ◽  
Credit Rating ◽  
Traditional Approach ◽  
Credit Ratings ◽  
Assessment Practices ◽  
Structured Finance ◽  
Rating Agencies ◽  
Measures Of Risk ◽  
Methodological Approaches ◽  
Ontological Uncertainty

This chapter studies calculative risk-assessment practices in credit rating agencies. It identifies two fundamentally different methodological approaches for producing ratings, which in turn shape the respective conceptions of credit risk. The traditional approach sees ‘risk’ as an only partially calculable and predictable set of hazards that should be avoided or minimized. This approach is particularly evident in the production of country credit ratings and gives rise to ordinal rankings of risk. By contrast, structured finance rating practices conceive of ‘risk’ as both fully calculable and controllable; they construct cardinal measures of risk by assuming that ontological uncertainty does not exist and that models can capture all possible events in a probabilistic manner. This assumption—that uncertainty can be turned into measurable risk—is a necessary precondition for structured finance securities and has become an influential imaginary in financial markets.

scholarly journals Three Letters that Move the Markets: Credit Ratings between Market Information and Legal Regulation

2017 ◽  
Author(s):  
Ulrich G. Schroeter
Keyword(s):  
Financial Markets ◽  
Applied Research ◽  
Credit Rating ◽  
Credit Ratings ◽  
Legal Regulation ◽  
Legal Regulations ◽  
Market Information ◽  
Market Reactions ◽  
Rating Agencies ◽  
Sovereign Credit Ratings

Journal of Applied Research in Accounting and Finance, Vol. 6, No. 1 (2011), pp. 14-30As demonstrated by the market reactions to downgrades of various sovereign credit ratings in 2011, the credit rating agencies occupy an important role in today’s globalized financial markets. This article provides an overview of the central characteristics of credit ratings and discusses risks arising from both their widespread use as market information and from the increasing references to credit ratings contained in laws, legal regulations and private contracts.

A comparative study of economic growth as a key determinant of sovereign credit ratings in Africa

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Misheck Mutize ◽  
McBride Peter Nkhalamba
Keyword(s):  
Economic Growth ◽  
Credit Rating ◽  
Credit Ratings ◽  
Credit Rating Agencies ◽  
African Union ◽  
African Countries ◽  
Content Type ◽  
Rating Agencies ◽  
Sovereign Credit ◽  
Sovereign Credit Ratings

PurposeThis study is a comparative analysis of the magnitude of economic growth as a key determinant of long-term foreign currency sovereign credit ratings in 30 countries in Africa, Europe, Asia and Latin America from 2010 to 2018.Design/methodology/approachThe analysis applies the fixed effects (FE) and random effects (RE) panel least squares (PLS) models.FindingsThe authors find that the magnitude economic coefficients are marginally small for African countries compared to other developing countries in Asia, Europe and Latin America. Results of the probit and logit binary estimation models show positive coefficients for economic growth sub-factors for non-African countries (developing and developed) compared to negative coefficients for African countries.Practical implicationsThese findings mean that, an increase in economic growth in Africa does not significantly increase the likelihood that sovereign credit ratings will be upgraded. This implies that there is lack of uniformity in the application of the economic growth determinant despite the claims of a consistent framework by rating agencies. Thus, macroeconomic factors are relatively less important in determining country's risk profile in Africa than in other developing and developed countries.Originality/valueFirst, studies that investigate the accuracy of sovereign credit rating indicators and risk factors in Africa are rare. This study is a key literature at the time when the majority of African countries are exploring the window of sovereign bonds as an alternative funding model to the traditional concessionary borrowings from multilateral institutions. On the other hand, the persistent poor rating is driving the cost of sovereign bonds to unreasonably high levels, invariably threatening their hopes of diversifying funding options. Second, there is criticism that the rating assessments of the credit rating agencies are biased in favour of developed countries and there is a gap in literature on studies that explore the whether the credit rating agencies are biased against African countries. This paper thus explores the rationale behind the African Union Decision Assembly/AU/Dec.631 (XXVIII) adopted by the 28th Ordinary Session of the African Union held in Addis Ababa, Ethiopia in January 2017 (African Union, 2017), directing its specialized governance agency, the African Peer Review Mechanism (APRM), to provide support to its Member States in the field of international credit rating agencies. The Assembly of African Heads of State and Government highlight that African countries are facing the challenges of credit downgrades despite an average positive economic growth. Lastly, the paper makes contribution to the argument that the majority of African countries are unfairly rated by international credit rating agencies, raising a discussion of the possibility of establishing a Pan-African credit rating institution.

scholarly journals Forecasting Credit Ratings of EU Banks

2020 ◽  
Vol 8 (3) ◽  
pp. 49
Author(s):  
Vasilios Plakandaras ◽  
Periklis Gogas ◽  
Theophilos Papadimitriou ◽  
Efterpi Doumpa ◽  
Maria Stefanidou
Keyword(s):  
Credit Rating ◽  
Credit Ratings ◽  
Support Vector ◽  
Credit Rating Agencies ◽  
Selection Scheme ◽  
Explanatory Variables ◽  
Rating Agencies ◽  
Financial Variables ◽  
Forecasting Models ◽  
Banking Institutions

The aim of this study is to forecast credit ratings of E.U. banking institutions, as dictated by Credit Rating Agencies (CRAs). To do so, we developed alternative forecasting models that determine the non-disclosed criteria used in rating. We compiled a sample of 112 E.U. banking institutions, including their Fitch assigned ratings for 2017 and the publicly available information from their corresponding financial statements spanning the period 2013 to 2016, that lead to the corresponding ratings. Our assessment is based on identifying the financial variables that are relevant to forecasting the ratings and the rating methodology used. In the empirical section, we employed a vigorous variable selection scheme prior to training both Probit and Support Vector Machines (SVM) models, given that the latter originates from the area of machine learning and is gaining popularity among economists and CRAs. Our results show that the most accurate, in terms of in-sample forecasting, is an SVM model coupled with the nonlinear RBF kernel that identifies correctly 91.07% of the banks’ ratings, using only 8 explanatory variables. Our findings suggest that a forecasting model based solely on publicly available financial information can adhere closely to the official ratings produced by Fitch. This provides evidence that the actual assessment procedures of the Credit Rating Agencies can be fairly accurately proxied by forecasting models based on freely available data and information on undisclosed information is of lower importance.

scholarly journals ESG Scores and the Credit Market

2020 ◽  
Vol 12 (8) ◽  
pp. 3456 ◽  
Author(s):  
Ga-Young Jang ◽  
Hyoung-Goo Kang ◽  
Ju-Yeong Lee ◽  
Kyounghun Bae
Keyword(s):  
Small Firms ◽  
Credit Rating ◽  
Credit Ratings ◽  
Debt Financing ◽  
Corporate Bond ◽  
Cost Of Debt ◽  
Rating Agencies ◽  
Bond Returns ◽  
The Cost ◽  
The Relationship

This study analyzes the relationship between Environmental, Social and Governance (ESG) scores and bond returns using the corporate bond data in Korea during the period of 2010 to 2015. We find that ESG scores include valuable information about the downside risk of firms. This effect is particularly salient for the firms with high information asymmetry such as small firms. Interestingly, of the three ESG criteria, only environmental scores show a significant impact on bond returns when interacted with the firm size, suggesting that high environmental scores lower the cost of debt financing for small firms. Finally, ESG is complementary to credit ratings in assessing credit quality as credit ratings cannot explain away ESG effects in predicting future bond returns. This result suggests that credit rating agencies should either integrate ESG scores into their current rating process or produce separate ESG scores which bond investors integrate with the existing credit ratings by themselves.

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