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The importance of obtaining a sovereign credit rating from an agency is still underrated in Africa. Literature on the determinants of sovereign credit ratings in Africa is scarce. The purpose of this research is to determine what the determinants are for sovereign credit ratings in Africa and whether these determinants differ between regions and income groups.

A sample of 19 African countries' determinants of sovereign credit ratings are compared between 2007 and 2014 using a panel-ordered probit approach.

The findings indicated that the determinants of sovereign credit ratings differ between African regions and income groups. The developmental indicators were the most significant determinants across all income groups and regions. The results affirm that the identified determinants in the literature are not as applicable to African sovereigns, and that developmental variables and different income groups and regions are important determinants to consider for sovereign credit ratings in Africa.

The results affirm that the identified determinants in the literature are not as applicable to African sovereigns, and that developmental variables and different income groups and regions are important determinants to consider for sovereign credit ratings in Africa. Rating agencies follow the same rating assignment process for developed and developing countries, which means investors will have to supplement the allocated credit rating with additional information. Africa can attract more investment if African countries obtain formal, accurate sovereign credit ratings, which take the characteristics of the continent into consideration.

This study attempts to identify fundamental determinants of bond ratings for non-financial and financial firms. Further the study aims to develop a parsimonious bond rating model and compare its efficacy across statistical and range of machine learning methods in the Indian context. The study is motivated by the insufficiency of prior work in the Indian context.

The authors identify the critical determinants of non-financial and financial firms using multinomial logistic regression. Various machine learning and statistical methods are employed to identify the optimal bond rating prediction model. The data cover 8,346 bond issues from 2009 to 2019.

The authors find that industry concentration, sales, operating leverage, operating efficiency, profitability, solvency, strategic ownership, age, firm size and firm value play an important role in rating non-financial firms. Operating efficiency, profitability, strategic ownership and size are also relevant for financial firms besides additional determinants related to the capital adequacy, asset quality, management efficiency, earnings quality and liquidity (CAMEL) approach. The authors find that random forest outperforms logit and other machine learning methods with an accuracy rate of 92 and 91% for non-financial and financial firms.

The study identifies important determinants of bond ratings for both non-financial and financial firms. The study interalia finds that the random forest technique is the most appropriate method for bond ratings predictions in India.

Better bond ratings may mitigate corporate defaults.

Unlike prior literature, the study identifies determinants of bond ratings for both non-financial and financial firms. The study also experiments with modern machine learning techniques besides the traditional statistical approach for model building in case of relatively under researched market.

This study aims to identify the determinants of Malaysian corporate Sukuk rating and attempts to find out which determinant has the most significant impact.

The framework tries to establish a relationship between firm’s size, profitability, Sukuk guarantee status and types of Sukuk with Sukuk rating from the perspective of Agency Theory and Information Asymmetry Theory. The data consist of 43 Sukuk issuances from 2006 to 2015. Multinomial Logistic Regression Model is then used to find out the significant determinants of Sukuk rating.

The study found that only three variables significantly impact Sukuk rating. The results show that a guaranteed Sukuk Ijarah or a guaranteed Sukuk Musyarakah that is issued by a highly profitable firm has a higher likelihood of getting rating AAA or rating AA as compared to getting rating A. A type of Sukuk, particularly Sukuk Murabahah, is the most significant variable influencing Sukuk rating. However, firm size is not a significant determinant of Sukuk rating in the context of this study.

The first limitation of the study is the relatively small sample size. Second, the study only tested four independent variables.

Several implications are derived from the results of the study. First, new firms that are planning to issue Sukuk should consistently maintain a high level of profit and consider issuing debt-based Sukuk to ensure that the issued Sukuk have higher rating. To increase the likelihood of getting higher rating, they should also consider providing a third-party guarantor. As for existing Sukuk issuers that are in lower rating category, they should increase their profitability to be upgraded to higher rating category. Second, risk-adverse investors should invest in highly profitable, guaranteed and debt-based Sukuk, as these Sukuk are likely to be in higher rating category and provide guarantee in terms of capital payments during liquidation or bankruptcy. Third, to reduce information asymmetry, policymakers should make it compulsory for all Sukuk issuers to have their Sukuk rated annually and make it mandatory for all rating agencies in Malaysia to publish their Sukuk rating methodologies.

This paper helps to expand the limited existing literature about the determinants of Sukuk rating, particularly for the Malaysian corporate Sukuk.

Since sovereign ratings provided by credit rating agencies (CRAs) are a key determinant of the interest rates a country faces in the international financial market and once sovereign ratings may have a constraining impact on the ratings assigned to domestic banks or companies, some studies have focused on identifying the determinants of sovereign credit risk assessments provided by CRAs. In particular, this study estimates the effect of fiscal credibility on sovereign risk using four different comprehensive credit rating (CCR) measures obtained from CRAs' announcements and two different fiscal credibility indicators.

We build comprehensive credit rating (CCR) measures to capture sovereign risk. These measures are calculated using sovereign ratings, the rating outlooks and credit watches issued by the three main credit rating agencies (S&P, Moody's and Fitch) for long-term foreign-currency Brazilian bonds. Based on monthly data from 2003 to 2018, we use different econometric estimation techniques in order to provide robust results.

The results indicate that fiscal credibility exerts both short- and long-run effects on sovereign risk perception, and macroeconomic fundamentals are important long-run determinants.

Since fiscal credibility reflects the government's ability to maintain budgetary balance and sustainable public debt, the government should keep its commitment to responsible fiscal policies so as not to deteriorate expectations formed by financial market experts about the fiscal scenario and, thus, to achieve better credit assessments issued by CRAs with respect to sovereign debt bonds. Sovereign credit rating assessment is a voluntary practice. It is up to the country whether they want to apply for a rating assessment or not. Thus, without a sovereign rating, one must find an alternative to measure the sovereign risk of a country. In this sense, an important practical implication that this study provides is that fiscal credibility can be used as a leading indicator of sovereign risk perceptions obtained from CRAs or even as a proxy for sovereign risk.

This paper is the first to verify how important the expectations of financial market experts in relation to the fiscal effort required to keep public debt at a sustainable level (i.e. fiscal credibility) are to sovereign risk perception of credit rating agencies. In this sense, the study is the first to address this relation, and thus it contributes to the literature that seeks to understand the determinants of sovereign ratings in emerging countries.

This paper aims to study the determinants of the sovereign debt ratings provided by the 3 main rating agencies for 32 European countries. It verifies the clusters of countries existing for each of the agencies, considering regional bias, and then analyzes whether the determinants were different before and after the global financial crisis. It also aims to explain how the determinants are taken into account for rich and developing countries, using a sample for the period between 2001 and 2008 and the period between 2009 and 2016.

To this purpose, this paper performs panel data estimation using an ordered Probit approach.

This method shows that for developing countries after the crisis, the relevant explanatory variables are the unemployment rate and the presence in the Eurozone. For rich countries, the inflation rate is pivotal after the crisis period.

This paper is the first to use a clustering methodology within sovereign debt rating literature, grouping the countries into cohesive clusters according to their sovereign debt ratings along with the proposed time frame. Moreover, it explains, which countries belong to strong or weak groups, according to the rating agencies under discussion; and, in these groups, it identifies the sovereign rating determinants.

This study aims to examine the determinants of Sukuk credit ratings of issuing firms in Malaysia, and the rating changes from lower to higher rating and vice versa.

A total of 328 Sukuk issuances and 1,110 Sukuk rating announcements from 2009 to 2014 were analysed using generalized ordered logit regressions approach. Firm financial characteristics, corporate governance attributes, macroeconomic factors and Sukuk structures (debt or equity based) were among the important determinants used to explain the different Sukuk credit ratings.

The results indicate a positive association of Sukuk credit rating with issuing firm’s financial information, governance attributes and the Sukuk structure whilst the macroeconomic factors did not explain the changes in the Sukuk credit rating. Specifically, firm size, profitability and leverage characteristics had significant positive effect on Sukuk credit rating for listed firms whilst only firm’s profitability had a positive effect on Sukuk credit rating by unlisted firms. With regard to governance, the board structure which includes board size, board independence and CEO/Chairman non-duality is associated with positive Sukuk credit rating for listed firms. Only financial report audited by big four auditors is associated with positive Sukuk credit rating for unlisted firms. Equity-based Sukuk are associated with positive Sukuk credit rating for listed firms while for unlisted firms only the Ijarah Sukuk had a positive Sukuk credit rating.

Data on credit rating is scarce and had to be hand-collected from published reports. Furthermore, issues on the lack of standardisation of Islamic contracts in different geographical areas could constrain on the comparability of findings on determinants of ratings in different jurisdictions.

The findings provide some guide to the rating agencies to objectively assess the issuer’s creditworthiness that could mitigate default risk. Mitigating the default risk will boost investors’ confidence and credibility of credit rating agencies.

This study examines the determinants of Sukuk credit rating of issuing firms in Malaysia, which include not only the listed firms but also the unlisted firms.

This 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.

The analysis applies the fixed effects (FE) and random effects (RE) panel least squares (PLS) models.

The 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.

These 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.

First, 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.

This study aims to identify the key determinants of Airbnb rating scores.

This study is based on a sample of 127,257 listings across 43 cities. A total of 24 explanatory variables were identified, and they were further grouped into host verification information, communication, policy of renting, space, information about environment, price and experience of hosting. Both Tobit and ordered logit models were used to perform the analysis.

The results indicate that good communication, large space and provision of information about the listings’ environment have a positive effect on users’ satisfaction, whereas experience of hosting negatively influences users’ satisfaction.

This study contributes to the peer-to-peer accommodation literature by affording a more complete understanding about guest satisfaction and its determinants.

This study aims to analyze the determinants of ratings of corporate bonds and sukuk issued by firms listed on the Indonesia Stock Exchange (IDX) for the 2013–2019 period.

This study uses a quantitative approach by testing hypotheses and using logistic regression. Ordinal logistic endogenous (or dependent) variables (Y) in ordinal logistics use data in the form of levels (ordinal scale). Independent (or exogenous) variables (X), include financial and non-financial factors for dependent (or endogenous) variables (Y), namely, of corporate bonds and sukuk ratings. There are two approaches to the study they are Logit and Gompit (Negative Log-Log. The population of the study is Indonesian companies listed on the IDX that issued bonds and sukuk for the 2013–2019 periods. The sampling technique is purposive. In total, 16 corporate companies adhering to the above criteria and issuing bonds and sukuk were chosen. In total, 270 types of bonds and 280 types of sukuk were selected as samples.

The results of the Logit and Gompit regression show that leverage ratio, firm size, security structure and maturity date are important determinants of corporate bond ratings while profitability and liquidity ratios appear to have no influence on the rating. In the case of sukuk, profitability, liquidity and maturity date play important roles in influencing the corporate sukuk rating. However, there is no evidence to suggest that leverage ratio, company size and security structure may affect sukuk ratings.

For both sukuk and bond issuers, it is necessary to pay attention to the factors that may affect the ratings. Specifically, Sukuk issuers need to pay attention to the return of asset, current ratio, growth and structure. On the other hand, bond issuers need to consider depth to equity, structure and maturity. As for investors, the findings of this study reveal that both bond and sukuk ratings reflect their performance.

This study provides useful information for investors that allows them to assess the risk of sukuk or bonds chosen based on rating and financial performance.

The novelty of this study lies in its econometric methodology used to identify factors which influence sukuk and bond ratings. Specifically, this study used two different techniques that allow a robust conclusion to be drawn. Furthermore, this study provides a systematic analysis which allows comparison between factors which affect bond and sukuk ratings in Indonesia.

Explains the rating system for US municipal bonds and its effect on borrowing costs, reviews relevant research and provides a study of the factors affecting grading by rating agencies in Virginia using 1995 data. Explains the methodology and presents the results, which identify five significant determinants of favourable ratings. Shows that net interest costs are lower when other rates of interest are low, real estate taxes are high (though not excessive), total municipal debt levels are low and credit risks are low. Confirms that bond ratings capture additional information and that a drop in ratings will raise net interest costs substantially. Considers consistency with other research and the implications of the findings for participants in the municipal bond market.