Search results

This study aims to provide further insights into the connection between corporate social responsibility (CSR) and companies’ credit ratings, while also exploring the role of corporate governance as a moderating factor. The hypotheses for this relationship are rooted in both legitimacy and stakeholder theories.

Using a sample of French non-financial listed firms from 2007 to 2020, this paper uses the ordered probit model introduced by Greene (2000). The issue of endogeneity has also been addressed.

The study reveals that CSR practices positively impact companies’ credit ratings by enhancing solvency and financial performance. Specifically, firms that prioritize CSR, particularly in the social and environmental dimensions (such as community relations, diversity, employee relations, environmental performance and product characteristics), tend to have higher credit ratings and a reduced risk of default. This suggests that credit rating agencies likely incorporate CSR performance when assigning credit ratings. Furthermore, the quality of corporate governance acts as a moderator, strengthening the relationship between CSR and credit ratings. The findings remain robust even after accounting for key firm attributes and addressing potential endogeneity between CSR and credit ratings.

This research provides valuable guidance for policymakers, corporate managers, investors and other stakeholders, as it offers insights into the influence of CSR activities on risk premiums and financing costs. For financial institutions, expanding credit decisions to encompass non-financial factors such as CSR can result in more accurate predictions of firm credit quality compared to relying solely on financial indicators.

To the best of the authors’ knowledge, this study stands out as the first to systematically examine the relationship between CSR and credit ratings within the French context. Moreover, it distinguishes itself by investigating the moderating influence of corporate governance on this relationship, setting it apart from prior research.

The authors examine the role of CEO political ideology in the credit rating process.

This study adopts a quantitative method with panel data regressions using a sample of 5,211 observations from S&P 500 firms from 2001 to 2012.

The authors find that firms run by Republican-leaning CEOs, who tend to have conservative political ideologies, enjoy more favorable credit ratings than firms run by Democratic-leaning CEOs. In addition, the association between CEO political ideology and credit ratings is more pronounced for firms with high operating uncertainty, low capital intensity, high growth potential, weak corporate governance and low financial reporting quality. Finally, the authors find that CEO political ideology affects a firm's cost of debt incremental to credit ratings, consistent with debt investors incorporating CEO political ideology in their pricing decisions.

Leveraging CEO political ideology, the authors document that credit rating agencies incorporate managerial conservatism in their credit rating decisions. This finding suggests that CEO political ideology serves as a meaningful signal for managerial conservatism.

The study suggests that credit rating agencies incorporate CEO political ideology in their credit rating process. Other capital market participants such as auditors and retail investors can also use CEO political ideology as a proxy for managerial conservatism when evaluating firms.

The paper carries practical implications for practitioners, firm executives and regulators. The results on the association between CEO political ideology and credit ratings suggest that other financial institutions could also incorporate CEO political ideology in their evaluation in their evaluation of firms. For example, when evaluating audit risk and determining audit pricing, auditors may add CEO political ideology as a risk factor. For firms, especially those that have Democratic-leaning CEOs, the authors suggest that they could reduce the unfavorable effect of CEO political ideology on credit ratings by improving their corporate governance and financial reporting quality, as demonstrated in the cross-sectional analyses. Finally, this study shows that CEO political ideology, as measured by CEOs' political contributions, is closely related to a firm's credit ratings. This finding may inform regulators that greater transparency for CEOs' political contributions is needed as information on contributions could help capital market participants perform risk analyses for firms.

Credit rating agencies release their research methodologies for determining corporate credit ratings and identify managerial conservatism as an important factor that affects their risk assessments. The extant literature, however, has not empirically investigated the relation between credit ratings and managerial conservatism, which, according to behavioral consistency theory, can be proxied by CEO political ideology. This study provides novel empirical evidence that identifies CEO political ideology as an important input factor in the credit rating process.

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 seeks to identify the main determinants of the optimal capital structure by reexamining the interpretation of the conventional set of explanatory variables used as proxies for the costs and benefits of debt in the context of the dynamic tradeoff theory.

The authors isolate the variation in leverage due to different targets from that caused by deviations by aggregating the data across a dimension identifying firms with similar targets – credit rating category.

Contrary to theoretical priors, large and profitable rated firms have lower targets. The authors show that size and profitability proxy for non-financial risk and that, for rated firms, non-financial risk is positively correlated to the optimal leverage. The benefits of a better rating outweigh the costs of foregone tax shields for firms with relatively low non-financial risk. The authors find support for that theory in institutional trading – institutional investors do not punish highly rated firms when credit downgrades occur.

This paper contributes to the capital structure literature by developing a new approach based on data aggregation. This study is the first, to the authors’ knowledge, to find a positive effect of the firm's non-financial risk on target leverage among rated firms. The authors argue that the benefit of a better credit rating is an increasing function of the rating itself. The authors also contribute to the literature on the impact of credit ratings on the capital structure choices of the firm.

Bank creditworthiness refers to the evaluation of a bank’s ability to meet its financial obligations. It is an assessment of the bank’s financial health, stability and capacity to manage risks. This paper aims to investigate the credit rating patterns that are crucial for assessing creditworthiness of the Islamic banks, thereby evaluating the stability of their industry.

Three distinct machine learning algorithms are exploited and evaluated for the desired objective. This research initially uses the decision tree machine learning algorithm as a base learner conducting an in-depth comparison with the ensemble decision tree and Random Forest. Subsequently, the Apriori algorithm is deployed to uncover the most significant attributes impacting a bank’s credit rating. To appraise the previously elucidated models, a ten-fold cross-validation method is applied. This method involves segmenting the data sets into ten folds, with nine used for training and one for testing alternatively ten times changeable. This approach aims to mitigate any potential biases that could arise during the learning and training phases. Following this process, the accuracy is assessed and depicted in a confusion matrix as outlined in the methodology section.

The findings of this investigation reveal that the Random Forest machine learning algorithm superperforms others, achieving an impressive 90.5% accuracy in predicting credit ratings. Notably, our research sheds light on the significance of the loan-to-deposit ratio as a primary attribute affecting credit rating predictions. Moreover, this study uncovers additional pivotal banking features that intensely impact the measurements under study. This paper’s findings provide evidence that the loan-to-deposit ratio looks to be the purest bank attribute that affects credit rating prediction. In addition, deposit-to-assets ratio and profit sharing investment account ratio criteria are found to be effective in credit rating prediction and the ownership structure criterion came to be viewed as one of the essential bank attributes in credit rating prediction.

These findings contribute significant evidence to the understanding of attributes that strongly influence credit rating predictions within the banking sector. This study uniquely contributes by uncovering patterns that have not been previously documented in the literature, broadening our understanding in this field.

This paper aims to examine the informational value of credit rating changes for investors. The article analyses whether credit rating changes indicate the future financial performance of a firm.

The study employs pooled time-series cross-section regression technique and two-sample t-test for analysis. The paper utilizes a firm's operating profit as a proxy of its future financial performance to understand what inference can be drawn about future financial performance from a change in a firm's credit rating.

The paper finds that a firm operating profit declines in the year after a credit rating downgrade. However, no such significant relationship is evident in the case of a rating upgrade. The results are consistent across rating categories and individual years of the sample period.

The study uses non-financial corporate rating data; hence, the findings may not apply to credit rating changes in financial corporates and structured finance.

Investors and analysts can incorporate credit rating downgrade by CRAs as a key input in a firm's future financial forecast. Analysts and investment managers can also look at credit rating changes of firms in the same industry and draw a definite conclusion about which firm is likely to see a higher deterioration in performance.

The author has not come across any literature that directly investigates credit rating changes from the perspective of information content about future financial performance.

Prior studies generally focus on income smoothing through discretionary accruals and document that managers have incentives to smooth earnings due to various reasons. This paper aims to focus on income smoothing through research and development (R&D) management and examine whether and how income smoothing through R&D management affects credit rating agencies’ perception of firm risk.

The authors use financial statement data from the CRSP/Compustat Merged data set universe for the period from 1992 to 2019 after excluding financial and utility industries. The authors follow the model for credit ratings used in previous literature to test the hypothesis. Specifically, the authors use an ordered probit model to express credit ratings as a function of income smoothing attributes.

The authors find that R&D-based income smoothing improves a firm’s credit rating. However, the positive effect of R&D-based income smoothing on credit ratings is less than that of accruals-based income smoothing. This study also shows that the positive effect of R&D-based income smoothing is more pronounced for firms less subject to opportunistic incentives, further strengthening the notion that managers smooth earnings through R&D management to provide more informative earnings.

This study contributes to the income smoothing literature in several ways. First, the authors contribute to the research by showing that managers’ income smoothing activity through R&D management positively affects firms’ credit rating. Second, the authors also document the relative benefits of the two different income smoothing techniques in terms of improving credit agencies’ perception of firms’ creditworthiness.

This study mainly aims to explore the impact of management practices and managerial behavioral attributes on credit rating quality in Tehran Stock Exchange.

In this study, 214 firms were assessed from 2014 to 2020. The credit rating quality was measured through Technique for Order of Preference by Similarity to Ideal Solution and the entropy weighting method. In accordance with the theoretical literature, managerial entrenchment, managerial myopia, managerial overconfidence and managerial narcissism were considered as the managerial attributes. Furthermore, to examine management practices, cash flow management and accrual management were explored.

The results of this study showed that the cash flow from operations management and the accrual management has a significant positive effect on the credit rating quality. The managerial entrenchment, managerial narcissism and managerial myopia have significant negative effects on credit rating quality, while the effect of managerial overconfidence on credit rating quality is not significant.

Understanding the factors that affect the credit rating quality is of a great importance. Considering the significance of cash management in the present era and the impact of managerial psychological and behavioral characteristics in the development of the organization, empirical results of this study can help investors, capital market regulators and other stakeholders to strengthen the firm and better decisions.

This manuscript reports evidence on how debt-taking decisions of top management in a multi-country setting do affect credit rating scores assigned by credit rating agencies (CRAs) as global monitors of creditworthiness of borrowers. This aspect has been long ignored by researchers in the literature. The purpose of this paper is twofold. A test model is specified first using theories to connect debt-taking behavior to credit rating scores. Once that model helps to identify a number of statistically significant factors, the next step helps to identify threshold values at which the variables driving debt-taking behavior would worsen the credit rating scores as turning points of the thresholds.

The study identifies factors driving creditworthiness scores due to debt-taking behavior of countries and develops a correct research design to identify a model that explains (1) credit rating scores and the factors driving the scores and runs (2) panel-type regressions to test model fit. Having found factors driving debt-taking behavior by observed units, the next step identifies threshold values of factors at which point further debt-taking is likely to worsen credit rating risk of the observed units. This is a robustness test of the methodology used. The observed units are 20 countries with data series across 14 years.

First, new findings suggest there are about six major factors associated with debt-taking behavior and credit rating changes. Second, the model developed in this study is able to account for substantial variability while the identified factors are statistically significant within the normal p-values for acceptance of hypotheses. Finally, the threshold values of factors identified are likely to be useful for managerial decisions to judge the levels at which further debt-taking would worsen the credit rating scores of the observed units.

The observed units are from 20 countries over 14 years of annual data available on credit rating scores (privately obtained from Standard and Poor [S&P]). The sample represents major economies but did not include emerging countries. In that regard, it will be worthwhile to explore the debt-taking behavior of emerging economies in a future study using the methodology verified in this study.

The findings help add few useful guidelines for top management decisions. (1) There are actually factors that are associated with debt-taking behavior, so the authors now know these factors as guides for managerial actions. (2) The authors are free to state that the credit rating changes occur on objective changes in the factors found as significantly related to the debt-taking behavior. (3) The threshold values of key factors are known, so top management could use these threshold values of named factors to monitor if a debt-taking decision is going to push the credit rating to a worse score.

There are society-wide implications. Knowing that the world's debt level is high at US$2.2 for each gross domestic product (GDP) dollar across almost 200 countries, any knowledge on what factors help drive creditworthiness scores, thus credit riskiness, is revealed in this paper. Knowing those factors and also knowing the turning points of the factors – the threshold values – likely to worsen creditworthiness scores is a powerful tool for controlling excessive debt-taking by an observation unit included in this study (The dataset in this research can also be used to see inter-temporal movement on debt-taking in a future study).

In the authors' view, there are many studies on debt-taking behavior. But none has connected debt-taking on how (1) named factors are observable to management that affect credit rating changes and (2) if a factor affects creditworthiness, at which point of the factor value, the creditworthiness will flip to worsen the score. These aspects are seldom found in the literature. Hence, the paper is original with practical value at the global level.

The purpose of this paper is to examine to which extent ownership and board structure improve financial institutions’ credit ratings.

Ordered Probit regression models were used to examine the association between corporate governance attributes and banks’ credit ratings. The sample consists of 97 publicly traded financial institutions on Gulf Cooperation Council (GCC) stock exchange markets and cover the period 2010–2019. All GCC countries were considered in this study which are United Arab Emirates, Saudi Arabia, Bahrain, Oman, Kuwait and Qatar.

The results show that banks’ credit ratings are positively associated with the size of the board of directors and with the number of female directors serving in the board of directors. And it is negatively associated with the frequency of board meetings. Furthermore, this study finds evidence that nonbank financial institutions’ credit ratings are positively associated with CEO duality and with frequency of board meetings. Also, this study shows that their credit ratings are negatively associated with the ownership percentage held by the major five shareholders and with the number of board members serving in the board of directors.

Unlike previous research, this study focuses on the effect of the role of two different corporate governance dimensions, namely, ownership and board structure on the rating of financial institutions. This paper contributes to the extant literature in various ways. It bridges the gap of this topic in the GCC region. And, unlike previous research, this study focused on the financial sector and divided the sample into banks and other financial institutions to examine both subsamples separately. Also, this study introduced new ownership and board structure variables for the purpose of investigating the impact of corporate governance on financial institutions’ credit ratings such as the presence of women in the board of directors.