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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.

The objective of this paper is to study the impact of political connection and governance on credit rating and whether there is a substitution or complementary relationship between them.

In order to achieve the objective, a succession of eight ordered probit regressions has been carried out. Moderating variables between the political connection and governance characteristics were introduced. The whole population is taken as a sample, i.e., 27 Tunisian companies that are evaluated by FITSH NORTH AFRICA agencies over a period of 10 years (2009–2018).

The outcomes are mixed. They show that the political connection does not always influence credit rating; the size and board independence always improves credit rating; the duality between the functions affects credit rating; whereas the majorities’ proportion does not influence credit rating; and a substitution between the political connection and the governance characteristics is validated.

Like any other research, our results are factors of our measures and variable choice and depends heavily on the how these variables were conceived. Also, although our number of observations responds to the statistical result generalization requirements, our sample remains relatively narrow with 27 companies only.

In practice, the research will allow investors to have a better vision upon the future of their investments based on whether to develop their governance system or promote political networking. It will also prompt lenders to look beyond ratings and consider factors such as political connections to make a rational judgment on their future placements.

This study leads us to find various solutions: the establishment of credit agencies that take into consideration all the data of all the operators taken as a whole (bank, leasing company, and factoring). It encourages the reorganization of the Tunisian banking sector through mergers for example.

This study is a pioneer in the credit rating field in Tunisia, where the source of debt financing is the most used by all enterprises across all sectors. This study extends the literature of political connection effectiveness, independent directors, board size, in improving corporate performance and credit rating.

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 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.

This paper aims to examine whether firms engage in earnings management immediately after experiencing a downgrade in their credit rating.

This paper uses fixed-effects regression models to examine real- and accrual-based earnings management after firms experience a downgrade in their credit rating.

Inconsistent with prior studies where firms are reported to opportunistically increase their earnings prior to a credit rating event, this paper finds that firms use income-decreasing earnings management after their ratings are downgraded. This paper also finds that firms downgraded to below the investment grade rating not only significantly reduce both abnormal cash flows and discretionary accruals but also report larger asset impairments, suggesting that these firms exploit the rating downgrade to employ a big bath accounting.

The results of this paper have practical implications for investors fixating on firm earnings after a credit rating downgrade, for shareholders of downgraded firms and regulators such as credit rating agencies.

The findings of this study contribute to the thin literature on earnings management after changes in credit rating by shedding lights on earnings management after a rating downgrade and complement the literature on the accounting choice of financially distressed firms. The empirical evidence documented in this study suggests that the occurrence of income-decreasing earnings management is not limited to only after a sovereign country rating downgrade as documented in a prior study but also occurs after a rating downgrade not associated with this event.

To determine the effect that covenants have on the credit ratings assigned by the two major agencies.

The authors examine 1,822 bond issues from 1991 to 2018, with a two-stage methodology to account for the endogeneity of the firms' choices and the ordinal nature of the ratings. The authors use Hendry's model selection method to find the best-fitting models from 37 control variables; the final models feature 20–24 orthogonalized variables, all significant at 5% and most at 1%.

The study’s results suggest that restrictive covenants positively affect ratings, particularly for bonds on the border of junk and investment grade. However, this effect appears to be decreasing with time, suggesting the financial crisis of 2008 has impacted ratings. Additionally, divergent covenant treatment leads to split ratings where the two agencies assign different levels of ratings on the same bonds. The study’s findings provide key insights into the factors that differentiate ratings given by each agency.

Managers must balance the perceived benefits of covenants against the costs, included lower credit ratings.

No other study has examined this issue controlling for both the ordinal nature of the ratings and the endogeneity in the decision to include specific covenants.

This paper aims to investigate how a US firm’s political landscape affects the integration of environmental, social and governance (hereafter ESG) measures in CEO compensation contracts, thereby affecting the firm’s ESG performance and credit rating.

Based on the results of state senatorial and presidential elections and the location of a US firm’s headquarters, the authors categorize whether a firm has a political environment that is predominantly Democratic (blue) or Republican (red). The empirical analyses are based on a sample of US firms in the period 2014–2021.

The authors find that firms in blue states are more likely to link CEO compensation to ESG performance measures. Further, the results show that firms in blue states with ESG-linked compensation contracts have better ESG performance. Lastly, the authors find evidence that a firm’s ESG performance has a positive impact on its credit rating, but the impact is weakened if firms in red states link ESG performance to executive compensation.

To the best of the authors’ knowledge, this is the first research that explores how a firm’s political environment affects the use of ESG performance measures in CEO compensation contracts. Furthermore, the authors contribute to the literature by showing evidence that the political environment interacts with the impact of ESG-linked compensation incentives on the firm’s ESG performance and, thus, its credit rating.

This research aims to revisit Gul and Goodwin (2010), which focuses on exploring the relationship between debt maturity structure, credit ratings and audit fees. Furthermore, the authors investigate whether this association varies based on firm size, firm life cycle and financial reporting quality.

To investigate the research question, the authors use an extended sample period, 2004–2017, in comparison to the sample period, 2003–2006, used in Gul and Goodwin (2010). The authors use ordinary least squares regression as a baseline methodology along with two-stage least-squares regression and change analysis to control for endogeneity concerns.

According to Gul and Goodwin (2010), auditors charge lower audit fees for firms with higher short-maturity debt and better credit ratings, indicating a lower likelihood of financial misreporting. Further, Gul and Goodwin (2010) find that lower credit rated firms benefit more from short-term debt. Primarily, the findings are consistent with Gul and Goodwin (2010) and provide further evidence that the beneficial effects of short-maturity debt for firms with poor ratings are evident for small firms, firms in the growth stage of their life cycle and firms with poor earnings quality.

The findings imply that practitioners in the audit profession and investors should take a more nuanced and comprehensive approach to varied firm and financial factors, taking into consideration the intricate relationships between many elements impacting a firm’s financial health. As a result, audit professionals may give more accurate appraisals of a firm’s financial condition, and investors can make better investment decisions.

The authors reconfirm the findings of Gul and Goodwin (2010) using an extended sample. The findings are novel, which evidence that the lower audit fees for rated firms with short-maturity debt are moderated by firm size, life cycle and financial reporting quality.

The purpose of this study is to examine whether the required disclosure and the high frequency of key audit matters (KAMs) are likely to moderate the effect of higher credit risk on earnings quality.

This study uses 15,106 Taiwanese firm-year observations to explore the relationship between earnings quality and credit risk during the 2011 to 2020 period. We use the two-stage least squares method to test whether the presence of KAM disclosures moderated the association between earnings quality and credit risk and also to examine whether higher KAM frequency moderates the association between earnings quality and credit risk.

Our results provide evidence that the presence of a KAM disclosure requirement moderates the impact of firms with higher credit risk on earnings quality. In addition, there is significant evidence that the higher the frequency of KAM disclosures the greater the moderation impact that is found.

This research investigates whether the disclosure and high frequency of KAMs moderates the effect of credit riskiness on earnings quality. This study improves our understanding of whether more KAMs disclosures would improve earnings quality of firms with higher credit risk. In addition, we also use Beneish M-SCORE, as an alternative earnings quality proxy, to reinforce our empirical results. This markedly differentiates this paper from other studies.