This study provided a comprehensive analysis into the investigation of the relationship between corporate governance and corporate credit ratings for US firms. Ordered logistic regression models were used, which is a method first conceived by McCullagh (1980), and rightly recommended by the likes of Alali et al. (2012) and Ashbaugh-Skaife (2006), who also investigated the impact of corporate governance on corporate bond ratings, for similar studies to theirs. The investigation into different types of models for explaining corporate bond ratings, conducted by Ederington (1985), aided the decision to use the chosen method. Whereas prior literature has proven links between corporate governance, surrogated by the G index of Gompers et al. (2003), the Gov-scire of Brown and Caylor (2006), and an entrenchment score of Bebchuk et al. (2009), as well as other surrogates
such as board member and audit committee compensation (used by Anderson et al., 2004); the present study finds further supporting evidence of the link by calculating another index for governance score based on the sum of strengths and weaknesses from MSCI (formerly KLD and GMI) data. The results find a highly statistically significant link, with sensitivity increasing for firms with investment grade ratings, and less for firms with speculative grade ratings. For the investigation into whether there is a trend over time in this relationship, or whether the Great Recession impacted the resulting credit ratings firms were given, the analysis finds no significant change and thus there is no trend over time or impact from the financial crisis. Overall, time and the Great Recession themselves were found to significantly impact credit ratings, both with negative coefficients, but not the relationship between corporate governance and credit ratings.
Our results are robust to a convincing extent, detailed in Section 6, strengthening the concluding remarks. Theories concerning this relationship, such as corporate governance being a secondary factor rather than primary in deciding credit ratings are proven to be consistent, with investment grade firms having ratings more dependent on corporate governance than speculative grade firms, and with corporate governance having smaller impacts on credit ratings than other financial variables which were included in the models used. Notably, we find different results to Murcia et al. (2014), who found corporate governance to have an insignificant link to credit ratings on Brazilian firms. However, the corporate governance variable used in their study was a dummy variable based on precise selection criteria, and not one broad enough to capture differences in levels of corporate governance.
Although there exists a high degree of completeness, this study wasn’t without its own limitations. Firstly, whilst it was intended to use the most modern data available, it was not possible to calculate corporate governance scores for firms in the years beyond 2013.
An extensive 23-year range of data was used, which is much more extensive than other studies investigating the same area, but the newest data is what will be most relevant to modern applications of the study. Secondly, the equivalent data for calculating a corporate governance score was not available for European firms, which would have provided excellent grounds for further robustness checks. Lastly, there are differences in the years that different provisions of strengths and weakness for calculating corporate governance were measured over. For example, the corporate governance concern of Accounting
Concern (CGOV_con_G) was only measured through years 2005 to 2009, whilst the Political Policy Strength (CGOV_str_F) was only measured through years 2007 to 2011.
If firms were to realise how the score was calculated and specifically targeted a higher score, it would be possible for recorded strengths to be accumulated but for weaknesses in other areas not measured to not be counted towards this score, therefore skewing the result. However, it is incredibly unlikely that firms were aware of the present scoring method for corporate governance and even more unlikely they would target a high score based on this method alone. Even if they did and they were successful, the winsorization applied likely forbids these results from skewing the dataset significantly. Nevertheless, we cannot be sure that this wouldn’t have an impact on our results in a way of magnitude or significance of the Corporate_Governance variable that was generated.
Even whilst factoring in the limitations of the study, the same differences in measures are applied for every firm in the same years, and the total years included in the study are comprehensive enough to draw firm conclusions. Additionally, whilst it was not possible to get newer data, the data collected is very modern given the selected region is North America, which is a highly economically developed continent relative to Asia or South America. We therefore have highly relevant data and much more complete data than other studies in the same area of research, making this one of the most extensive papers yet.
For future studies within this area, it is recommended to apply the model used here to newer data once it becomes more available, to apply the model to low economically developed countries to investigate whether the same results apply, and to use other methods of calculating governance score to add further robustness to the results.
The results of our study have especially relevant implications for a firm’s management team. It is known that credit ratings directly affect the cost of borrowing and therefore its overall capital structure (Kisgen, 2006), and we know from the present study and others that corporate governance is linked to the credit ratings. Therefore, there is an opportunity for management to target improvements in their firm’s credit ratings through boosting the corporate governance levels of their firm and to reap benefits in the form of more efficient and cost-effective capital structures. We detail that over time credit ratings have generally decreased in superiority, meaning that determinants including corporate governance have and will likely continue to become more important for maintaining credit ratings, but that credit ratings have not increased in sensitivity to corporate governance levels. Firm
management should not specifically focus on increasing corporate governance levels during times of financial crises yet should consider implementing improvements if/when firms have rating increases from a speculative to investment grade, in order to utilise the increase in sensitivity ratings have to corporate governance in this group.
References
Alali, F., Anandarajan, A. and Jiang, W., 2012. The effect of corporate governance on firm’s credit ratings: further evidence using governance score in the United
States. Accounting & Finance, 52(2), 291-312.
Allison, P. D., 1999. Multiple Regression: A Primer. 1st ed. Thousand Oaks, California:
SAGE Publications, 142.
Altman, E. and Katz, S., 1976. Statistical bond rating classification using financial and accounting data. Proceedings of the Conference on Topical Research in Accounting, 205-239.
Ashbaugh-Skaife, H., Collins, D., & LaFond, R. (2006). The effects of corporate governance on firms’ credit ratings. Journal of Accounting and Economics, 42(1), 203-243
Bebchuk, L., A. Cohen, and A. Ferrel, 2009, What matters in corporate governance?
Review of Financial Studies 22(2), 783–827.
Bhojraj, S. and Sengupta, P., 2003. Effect of Corporate Governance on Bond Ratings and Yields: The Role of Institutional Investors and Outside Directors. The Journal of Business, 76(3), 455-475.
Bradley, M., Dallas, G. S., Snyderwine, E. and Chen, D., 2008. The Effects of
Corporate Governance Attributes on Credit Ratings and Bond Yields. SSRN Electronic Journal, 1-35.
Brown, L.D. and Caylor, M.L., 2006. Corporate Governance and Firm Valuation. Journal of Accounting and Public Policy, 25(4), 409-434.
Chang, S., Stuckler, D., Yip, P. and Gunnell, D., 2013. Impact of 2008 Global
Economic Crisis on Suicide: Time Trend Study in 54 Countries. BMJ, 347. Available at: https://www.bmj.com/content/347/bmj.f5239. Last Received: 05/01/2022.
Chavez, G.A. and Silva, A.C., 2009. Brazil's Experiment with Corporate Governance.
Journal of Applied Corporate Finance, 21(1), 36-44.
Daoud, J., 2017. Multicollinearity and Regression Analysis. Journal of Physics:
Conference Series, 949(1), 1-6.
Ederington, L., 1985. Classification Models and Bond Ratings. The Financial Review, 20(4), 237-262.
Feki, ِA. and Khoufi, W., 2015. The Determinants of Issuers’ Long Term Credit
Ratings: American S&P500 Index. International Journal of Accounting and Economics Studies, 3(1), 78-85.
Gompers, P., Ishii, J. and Metrick, A., 2003. Corporate Governance and Equity Prices. The Quarterly Journal of Economics, 118(1), 107-156.
Gupta, R., 2021. Financial Determinants of Corporate Credit Ratings: An Indian Evidence. International Journal of Finance & Economics, 1-16.
Gupta, R., Gupta, D. B. and Chahal, H., 2017. Financial Determinants of Credit Ratings of Indian Companies. International Journal of Business Insights and Transformation, 10(2), 30-37.
Horrigan, J., 1966. The Determination of Long-Term Credit Standing with Financial Ratios. Journal of Accounting Research, 4, 44-62.
Huang, Z., Chen, H., Hsu, C., Chen, W. and Wu, S., 2004. Credit Rating Analysis With Support Vector Machines and Neural Networks: A Market Comparative
Study. Decision Support Systems, 37(4), 543-558.
Johnston, R., Jones, K. and Manley, D., 2017. Confounding and Collinearity in Regression Analysis: A Cautionary Tale and an Alternative Procedure, Illustrated by Studies of British Voting Behaviour. Quality & Quantity, 52(4), 1957-1976.
Kirkpatrick, G., 2009. The Corporate Governance Lessons from the Financial Crisis. Financial Market Trends, 2009/1, 1-30. Available at:
https://www.oecd.org/daf/ca/corporategovernanceprinciples/42229620.pdf. Last Received: 05/01/2022.
Kisgen, D. J., 2006. Credit Ratings and Capital Structure. The Journal of Finance, 61(3), 1035-1072.
Matthies, A. B., 2013. Empirical Research on Corporate Credit-ratings: A Literature Review. SFB 649 Discussion Paper, 1-26.
McCullagh, P., 1980. Regression Models for Ordinal Data. Journal of the Royal Statistical Society: Series B (Methodological), 42(2), 109-127.
McFadden, D., 1977. Quantitative Methods for Analyzing Travel Behaviour of Individuals: Some Recent Developments. Cowles Foundation Discussion Paper No.
474, 35. Available at: https://cowles.yale.edu/sites/default/files/files/pub/d04/d0474.pdf.
Last Received: 05/01/2022.
Menard, S., 2000. Coefficients of Determination for Multiple Logistic Regression Analysis. The American Statistician, 54(1), 17-24.
Menard, S., 2001. Applied logistic regression analysis. 2nd ed. Thousand Oaks, California: SAGE Publications, 1-128.
Merle, R., 2018. A Guide to the Financial Crisis — 10 years later. The Washington Post. Available at: https://www.washingtonpost.com/business/economy/a-guide-to-the-
financial-crisis--10-years-later/2018/09/10/114b76ba-af10-11e8-a20b-5f4f84429666_story.html. Last Received: 05/01/2022.
Mohamad, S., 2004. The Importance of Effective Corporate Governance. SSRN Electronic Journal, 1.
Murcia, F., Murcia, F., Rover, S. and Borba, J., 2014. The Determinants of Credit Rating: Brazilian Evidence. Brazilian Administration Review, 11(2), 188-209.
OECD, 2010. Corporate Governance and the Financial Crisis: Conclusions and
Emerging Good Practices to Enhance Implementation of the Principles. 1-34. Available at: https://www.oecd.org/daf/ca/corporategovernanceprinciples/44679170.pdf. Last Received: 05/01/2022.
Pinches, G. and Mingo, K., 1975. The Role of Subordination and Industrial Bond Ratings. The Journal of Finance, 30(1), 201-206.
S&P Global Ratings, n.d. Guide to Credit Rating Essentials: What Are Credit Ratings and How Do They Work? 1-22. Available at:
https://www.spglobal.com/ratings/_division-assets/pdfs/guide_to_credit_rating_essentials_digital.pdf. Last Received: 05/01/2022.
Sareen, R. and Vij, M., 2022. Corporate Governance and Credit Ratings. Journal of Business Thought, 5, 103-125.
Schneider, D., 2015. The Great Recession, Fertility, and Uncertainty: Evidence From the United States. Journal of Marriage and Family, 77(5), 1144-1156.
Standard & Poor’s Governance Services, 2004. Standard & Poor’s Corporate
Governance Scores and Evaluations. Criteria, Methodology and Definitions. New York:
McGraw-Hill, 1-23. Available at: https://pdf4pro.com/cdn/standard-amp-poor-s-corporate-governance-scores-2e0f9.pdf. Last Received: 05/01/2022.
Standard & Poor’s Ratings Services. (2010). Guide to Credit Ratings Criteria: Why Criteria Are Important and How They Are Applied. 1-19. Available at:
https://www.countyofkane.org/Lists/Events/Attachments/541/Why%20Criteria%20Are
%20Important-How%20They%20Are%20Applied.pdf. Last Received: 05/01/2022.
Tarigan, C. K. and Fitriany, F., 2017. Impact of Corporate Governance on Credit Rating. Advances in Economics, Business and Management Research, 55, 248-253.
United Nations on Trade and Development (UNCTAD), 2010. Corporate Governance in the Wake of the Financial Crisis. 1-159. Available at:
https://unctad.org/system/files/official-document/diaeed20102_en.pdf. Last Received:
05/01/2022.
Wijayatunga, P., Mase, S. and Nakamura, M., 2006. Appraisal of companies with Bayesian networks. International Journal of Business Intelligence and Data Mining, 1(3), 329-346.
Appendix
Table A1: Credit Ratings Data Spread Over Time Rating
Year
1 2 3 4 5 6 7
Total
1991 4 6 13 36 58 40 11 168
1992 4 7 11 38 63 39 11 173
1993 0 7 12 35 70 43 10 177
1994 0 5 14 39 78 35 10 181
1995 0 4 16 44 77 34 9 184
1996 0 4 15 49 86 31 9 194
1997 0 7 14 58 92 32 8 211
1998 1 4 15 61 98 27 8 214
1999 0 4 21 71 106 28 7 237
2000 1 2 23 85 112 27 8 258
2001 2 30 64 132 141 25 9 403
2002 4 21 84 160 135 26 8 438
2003 11 84 164 225 139 20 7 650
2005 11 113 183 229 139 18 7 700
2004 6 118 193 237 135 16 6 711
2006 9 114 203 239 133 18 5 721
2007 8 132 218 252 131 20 5 766
2008 5 120 224 256 131 20 4 760
2009 10 140 203 259 120 20 5 757
2010 19 152 185 276 114 18 4 768
2011 10 148 196 288 125 16 4 787
2012 7 142 227 292 127 14 4 813
2013 5 140 228 311 145 20 5 854
Total 117 1504 2526 3672 2555 587 164 11125