Conservatism in credit ratings

Credit rating agencies faced severe criticism due to the fact they didn’t predict the 2008 financial crisis. In the aftermath of the crisis, it appeared that asset-backed securities had been assigned with inflated ratings from the major agencies. In other words, it seems that credit rating agencies had relaxed their credit standards. The main problem was that financial institutions, regulators and investors were made the capital allocation decisions based on these ratings. Thus, they face severe losses, due to the increase in asymmetric information.

However, it is possible that the ratings became more conservative, after the technological crisis in 2001. Credit rating agencies applied stricter criteria in their assessments to protect from reputational risk. It is crucial to determine whether credit ratings were stricter during the period before 2008, and this change in credit rating agencies standards affect to firms’

financial profiles. Thus, I introduce the studies Baghai, Servaes, and Tamayo (2014), and Alp (2013).

Overall, the evidence provided in this sub-section, indicate that credit rating agencies become more conservatism about their corporate credit ratings assignments, in the period before the financial crisis of 2008. The capital markets take into account this conservatism and ask for lower yields for firms affected by phenomenon.

Alp (2013) studies the agencies’ credit standards stringency during the 1985 to 2007 period. She searches for differences in a firm’s credit rating during this period, while firm’s risk characteristics remain constant. She finds that stricter ratings are not assigned by credit rating agencies for every rating category. More specifically, loosen credit ratings observed is some rating categories during this period. Hence, she examines whether that rating agencies become stricter for investment grade and more lenient for speculative- grade assignments prior to 2002.

The author studies S&P’s and Moody’s reports, and she highlights that the majority of changes in credit ratings are downgrades indicating that credit ratings agencies become more conservative with their standards. She posits that due to heavy scrutiny after the agencies’ failure to predict the 2001 technological bubble, they try to protect their reputation by applying stricter credit standards.

Also, she creates variables to capture specific-firm characteristics like: interest coverage, operating margin, leverage, firm’s size, systematic risk, firm-specific risk, dividend payer, market value-to-book value ratio, research and expenses, retained earnings, capital expenditures, and cash balances and tangibility. She estimates a regression model of credit ratings against all these variables assigning a number to every rating letter: 1 for the CCC to 17 for the AAA.

She finds that the estimating coefficients of the regression for the 1985 to 2007 sample period are significant and have the logical signs except for the market-to-book ratio. More specifically, large profitable firms that pay dividends and firms with tangible assets, and higher growth opportunities are assigned with higher credit ratings. However, the results suggest that higher credit risk is expected for firm’s holding more cash.

Furthermore, the author estimates another ordered probit model using as dependent variables two sub-samples, the one for the investment-grade and the other for speculative- grade firms, and present the results. The results of the latter model are identical to them presented above. Compare to the whole sample, the signs of long-term debt and total debt leverage are reversed for speculative-grade firms, suggesting that the rating for speculative-grade firms is depended on total debt leverage. Also, the coefficient of long- term debt leverage is insignificant, indicating the speculative-firms doesn’t issue significant long-term debt amounts. She observes that unlike the investment-grade firms the cash balances coefficient is negative for speculative-grade, hence the negative cash balance in the entire sample is explained by speculative-grade firms.

Moreover, the author examines the changes of credit rating standards over time, using the year indicator variables. The results support that during the 1986 to 2002 period there is no clear trend because the coefficient estimates are close to zero. However, from 2003 to 2007 the coefficients are negative and significant, indicating that agencies adopt stricter credit standards post-2002.

She finds that year indicator variables were consistently negative in investment-grade subsample and positive in speculative-grade during the 1985 to 2002 period. It seems that credit rating agencies were more lenient in the speculative-grade ratings and stricter for investment-grade ratings. Therefore, based on the above evidence, she posits that there is shift towards conservatism in credit ratings around 2002, especially for speculative-grade firms.

Finally, the author examines the relation between ratings standards and credit spreads and the relation between ratings standards and default rates. She argues that if the investors understand that firms are downgraded because of the shift in stricter rating standards rather than increased credit risk, they should not ask for higher yields. The results of his analysis suggest that the changes in rating standards cannot be completely explained by a change in economic climate. In addition, she expects that the stringency of rating standards will decrease the credit risk of a given rating category because the increase in quality of the firms’ grouped together.

Baghai, Servaes, and Tamayo (2014) investigate the credit rating agencies’ conservatism and the effects of this event in firm’s finance decisions. They state that there is a common

view that the issuer-paid model creates incentives to agencies’ management, leading to inflated ratings. Their results are consistent with Alp’s (2013) on credit rating agencies’

conservatism.

In addition, they find that conservatism in credit ratings influence firms’ financial decisions, leading them to issue less debt compare to firms assigned with a rating consistent with their credit risk. Also, the stricter ratings have a negative impact on firm’s growth and investments in acquisitions strategy.

They present the explanatory variables used in their models as the determinants of firm credit ratings: leverage, convertible debt divided, rental expenses, cash and equivalents, debt-to-EBITDA ratio, interest coverage, profitability, the volatility of profits, size, tangibility, property, plant, and equipment, capital expenditures, the firm’s beta as a measurement of firm’s systematic risk, the firm-specific risk, and year indicator variables.

Moreover, they assess OLS and ordered logit models and they find that all explanatory variables are significant and have logical signs. More specifically, the firms with high amounts of debt, high rental payments, low profitability and increased uncertainty in their profits are more likely to default on their obligations. Similarly with Alp’s (2013) study, they find evidence that firm saving cash is assigned with lower-grade ratings. However, they key variables are the year indicators, all of them are positive and significant, supporting that credit standards become stricter over time.

The authors postulate that credit standards had been readapted by credit rating agencies to the changes in the macroeconomic environment. Otherwise, the firms’ credit ratings may be worse than those implied by their actual credit risk. Hence, if expected default rates decline overtime, the latter assumption will be valid. Their results confirm the hypothesis that credit ratings become stricter, since default rates decreasing over time during the sample period.

Furthermore, the authors expect the stringency in credit standards force firms to use less debt. Thus, they define as dependent variable the difference between actual firms’ ratings and predicted firms’ ratings (a measure of conservatism) and estimate a regression with the aforementioned explanatory variables. Their findings suggest that credit rating agencies’ conservatism affect firm’s capital structure. More specifically, they predict that firms with assets which can be used as collateral, lower expenses for development, significant and constant profits, and more often smaller is size, issue more debt among others. They also argue agencies’ conservatism affect firm’s financial decisions stricter ratings equal to less debt issues.

The authors study whether the increased stringency of the rating agencies had real effects.

They focus on firm growth as well as various investment decisions: capital expenditures, acquisitions, and R&D and estimate models of growth and investment, including their measure of conservatism as an additional explanatory variable. The results indicate that stringency in credit ratings decreases firm’s ability to grow and to participate in acquisitions.

In addition, they study whether the credit rating agencies conservatism influence bond spreads. To determine whether investors understand the increase in conservatism over

time when they make their cost of debt assessment, the authors estimate a regression model of spreads against the difference between actual firms’ ratings and predicted firms’

ratings, and some control variables. Their findings are similar with Alp’s result in the specific hypothesis. It seems that investors understand credit standards stringency and ask for lower yields, hence the spreads get tighter.

To sum up, Baghai, Servaes, and Tamayo results are consistent with Alp’s (2013) on credit rating agencies’ conservatism. In addition, they find that conservatism in credit ratings influence firms’ financial decisions, leading them to issue less debt compare to firms assigned with a rating consistent with their credit risk. Also, stricter ratings have a negative impact on firm’s growth and investments in acquisitions strategy.