Is the Effect of Earnings Management Neutral on the Bank Cost of Debt?
—The Credit Rating Approach—
Chung-Hua ShenDepartment of Finance
National Taiwan University
Yu-Li HuangDepartment of Money and Banking
National Chengchi University
2
Motivation
Healy and Wahlen (1999) indicate financial statements exist the phenomenon of earnings management is prevalent.
Past studies focus on the effect of EM on stock returns. (Sloan,1996; Collins and Hribar, 2000; Rangan, 1998; Teoh et al., 1998a, 1998b)
Bhattacharya et al. (2003) find EM adversely affects the cost of equity and the trading in the stock market.
Few studies have examined whether EM also affects
debt burden.
3
The purpose of this paper
This study examines the impact of EM on bank borrowing cost through the changes in credit ratings
Since banks managing their earnings creating asymmetric information, we want to know
whether credit rating agencies (CRAs) know banks manage their earnings
how do they evaluate this behavior.
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Effect of EM on Credit Ratings
1.EM has only a “neutral” effect on credit ratings.
(1) Raters do not recognize the existence of any EM because the information of engaging in EM is not immediately available to the public.
(2) Raters know EM but care little about it. Raters see EM is simply shifting income between
current and future periods and therefore as not altering firms’ intrinsic value.
5Effect of EM on Credit Ratings
2.EM has an “adverse” effect on credit ratings
Raters know earnings are managed either from public or non-public information and do not agree with banks’ EM behavior.
Since EM creates asymmetric information, this suggests true financial strength is suspicious and true losses are hidden.
6Effect of EM on Credit Ratings
3.EM increases for banks credit ratings.
Raters believe EM can smooth income or boost current earnings. The former can decrease tax payable while the latter can increase earnings per share and thus help drive up the stock price.
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This Paper focus on
1.the banking industry Since the serious asymmetric information problem. Banks have a greater incentive to smooth earnings than non-
financial firms and their financial stability is paramount given their critical economic role.
2.across 85 countries. Different countries have different information asymmetry The use of cross-country data further enables researching
how asymmetric information influences the impact of EM at the country level.
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Our Better Governance Effect Hypothesis
A. In a country with better governance: We posit the asymmetric information problem is mitigated in a
country with better governance. even when a bank manages its earnings, raters view reported
earnings as trustworthy, reducing the impact of EM to insignificance.
Expectation: EM does not affect ratings and thus does not affect the cost of borrowing.
B. In a country with weak governance, raters realize there is severe information asymmetry and do not
trust the reported earnings, Expectation: weak governance aggravating the impact of
EM on ratings
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Three Proxies for Better Governance
1.In a high-income country. Previous studies indicate the information asymmetry problem in high-
income or well-developed countries is effectively reduced but this problem is aggravated in less-developed countries. (Cantor and Falkenstein, 2001; Vives, 2006; Poon, 2003)
2.Financial statements are audited by Big-Five auditors. Literatures suggest auditing reduces information asymmetries between
managers and firm shareholders by allowing outsiders to verify the validity of financial statements. (DeAngelo, 1981; Becker et al., 1998)
3.In an environment with strong creditor protection. The protection of creditor rights provided by national laws and regulations
signals the ease with which creditors can repossess collateral and take control of a firm in the event of default. (Galindo and Micco, 2004, 2007)
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Measures of EM
1.Earnings Smoothing (EM1)
A higher positive correlation coefficient implies greater earnings smoothing. (Chi, Chih and Shen, 2007)
),(,
,
,
,,
1ti
ti
1ti
titi TA
EBP
AT
LLP 1EM
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Measures of EM
2.Discretionary Accrual (DLLP, EM2)
Large DLLP values are conventionally interpreted as the existence of EM (Cornett et al., 2006).
tititi DLLP2EM ,,, ̂
, , ,
, , , ,
i t 0 1 i t 2 i t
3 i t 1 4 i t 5 i t 1 i t
LLP LOANS NCO
NPL NPL LLR
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Econometric Model
Dependent Variable :Rating is the observed long-term foreign currency credit
rating of a bankThe original sample consists of 3,475 bank-year
observations from 85 countries.
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14
Ordered Probit Model
where, C is the number of countries,
B is the number of banks in country i and T is the time span, from 2002~2008.
1,..., , 1,..., , 1,..., ,ii C j B t T
Proxies for Governance Variables
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1 11 12Z
We expect if strong governance if weak governance Net effect of EM (=α):
α = 0 if strong governance α < 0 if weak governance
12 0 12 > 0
11 12
11 12
( + Z) EM
= EM + Z EM
= EM
11 0
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Control variables
Earnings management indicators
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Z=(HIC, MIC, EEUROPE, EASIA, LATIN, AUDITOR, CREDITOR)
All of these are dummy variables
This index ranges from 0 to 4
1.We use HIC, AUDITOR, CREDITOR to proxy better governance.
2.We use MIC, EEUROPE, EASIA, LATIN, non BIG-5 auditors, lower CREDITOR to proxy weak governance.
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1. the correlation coefficient between rating and EM1 at –0.072, implying credit ratings are negatively correlated with earnings smoothing.
2. a negative correlation coefficient exists between rating and EM2 (–0.144), suggesting a DLLP is associated with low rating.
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the average of EM1 increases with deteriorating ratings, implying that lower rated banks tend to smooth their earnings.
except for AAA, EM2 values increase with deteriorated ratings, implying banks with higher DLLP tend to receive worse ratings.
Overall, lower rated banks are associated with active EM, indicating that raters consider EM a “negative” factor when assigning credit ratings.
larger
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Panel B illustrates the positive relationship between sovereign and bank ratings. With few exceptions, national sovereign rating typically acts as the ceiling for local bank rating.
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Panel C shows the conditional variables across different rating grades. 1.AAA rated banks are restricted to high-income countries, and
elsewhere most banks are rated lower. 2.AAA rated banks are all rated by Big-Five auditors. 3.Creditor protection and ratings exhibit no significant trend.
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All coefficients of EM1 are negative indicating a bank that smoothes its earnings more is likely to receive a lower rating.
The coefficients of EM1×HIC, EM1× AUDITOR, EM1×CREDITOR are all significantly positive as our expectation, suggesting asymmetric information problem is mitigated .
The coefficients of EM1×MIC, EM1×EEUROPE, EM1×EASIA are all significantly negative, indicating the adverse effect of earnings smoothing on ratings is aggravated.
The net effect is zero in HIC, AUDITOR and when CREDITOR is 2 or 3.
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The coefficient of EM2 is significantly negative indicating banks with higher DLLP tend to obtain a lower rating.
The coefficient of EM2×HIC is significantly positive and the coefficient of EM2×MIC, EM2×EEUROPE, are significantly negative.
All these results support our governance effect. The zero net effect exists in HIC.
Support our Better Governance Effect.
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Robust Testing
1. Effect of Sovereign CeilingWhile this study has considered SCR as one of the
explanatory variables for controlling the third variable effect (Borensztein et al., 2007), influences from other unknown routes may persist, biasing the hypothesis.
We exclude bank ratings meet or exceed sovereign ratings because we expect these banks’ incentive to manage earnings to obtain a better rating is small.
We use only bank ratings are below sovereign ratings (2,974 observations).
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Robust Testing
2. Effect of Capital ManagementThe previous literature found that bank managers use
LLP to perform EM, capital management, and to signal private information regarding future prospects (Collins et al., 1995; Beaver and Engel, 1996; Ahmed et al., 1999).
Banks thus may conduct EM for purposes of capital management rather than for ratings.
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We find the sign and significance of the coefficients are the same as Table 6. EM1 has neutral and negative effects in countries with better and worse governance, respectively, even after removing the sample of meeting and exceeding sovereign ceiling.
Our better governance effect is still supported.
The sign and significance are the same as Table 6.
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We find the sign and significance of the coefficients are still the same as Table 7.
Our better governance effect is still supported.
The sign and significance are the same as Table 7.
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The Effect of Capital Management
This study creates three dummy variables, CAR8, CAR8_10 and CAR10, representing banks with capital adequacy ratio (CAR) less than 8, 8~10 and greater than 10%, respectively.
The new regression model considering the effect of CAR becomes
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We find the negative effect of earnings smoothing is mitigated in HIC and when banks’ financial statements are audited by Big-5 auditors when capital adequacy ratio is below 10%
The negative effect of EM1 on ratings is aggravated in MIC when CAR is below 10%.
The result still support our better governance effect.
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When CAR10 is used, the coefficients of EM2×HIC and EM2×MIC are significantly positive and negative again supporting our better governance hypothesis.
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Conclusions
The negative influence of EM on ratings exists and is robust after controlling for other potential determinants of a bank credit rating.
That is, raters are aware of the existence of EM, and take a negative view towards this behavior when assigning ratings.
Our better governance hypothesis is supported. The negative effect of EM is mitigated in counties with better
governance but aggravated in countries with worse governance.
Furthermore, the neutral effect also exists in countries with better governance.
