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Review of Accounting Studies
Erschienen in: Review of Accounting Studies 1/2014

01.03.2014

Impact of proximity to debt covenant violation on earnings management

verfasst von: Diana R. Franz, Hassan R. HassabElnaby, Gerald J. Lobo

Erschienen in: Review of Accounting Studies | Ausgabe 1/2014

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Abstract

We examine the impact of differential incentives arising from proximity to debt covenant violation on earnings management. We reason that firms with loans close to violation or in technical default of their debt covenants have a stronger incentive to engage in earnings management than firms that are far from violating their debt covenants. We find results consistent with this expectation. Firms close to violation or in technical default of their debt covenants engage in higher levels of accounting earnings management, real earnings management, and total earnings management than far-from-violation firms. In additional analysis, we find that firms with a stronger incentive to avoid covenant violation switched from using more accounting earnings management before the Sarbanes–Oxley Act to using more real earnings management and more total earnings management afterwards. We also document that the earnings management implications of debt covenant violation are observed primarily for firms with poor credit ratings and for firms that do not meet analyst forecasts.
Vorheriger Artikel Distilling the reserve for uncertain tax positions: the revealing case of black liquor
Nächster Artikel A new measure of accounting quality

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Fußnoten
1
Additionally, firms may also use accounting method changes to manage earnings. However, many private debt contracts constrain the use of such changes (Mohrman 1996; Beatty et al. 2002).
 
2
Prior research that indirectly examines the tradeoffs between AEM and REM includes Barton (2001), Kilic et al. (2013), and Pincus and Rajgopal (2002), who study income smoothing through derivative hedging and loan loss provisions; Hunt et al. (1996), who study earnings management to meet solvency and tax and financial reporting goals; and Zang (2012), who focuses on litigation risk.
 
3
In a robustness test, we also consider net worth covenants.
 
4
Dealscan includes the average life for most loans. Using the average life to represent the effective life of the loan does not change the main conclusions.
 
5
We also conduct our analysis on the active sample only. The results (not tabulated) are qualitatively similar.
 
6
We also conduct the analysis after classifying loans with covenant proximity between zero and 10 % as CLOSE. Although this alternate classification reduces the sample size considerably, it does not alter the main results.
 
7
Rule 4-08 of Regulation S-X of the United States Securities and Exchange Commission (17 CFR §210.4-08, i.e., “Rule 4-08,” entitled “General notes to financial statements” and Item 303 of Regulation S–K (17 CFR §229.303, i.e., “Item 303,” entitled “Management’s Discussion and Analysis of Financial Condition and Results of Operations” MD&A).
 
8
We adjust data items reported on a cumulative basis in COMPUSTAT to reflect quarterly values.
 
9
Kothari et al. (2005) find that matching on current ROA outperforms matching on lagged ROA. Therefore we match on current ROA. However, matching on lagged ROA does not change our main inferences. Current ROA is more correlated with the mean realization of discretionary accruals than lagged ROA.
 
10
Many syndicated loan contracts place restrictions on asset sales. In our sample, almost 41 % of the debt contracts include asset sweep covenants. These covenants determine the percentage of the loan that must be repaid if a firm sells more than a certain dollar amount of its assets. This suggests that the relation between closeness to (or violation of) a current ratio covenant and gains from asset sales likely are spurious.
 
11
We also estimate the models using OLS and report these results in footnotes when the inferences from OLS and QR are qualitatively different.
 
12
Quarterly CEO bonus and stock option payment data are not available; therefore we do not include them as control variables in our models.
 
13
Using OLS estimation, the coefficient on DEFAULT is positive but insignificant in the TEM1 model and significantly positive at the 5 % level in the TEM2 model.
 
14
Using OLS the coefficients on CLOSE are significantly positive at the 1 % level for the AEM DA and AEM PMDA models. The coefficient on DEFAULT is significantly positive at the 1 % level for the AEM DA model but insignificant for the AEM PMDA model.
 
15
Using OLS the coefficient on DEFAULT is significantly positive for the REM COMBINE model and significantly negative for the REM EXP and REM CFO models at the 10 % level. The coefficient on DEFAULT is significantly negative at the 10 % level for the REM CFO model.
 
16
We thank an anonymous reviewer for suggesting this test.
 
17
We recognize that firms with low credit ratings are more likely to be close to or in violation of debt covenants. The overlap in classifications will likely reduce the efficacy of this analysis. In a robustness test, we estimate financial distress using Ohlson’s (1980) model.
 
18
Using OLS the coefficient on CREDIT_RATINGS in column (3) for REM is significantly negative at the 10 % level. The coefficients on DEFAULT*CREDIT_RATINGS in columns (2) and (3) are significantly negative at the 10 % level.
 
19
Using OLS the coefficients on MEET in column (2) for AEM and column (3) for REM are significantly negative at the 10 % level, while DEFAULT*MEET in column (1) for TEM is insignificant.
 
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Metadaten
Titel
Impact of proximity to debt covenant violation on earnings management
verfasst von
Diana R. Franz
Hassan R. HassabElnaby
Gerald J. Lobo
Publikationsdatum
01.03.2014
Verlag
Springer US
Erschienen in
Review of Accounting Studies / Ausgabe 1/2014
Print ISSN: 1380-6653
Elektronische ISSN: 1573-7136
DOI
https://doi.org/10.1007/s11142-013-9252-9

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