Real earnings management and the cost of new corporate bonds

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Abstract

We examine the association between real earnings management and the cost of new bond issues of U.S. corporations. We consider three types of real earnings management: sales manipulation, overproduction, and the abnormal reduction of discretionary expenditures. We find that overproduction impairs credit ratings and that sales manipulation and overproduction are associated with higher bond yield spreads. Overall, our results imply that credit rating agencies and bondholders perceive real earnings management as a credit risk-increasing factor and thus require high risk premiums.

Introduction

This paper examines the association between real earnings management (REM) and the cost of new corporate bond issues. Standard & Poor's indicates that earnings and cash flows are important financial factors for assessing a firm's creditworthiness; it also notes that a firm's profitability and ongoing earnings power are critical determinants of credit ratings (S&P, 1998). Consistent with this notion, Khurana and Raman (2003) find the bond market prices earnings-related fundamentals. However, much empirical evidence suggests that earnings management is a common phenomenon. In particular, prior literature documents that raising capital provides incentives for earnings management because managers tend to inflate earnings to reduce the risk premium (e.g., Bhojraj et al., 2009, Cohen and Zarowin, 2010, Graham et al., 2005). Managers can manage current earnings in two different ways. First, managers can exercise discretion over accrual choices that are allowed under Generally Accepted Accounting Principles to reach a desired level of earnings (referred to as accrual-based earnings management). Second, managers can manage earnings by altering the timing and scale of operating decisions. These actions deviate from normal business practices, with the primary objective of misleading stakeholders on underlying economic performance. Researchers refer to the second type as REM, or real activities management (Cohen and Zarowin, 2010, Mizik and Jacobson, 2008, Roychowdhury, 2006, Zang, 2012).

Earnings management distorts the quality of reported earnings (e.g., Chung et al., 2005, Hadani et al., 2011, Sun et al., 2011), which can impact bondholders' estimates of future cash flows. Recent research demonstrates that abnormal accruals (a measure of accounting quality or accrual-based earnings management) have a negative impact on the cost of debt (Bharath et al., 2008, Francis et al., 2005, Prevost et al., 2008). Since these studies focus on the impact of accrual-based earnings management on the interest cost of borrowing, there is little evidence on how investors in the bond market perceive REM. To fill this void, our study investigates whether potential bondholders perceive REM to be a credit risk increasing or decreasing factor. Stated another way, our analysis focuses on the hitherto unexplored question of whether bondholders require higher or lower risk premiums in response to REM.

Following recent REM studies (e.g., Cohen et al., 2008, Roychowdhury, 2006), we consider three types of REM activities: (1) sales manipulation, (2) overproduction, and (3) cutting discretionary expenses. Sales manipulation reflects managers' attempts to increase sales during the year by offering “limited-time” price discounts or more lenient credit terms. The escalated sales are likely to disappear once the firm reverts to old prices. In addition, offering more lenient credit terms, such as a longer payment period, increases a firm's risk exposure to uncollectible accounts. Sales manipulation leads to lower current-period operating cash flows for a given level of sales.

Overproduction refers to producing more goods than necessary to increase earnings. The cost of products sold appears as the cost of goods sold (COGS) in the income statement and the cost of products unsold appears as inventory in the balance sheet. By overproduction, the overhead cost spreads over more units of products, which results in lower unit cost. This allows managers to report a lower COGS given sales levels and thus increase reported earnings while leaving a substantial portion of production costs in the inventory account in the balance sheet. Earnings boosted this way are less sustainable and the excessive inventory may turn out to be obsolete so that a loss may occur in the future.

Discretionary expenses often include advertising, employee training, maintenance, and other expenses. Firms generally pay discretionary expenditures by cash. Reducing such expenditures lowers cash outflows and has a positive effect on abnormal cash flows in the current period, possibly at the risk of lower future cash flows. For example, the abnormal reduction of advertising expenses can result in lower future sales revenues and therefore lower future cash flows; an abnormal reduction of employee training expenses can hurt a firm's competitive edge in the long run.

Examining the effect of REM in the bond market is important for several reasons. First, REM appears to be a common practice. For example, the survey of Graham et al. (2005) suggests that 80% of the survey participants, executives of U.S. firms, would rather implement real economic actions that could have long-term adverse consequences than make accounting adjustments to meet short-term earnings targets.

Second, as described earlier, REM deviates from optimal business operations, hides a firm's unmanaged earnings, and can be detrimental to a firm's long-term profitability and competitive advantages (Cohen and Zarowin, 2010, Wang and D'Souza, 2006, Zang, 2012). Therefore, REM increases the information asymmetry between managers and bondholders with respect to a firm's current-period unmanaged earnings performance and thus can affect bondholders' estimates of a firm's ongoing earnings power. This information risk has a potential effect on bond pricing.

Third, bondholders have contractually fixed claims such as periodic interest payments. They tend to focus on future cash flows to ensure a firm's ability to pay interest and bond principal. Because REM can have direct negative consequences on the level of future net cash flows (Graham et al., 2005, Kim and Sohn, forthcoming, Roychowdhury, 2006), bondholders are likely to be concerned about and respond to REM activities.

Fourth, prior studies argue that REM is opaque to outside stakeholders and difficult to detect (Graham et al., 2005, Zang, 2012) because they are not subject to external monitoring and scrutiny by auditors and regulators. It is an open question whether potential bond investors perceive REM as an opportunistic behavior. Our study therefore aims to provide empirical evidence on the impact of REM on new corporate bond offerings in the U.S. market.

Section snippets

Related literature and hypothesis development

Creditors use earnings and other accounting information to assess firm health, credibility, and viability (e.g., Ederington and Yawitz, 1987, Fischer and Verrecchia, 1997, Ho and Rao, 1993, Khurana and Raman, 2003, Standard and Poor's, 1998, West, 1970). However, empirical evidence suggests that managers tend to manage earnings for their private benefit. Earnings management occurs when managers use discretion in financial reporting or structure transactions to alter financial reports either to

Models for estimating REM proxies

Roychowdhury (2006) develops empirical models to estimate the normal levels of real business activities, as reflected in cash flow from operations, production costs, and discretionary expenditures. The author uses the residuals from these models as proxies for REM. Consistent with several recent studies (e.g., Cohen and Zarowin, 2010, Cohen et al., 2008, Hong and Andersen, 2011, Zang, 2012), we use these models to construct REM measures. We use model (1) to estimate the normal level of cash

Sample selection and descriptive statistics

We obtain accounting data from Compustat. We eliminate observations with negative sales numbers or where the total assets value is zero or missing. We also exclude financial institutions (SIC codes 6000–6999) and utility industries (SIC codes 4400–4999) because these industries have different accounting rules, operating characteristics, and debt financing activities.

We obtain bond data from the 2010 version of the Mergent Fixed Income Securities Database (FISD) (data available until 2009).

Results

We estimate models (4), (5) using the ordinary least squares procedure. For all regressions, we correct the standard errors for heteroskedasticity and firm-level clustering and report the corresponding p-values.

Table 3 reports the results of model (4). Columns (1) to (3) present the results when an individual REM proxy, Ab_CFO, Ab_Prod, or Ab_Dexp, respectively, is in the model; column (4) includes all three REM variables and column (5) is the result when the comprehensive measure, RealEM,

Ordered logistic regression

In the main tests, the coding of S&P ratings ranges from one to 27. As a robustness check, we follow Ashbaugh-Skaife, Collins, and LaFond (2006) and collapse bond ratings into a seven-point scale, with 7 for an AAA rating; 6 for AA +, AA, and AA −; 5 for A +, A, and A −; 4 for BBB +, BBB, and BBB −; 3 for BB +, BB, and BB −; 2 for B +, B, and B −; and 1 for CCC +, CCC, CC, C, D, and SD. We perform an ordered logistic regression of S&P rating on the same set of explanatory variables as in model (4). The

Discussion and conclusion

Given that previous research pays little attention to the economic consequences of REM in the bond market, this study investigates the impact of REM on credit ratings and bond pricing. Using a sample of firms with new bond issues during 1993–2009, we find that overproduction impairs credit ratings. Our results also show that sales manipulation and overproduction are associated with higher bond yield spreads. Our main results are generally robust to controlling for a variety of potentially

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  • Cited by (0)

    We appreciate the helpful comments on an earlier version of this manuscript from Olubunmi Faleye (associate editor), two anonymous reviewers, Jeffrey L. Callen (University of Toronto), Art Durnev (University of Iowa), Ehsan H. Feroz (University of Washington at Tacoma), Luo He (Concordia University), Maureen Gowing (University of Windsor), Kin Lo (University of British Columbia), Janet Morris (University of Manitoba), Shahrokh Saudagaran (University of Washington at Tacoma), Zvi Singer (McGill University), Desmond Tsang (McGill University), G.A. Whitmore (McGill University), Sanjian Zhang (McGill University), and workshop participants at Concordia University, Loyola Marymount University, Michigan Technology University, McGill University, Singapore Management University, the University of British Columbia at Okanagan, the University of Manitoba, the University of Ottawa, the University of Saskatchewan, the University of Washington at Tacoma, the University of Windsor, and the 2010 CAAA Annual Conference. W. Ge acknowledges funding support from the Institute of Chartered Accountants of Manitoba and from the University of Manitoba start-up grant.

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