Do Acquiring Firms Manage Earnings?

Do Acquiring Firms Manage Earnings? Raunaq S. Pungaliya and Anand M. Vijh *

Abstract This paper re-examines the evidence in favor of earnings management before merger and acquisition announcements documented by Erickson and Wang (1999), Louis (2004), Baik, Kang, and Morton (2007), Botsari and Meeks (2008), and Gong, Louis, and Sun (2008b), and it finds evidence to the contrary. We argue that the results of these studies can be explained by an incomplete specification of the quarterly discretionary accruals model, which arises from not adjusting for cross-sectional differences in the long-term sales growth rates of acquirer firms. Incorporating this sales growth factor leads to insignificant differences between discretionary accruals of cash versus stock acquirers, and across stock acquisitions of relatively small versus large targets (with different economic incentives for earnings management). In an interesting reversal of the experiment, we find that acquirer firms in the decile of most negative discretionary accruals are about as likely to choose stock payment (instead of cash payment) as acquirer firms in the decile of most positive discretionary accruals.

August 2008

*

Tippie College of Business, The University of Iowa, Iowa City, IA 52242-1994. Email: [email protected] and [email protected].

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Do Acquiring Firms Manage Earnings? I. Introduction Mergers and acquisitions are important events associated with the creation, destruction, and redistribution of shareholder wealth. Previous literature documents negative announcement and long-term returns earned by acquirer firms that use stock payment.1 This points to the potential overvaluation of acquirer stock which is not fully corrected on the announcement date. The overvaluation may stem from an irrational assessment of the firm’s future prospects by investors, as modeled by Shleifer and Vishny (2003), or an intentional misleading by the firm’s managers in the form of earnings management. Erickson and Wang (1999), Louis (2004), Baik, Kang, and Morton (2007), Botsari and Meeks (2008), and Gong, Louis, and Sun (2008b) examine the discretionary accruals of acquiring firms and find them to be significantly higher in stock acquisitions (where there is an incentive to inflate stock prices) than in cash acquisitions (where there is no such incentive). Thus, they conclude that stock acquisitions are preceded by earnings management. This paper re-examines their evidence with a comprehensive sample of 3,135 cash and stock acquisitions during 1989 to 2005 and concludes the opposite. There are numerous reports of earnings management (and even accounting fraud) both in the popular press and the accounting literature, so the existence of earnings management per se is not disputable.2 Burgstahler and Dichev (1997) and Degeorge, Patel, and Zeckhauser (1999) examine the incidence of earnings management without any corporate event and find that firms manage earnings to exceed three different thresholds: report positive profits, sustain recent performance, and meet analysts’ expectations. Their evidence is based on the simple distribution of earnings, which tends to cluster unreasonably around these thresholds. In the context of corporate events, however, the evidence on earnings management is usually based on the magnitude of discretionary accruals. The most extensive evidence documented to date is in the context of equity issues, which take the form of stock acquisitions, initial public offerings (IPOs) and seasoned equity offerings (SEOs), and stock repurchases (which can be 1

See Andrade, Mitchell, and Stafford (2001) for evidence on announcement-period returns, and Loughran and Vijh (1997), Rau and Vermaelen (1998), and Agrawal and Jaffe (2000) for evidence on long-term returns. 2 Earnings management refers to inflating or deflating accruals and charges within generally accepted accounting principles (GAAP), whereas accounting fraud refers to misreporting accounting numbers outside GAAP.

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thought of as negative equity issues). Besides the evidence on stock acquisitions mentioned above, Teoh, Welch, and Wong (1998) document that firms manage accruals to increase their earnings before SEOs, in an apparent effort to boost their stock price, while Gong, Louis, and Sun (2008a) document that firms decrease their earnings before stock repurchases, in an effort to suppress their stock price. There are several reasons that prompt us to re-examine the results of previous studies of earnings management through accrual inflation by stock acquirers. First, stock acquisitions involve shareholders of two firms with opposite outcomes. The target shareholders have their managers to protect their interests, and those managers hire investment bankers to render an opinion on the fair value of the stock offer. The prior literature assumes that both the target managers and investment bankers cannot detect earnings management, or that they can be influenced into making a recommendation that is not in the interests of their shareholders. Regarding the first assumption, if academic researchers can mechanically detect earnings management in broad samples, then it is not entirely clear why the target managers and investment bankers with greater access to firm specific information cannot do the same. Regarding the second assumption, there is some supporting evidence in the case of public targets. Hartzell, Ofek, and Yermack (2004) show that target managers are given merger bonuses and lucrative post-acquisition contracts, while Cai and Vijh (2007) show that target managers may be motivated to cash out of their illiquid stock and option holdings. However, there is no such influence in the case of private targets where presumably the interests of shareholders and managers are aligned. Yet, Baik, Kang, and Morton (2007) report stronger evidence of earnings management in the case of private targets than in the case of public targets. We replicate their result using extant methodology and find it to be perplexing. A second doubt on the existence of earnings management in stock acquisitions is cast by the contrasting results for targets and acquirers. Erickson and Wang (1999) and Louis (2004) find significant evidence of earnings management by acquiring firms, but no evidence of earnings management by their publicly-traded target firms. This seems odd since the target firms have as much control over the acquisition process and their incentive to boost their stock price by inflating accruals is at least as strong, if not stronger. If we consider earnings management to be a strategic game between targets and acquirers, where the players choose between playing fair (i.e., not managing earnings) and cheating (i.e., managing

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earnings), then the targets play a one-shot end-game as they cease to exist after the acquisition. They have no reputational effects to consider, and no penalties to fear as currently inflated accruals deflate at some time in future. In contrast, the acquirers are likely to be playing a repeat game, so their reputational effects are more important. The eventual deflation of their accruals and the accompanying market penalty of lower stock prices could be serious considerations reducing the wealth of acquirer shareholders in the long run. The findings of stronger earnings management by stock acquirers of private targets and no earnings management by public targets among other reasons raise the possibility that the results may be driven by an error in measuring accruals, or a misspecification of the discretionary accruals model. The first effect has been documented by Hribar and Collins (2002). They show that the traditional balance sheet measures used by most of the existing literature are biased in the presence of prior mergers and acquisitions (besides other non-operating events such as divestitures and foreign currency translations). These events affect the current assets and liabilities recorded on the balance sheet of sample firms, but do not affect the income statement. It is possible that some of the differences between balance sheet accruals of cash versus stock acquirers, or targets versus acquirers, in existing literature are driven by differences in the frequency of prior non-operating events.3 We document a second effect, which is the misspecification of the discretionary accruals model used in the extant literature. The quarterly Jones model used in the literature controls for the effect of quarterly sales changes on accruals but does not account for the effect of long term sales growth. Accounting for the impact of growth on accrual estimates is essential as firms with strong prior growth and expectations of future growth are likely to make different working capital decisions (McNichols (2000)). We argue that this becomes especially important in the context of mergers and acquisitions since cash acquirers and stock acquirers differ markedly in their annual sales growth (12.1% versus 41.1%). We show that performance matching using ROA alone does not adequately control for the effect of extreme performance on quarterly accrual estimates. This result is consistent with McNichols (2000) who shows 3

Note, however, that Botsari and Meeks (2008) report results using both the balance sheet and cash flow method, while Gong, Louis, and Sun (2008b) report that their inferences based on the balance sheet method do not change with the cash flow method.

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that both growth and ROA are strongly correlated with residuals from the Jones model in the presence of each other. Our results add to a growing literature that questions the reliability of discretionary accrual estimates for firms experiencing rapid growth (Dechow, Sloan, and Sweeney (1995), Kaznik (1999), McNichols (2000), Kothari, Leone, and Wasley (2005), and Ball and Shivakumar (2008)). Our detailed results are as follows. First, we replicate results shown in the extant literature and document that current accruals computed using the traditional balance sheet method and ROA adjustment are significantly positive and greater for stock acquirers than for cash acquirers. This evidence holds over a three-quarter period centered on the quarter of earnings announcement immediately preceding the merger announcement. The results are stronger for acquirers of private targets than public targets, and become largely insignificant if the measure of accruals is changed to total accruals computed using the cash flow method. So we investigate further. We arrange all firms in our merger sample into deciles formed by long-term sales growth rate, measured by the growth over a four-quarter period ending before the merger announcement. The first important inference is that half of all stock acquirers belong to the highest decile of sales growth rate computed for all NYSE firms. The second inference is that after adjusting for the effect of sales growth the difference between discretionary accruals for cash acquirers and stock acquirers disappears. We next examine whether the sales growth effect is more general and not restricted to the event sample by documenting ROA adjusted discretionary accruals across decile portfolios of all Compustat firm-quarters. The results are startling. The rank correlation between sales growth decile and ROA adjusted quarterly discretionary accruals equals one, and the slope coefficient indicates an increase of about 0.13 in discretionary accruals (normalized by lagged total assets) with each decile of sales growth. We argue that this makes it necessary to design a procedure to adjust for the effect of long-term sales growth on discretionary accruals. We propose extending the Kothari, Leone, and Wasley (2005) matching-firm procedure to incorporate both ROA and sales growth. This procedure works well on the decile portfolios of all Compustat firm-quarters, producing rank correlations and slope coefficients that are close to zero. It also produces discretionary accruals for stock acquirers that are insignificantly different from zero or the corresponding numbers for cash acquirers.

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While there is no evidence on earnings management in the aggregate sample of cash and stock acquirers, a question arises whether there is still some evidence in subsets characterized by a stronger incentive for earnings management. The most obvious proxy for incentives is the relative size of the target to that of the acquirer. Surprisingly, however, we find even weaker evidence for earnings management in the subset of acquisitions with above-median relative size. We next examine whether there is any relation between the magnitude of discretionary accruals and the excess stock returns around the corresponding earnings announcement. We find that the two are uncorrelated. Apparently, the market is unimpressed by the discretionary accruals part of earnings announcements. In the last part of our investigation we present evidence that raises strong doubts whether the discretionary accruals – ROA adjusted or ROA and sales growth adjusted – were ever intended to expropriate wealth from target to acquirer shareholders. If they were, then we would expect a positive relation between discretionary accruals and the probability that an acquiring firm would choose stock payment rather than cash payment. Surprisingly, however, we find a strong U-shape relation between the accrual decile rank and the percent frequency of stock payment. In other words, acquirer firms in the decile of most negative discretionary accruals are about as likely to choose stock payment (instead of cash payment) as acquirer firms in the decile of most positive discretionary accruals. The cumulative evidence presented in this paper is inconsistent with the conclusions of Erickson and Wang (1999), Louis (2004), Baik, Kang, and Morton (2007), Botsari and Meeks (2008), and Gong, Louis, and Sun (2008b). We emphasize that our results are robust to using current accruals or total accruals, and balance sheet or cash flow methods. Of course, this does not eliminate the possibility that there may be earnings management in isolated cases, or that a more sophisticated investigation of other accounting items may produce such evidence in a broad sample of firms. The remaining paper proceeds as follows. Section II discusses the accrual measures in detail, and Section III describes the data sources. Section IV presents the main results relating to measures and the evidence within aggregate samples. Section V presents additional results that are inconsistent with earnings management by stock acquirers, and Section VI concludes.

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II. Measures of earnings management The choice between current and total accruals is somewhat arbitrary in previous literature. Louis (2004) argues that investment bankers in mergers and acquisitions rely on EBITDA (earnings before interest, taxes, depreciation, and amortization) in their valuation, so acquiring firms are more likely to manipulate current accruals that exclude depreciation. However, in the context of IPOs, Teoh, Wong, and Rao (1998) document that issuing firms are more likely to choose income-increasing depreciation policies relative to their matched firms. Further, while depreciation is the largest non-current accrual, there are other non-current accruals that may also be manipulated (such as deferred taxes, restructuring charges, and special items).4 Thus, it can be argued that the total accruals are a more complete starting point for detecting earnings management. In a similar spirit, Richardson et al. (2005) argue that the power of accruals-based tests of earnings management can be improved by using a more comprehensive measure of accruals (total accruals) rather than a narrow one (current accruals). Many studies (such as Louis (2004) and Gong, Louis, and Sun (2008a, 2008b)) estimate current accruals using successive balance sheet statements as follows: (1)

Here, CA is the change in current assets (Compustat quarterly item 40), liabilities (item 49),

is the change in cash and cash equivalents (item 36),

is the change in current is the change

in current maturities of long-term debt and other short-term debt included in current liabilities during period t under consideration (item 45). When measured using the balance sheet, total accruals further account for depreciation as follows: (2)

Here, DEP is the depreciation expense during period t. For comparison across firms, each variable in Equations (1) and (2) is scaled by the lagged total assets (i.e., assets as of the last quarter end).

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In the context of earnings management to meet thresholds, Phillips, Pincus, and Rego (2003) show that some firms manipulate deferred tax expense, while Moehrle (2002) shows that others manipulate restructuring charges.

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Hribar and Collins (2002) demonstrate that measuring accruals using the balance sheet results in a significantly biased estimate in the presence of non-operating events such as mergers and acquisitions, divestitures, and foreign currency translations. These events affect the balance sheet with no corresponding impact on earnings as changes in current assets and liabilities do not flow through the income statement. This is relevant in our study as accrual estimates from working capital accounts on the balance sheet may be contaminated with changes related to prior merger and acquisitions, which are frequent for the sample of current acquirers. Hribar and Collins (2002) therefore recommend computing total accruals directly from the cash flow statement as it does not suffer from the above bias. Under this method, total accruals are computed, quite intuitively, as the difference between earnings before extraordinary items and discontinued operations (Compustat quarterly item 76) and operating cash flows (item 108 – item 78): (3)

Unlike a total accrual measure computed from the balance sheet in Equation (2), the total accrual measure computed from the cash flow statement in Equation (3) naturally includes non-current accruals besides depreciation as mentioned above. In order to maintain comparability and contrast with previous literature, we report results with current accruals computed using the balance sheet in all our tables. In addition, given the Hribar and Collins (2002) and Richardson et al. (2005) criticisms, we report results for total accruals computed using the cash flow statement. However, we do not report current accruals using the cash flow statement as the corresponding data are missing in a large majority of cases. We also do not report total accruals using the balance sheet as they are clearly dominated by the total accruals using the cash flow statement that are available in nearly as many cases. For easier exposition, we refer to simply current accruals and total accruals in the following discussion.

and

as

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B. Separating accruals into discretionary and nondiscretionary components: The modified Jones model with quarterly data We follow the prior literature on earnings management in the context of mergers and acquisitions (Erickson and Wang (1999), Louis (2004), Baik, Kang, and Morton (2007), Gong, Louis, and Sun (2008b)) and derive a measure of discretionary accruals from a modified Jones (1991) model applied to quarterly data. Specifically, we follow the procedure in Gong, Louis, and Sun to separate the current accruals into discretionary and nondiscretionary components as below:

(4)

This is a cross-sectional regression estimated over all Compustat firms i belonging to the same two-digit SIC (standard industry classification) code as the sample acquirer firm during the current quarter t.5 However, for easier exposition, the subscript t is dropped from all variables. We use a parallel procedure to compute discretionary total accruals:

(5)

In both regressions, Q1,i  Q4,i are fiscal quarter dummies included to account for seasonality, the change in sales since last quarter (item 2), quarter (item 37),

(

is

is the change in accounts receivables since the last ) is the accrual from four quarters before the

current quarter, and PPEi is the property, plant, and equipment during the current quarter (item 42). As before, all variables are scaled by lagged total assets. The discretionary accruals are obtained as residuals from Equations (4) and (5) for the sample firm. Finally, following the methodology outlined in Louis (2004), Kothari, Leone, and Wasley (2005), and Gong, Louis, and Sun (2008a, 2008b), we performance-adjust the discretionary accruals. This

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We require at least 20 observations for each separate regression by calendar quarter and 2-digit SIC industry code. We winsorize several variables at the one-percentile level (accruals, change in sales, change in accounts receivable, and PPE) that are used in the Jones model. Following Louis (2004) and Kothari et al. (2005), we discard untenable observations where the absolute value of accruals scaled by total assets are greater than 1.

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involves computing the difference between discretionary accrual for the sample firm and the median discretionary accrual for the quintile of same-industry firms matched by ROA (return on assets) from the same quarter in the previous year. We refer to this final statistic as ROA adjusted discretionary accrual. It constitutes the starting measure of earnings management in our study. Using simulations, Kothari, Leone, and Wasley (2005) argue that the ROA adjusted discretionary accruals have an expected median value close to zero. Thus, in all our tests, we report the median values of performance-adjusted discretionary accruals calculated using the balance sheet method and the cash flow method and the corresponding p-values using the Wilcoxon sign-rank test. Further, in regression tests that use the discretionary accrual for each firm we winsorize this variable at the one-percentile level.

III. Data sources A. Sample of acquisitions Our comprehensive sample includes all acquisitions from the Securities Data Company (SDC) database that meet the following criteria: 1. The acquisition is announced during January 1989 to December 2005. (We start in 1989 since this is the first year when U.S. firms were required to file a cash flow statement.) 2. The target is a public, private, or subsidiary firm domiciled in the U.S. 3. The acquirer is a public firm included in The Center for Research in Security Prices (CRSP) and Compustat databases with ordinary common shares outstanding (CRSP share code 10 or 11, which excludes American Depository Receipts (ADRs), Real Estate Investment Trusts (REITs), units, certificates, and trusts). 4. The acquirer is not a financial firm. 5. The transaction value exceeds $10 million. 6. The transaction form is categorized as deal type 1 (disclosed value mergers and acquisitions). 7. The acquirer owns less than 50% of target shares before announcement and 100% of target shares after completion. 8. The form of payment is all cash or all stock (thus, mixed payment cases are excluded). 9. The acquirer has relevant data on Compustat quarterly file to calculate the performance-adjusted discretionary accruals using both the balance sheet and cash flow methods (as described in Section II). We obtain the transaction value from the SDC and the acquirer total assets and market value from Compustat as of the last quarter-end. We calculate relative size of the deal as the transaction value divided

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by the acquirer market value, the acquirer book-to-market value as the book value divided by the market value of equity, and the acquirer return on assets as the net income divided by total assets. The prior-year market-adjusted excess returns are calculated by subtracting the cumulative market returns from the cumulative stock returns over a 254-day period ending on MAD-2 (where MAD denotes the merger announcement date). B. Sample description Table 1 lists descriptive statistics for the acquisition sample. Panel A shows that the final sample includes acquisitions of 866 public targets, 1,337 private targets, and 932 subsidiary targets, for a total of 3,135 deals. Of these, 1,998 are cash acquisitions and 1,137 are stock acquisitions. To our knowledge, this is the most comprehensive sample used to study earnings management around mergers and acquisitions. Panel B of Table 1 reveals many systematic differences across target types. First, not surprisingly, private targets are sought by smaller acquirers, while public targets are sought by larger acquirers. Second, for any target type, cash acquisitions are made by bigger firms than stock acquisitions. Third, as we later argue, relative size is a more relevant criterion than absolute size for earnings management, and it is the smallest for private targets and the largest for public targets. Fourth, stock acquirers tend to have lower book-to-market values than cash acquirers for all target types, while the prior-year market-adjusted excess returns show the opposite pattern. This evidence is consistent with the Shleifer and Vishny (2003) hypothesis that market sometimes overprices certain stocks and managers respond rationally by making stock acquisitions. Fifth, and perhaps the most relevant to the subsequent tests in our study, cash acquirers have much lower annual sales growth rates than stock acquirers (computed as sales for quarter t-1 divided by sales for quarter t-5, where t-1 is the fiscal quarter with the last earnings announcement date (EAD) before the merger announcement date (MAD)). The median sales growth rates for cash and stock acquirers equal 12.1% and 41.1% in the aggregate sample, and a similar difference is observed across subsets formed by public, private, and subsidiary targets. Panel C shows a strong calendar pattern in the relative numbers of stock and cash acquisitions. For example, while the numbers are fairly comparable during 1995-2000, a period characterized by rich

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stock valuations, there are very few stock acquisitions during 2002-2005, a period characterized by poor stock valuations. Given that earnings management makes sense only for stock acquisitions, one might ask whether there is a parallel calendar-time pattern in earnings management by domestic firms. However, we are not aware of any study that documents such patterns.

IV. Main results A. Traditional measures of earnings management preceding cash and stock acquisitions Traditional tests of earnings management check whether stock acquirers have significantly greater discretionary accruals in the quarter preceding the merger announcement (Erickson and Wang (1999), Louis (2004), Baik, Kang, and Morton (2007), and Botsari and Meeks (2008)). Clearly, if increasing bottom line earnings via accrual management sustains or increases acquirer stock price, then an acquisition financed by a stock swap would result in an expropriation of wealth from the target shareholders to the acquirer shareholders. Thus, it is argued by these studies that a strategic intent to manage earnings by inflating accruals exists in the case of stock acquisitions but not in the case of cash acquisitions. However, in order for this intent to manifest into action, certain additional conditions would have to be met. First, it must be assumed that the acquirer managers know as of last quarter (if not earlier) that with a high probability they would be able to acquire a target firm, and that the target shareholders would accept stock payment. Second, it must be assumed that the target shareholders, managers, and investment bankers would not detect earnings management, or that if they do detect earnings management, then they somehow would be influenced into making a recommendation that is not in the interests of shareholders. Neither of these conditions is clearly feasible or clearly infeasible, so earnings management becomes an empirical issue. Table 2 lists performance-adjusted discretionary accruals for acquirer firms as of quarters t-2, t-1, and t, where quarter t-1 is the fiscal quarter with the last earnings announcement date (EAD) before the merger announcement date (MAD). Previous literature finds strong evidence of earnings management during quarter t-1. In addition, the examination of quarter t-2 is necessary since there must be some uncertainty about when a merger would be announced. Further, Erickson and Wang (1999) suggest that

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the incentive to manage earnings does not disappear during the following quarters with earnings announcement dates preceding the merger completion date. In fact, one may argue that the acquirers would be even more motivated to manage earnings during the following quarters in order to support stock prices after having made a stock offer. We therefore examine the discretionary accruals during quarter t for the roughly 60% of cases where the merger is not completed by the corresponding earnings announcement date. Panel A of Table 2 presents results based on accruals calculated using the balance sheet method. These results are broadly consistent with earnings management as in previous literature. First, in the aggregate sample of all acquisitions, the stock acquirers have median discretionary current accruals of 0.419% during quarter t-1, compared to 0.082% for cash acquirers. The difference between medians equals 0.337%, with a Wilcoxon p-value of 0.001. To understand the economic significance of these numbers, note that the median quarterly return on assets is the order of 1.65% for all acquirers. The results are also highly significant for quarters t-2 and t, which cumulatively paint a picture of strong earnings management in the aggregate sample of all acquirers. Second, looking across subsets, there is even stronger evidence of earnings management by stock acquirers of private targets, while there is less significant evidence for stock acquirers of public targets. This supports the results of Baik, Kang, and Morton (2007). However, it is surprising because the median relative size in Table 1 is much smaller for private targets than for public targets (hence a lower incentive), and because there is little or no divergence between manager and shareholder interests of private targets (hence a lower ability). Third, given the relatively low numbers of stock acquisitions of subsidiary targets, the evidence is in the direction of earnings management by stock acquirers, but statistically insignificant. Panel B of Table 2 shows that the evidence is not robust to discretionary total accruals computed using the cash flow statement. For the aggregate sample and the subset of public targets, the difference between total accruals of stock acquirers and cash acquirers is insignificant during all three quarters. For the subsets of private and subsidiary targets, the evidence is equally insignificant during quarters t-2 and t-1. However, during quarter t, the difference is positive and significant for private targets, while it is negative and significant for subsidiary targets.

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The overall inference from Table 2 is mixed. While current accruals computed using the balance sheet method provide significant evidence in favor of earnings management, the total accruals computed using the cash flow method do not support this inference. The difference could be driven by a higher frequency of prior acquisitions during a one-year period ending with quarter t-1 for stock acquirers compared to cash acquirers (following Hribar and Collins (2002)), or an omitted variable that influences discretionary accruals, which is explored below. B. The impact of annual sales growth on discretionary accruals of stock versus cash acquirers B.1. Discussion and preliminary tests Any test of earnings management that uses discretionary accruals is also a joint test of the discretionary accrual model. As a result, the specification of the discretionary accrual model assumes critical importance in making unbiased inferences. Several studies have questioned the Jones model and found it to be misspecified for firms experiencing extreme performance. For example, Dechow, Sloan, and Sweeney (1995) show that Jones-type models over-reject the null hypothesis of no earnings management in firms with extreme financial performance, and Kaznik (1999) shows that the estimated discretionary accruals are correlated with current ROA. For such reasons, Kothari, Leone, and Wasley (2005) show that performance matching on ROA improves the reliability of earnings management tests. However, McNichols (2000) shows that both growth and ROA are highly correlated with discretionary accruals in the presence of each other. Thus, matching by ROA alone as suggested by Kothari, Leone, and Wasley (2005) and used in Louis (2004), Gong, Louis, and Sun (2008a, 2008b), and our Table 2 may not be adequate.6 The stark difference between the annual sales growth rates of cash and stock acquirers at 12.1% and 41.1% as shown in Table 1 increases the concern that these results may be biased. An investigation of the role of sales growth in discretionary accruals starts with a measure of this variable. Notice the modified Jones model applied to quarterly data as described by Equations (4) and (5) includes the changes in quarterly sales changes as an explanatory variable. However, this short-term

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Kothari, Leone, and Wasley (2005) acknowledge matching by past sales growth as an alternative to matching by ROA, but they settle on the latter by arguing that it incorporates ‘other factors contributing to the firm’s accrual generating process… that are likely to affect the magnitude of nondiscretionary accruals’ (footnote 5, page 169).

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growth measure may be noisy and may not capture the long-term trend in sales growth. In addition, it may be confounded with the effect of seasonality, which is quite distinct from growth. We therefore measure the long-term sales growth by the annual growth rate from quarter t-5 to t-17. We next form sales growth decile portfolios by following a procedure similar to the Fama-French procedure of forming size and book-to-market portfolios. Specifically, we compute annual sales growth rate for all NYSE firms during each calendar quarter with available data to ascertain the sales growth decile cutoffs. Using these cutoffs we assign an annual sales growth decile rank to all cash and stock acquirers. Panel A of Table 3 reports median ROA adjusted discretionary accrual estimates during quarter t-1 for our sample of acquisitions arranged by the annual sales growth decile and payment method. The importance of sales growth on payment method is highlighted by the fact that approximately half of all stock acquirers belong to the highest sales growth decile. Further, we notice a strong positive correlation between discretionary accruals and annual sales growth rate. For cash acquirers, the rank correlation equals 0.903 with current accruals and 0.915 with total accruals, both significant at the 1% level. For stock acquirers, the corresponding rank correlations equal 0.661 and 0.345, significant in the former case at the 5% level. Weaker correlations with stock acquirers may be the result of a smaller number of observations in decile ranks below 9. More importantly, although not shown in the table, the difference between either measure of discretionary accruals for cash and stock acquirers is about as likely to be positive as negative for a given sales growth decile rank. This provides one piece of evidence that after controlling for sales growth the discretionary accruals for cash and stock acquirers are not different. Panel B of Table 3 carries this analysis further with regressions. Models (1) to (3) use the current accruals computed using the balance sheet method as the dependent variable, and models (4) to (6) use the total accruals computed using the cash flow method. Models (1) and (4) report a univariate regression on stock payment dummy, which is significant at the 1% level in the first case and insignificant in the second case. Models (2) and (5) add the sales growth decile rank, which is highly significant by itself. More importantly, it makes the stock payment dummy insignificant in the first case and significantly negative in 7

Alternately, one could use IBES estimates of long run growth in earnings as used by McNichols (2000). However, using IBES data would limit the sample size and introduce issues of stale forecasts as the analysis in this paper is conducted at a quarterly frequency.

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the second case. The last result is somewhat surprising since there is no reason why the total accruals computed using the cash flow method should be negative for stock acquirers. While this may point to the fragility of making inferences about earnings management by using accrual models, we conjecture that there may be another reason related to over-adjustment. To understand this, notice that the sales growth may be organic (i.e., from existing business), or driven by prior acquisitions. While both types of sales growth increase the current accruals computed using the balance sheet method, only the organic growth increases the total accruals computed using the cash flow method. Models (3) and (6) test this conjecture by including a prior acquisition dummy that equals one if there was another acquisition during a one-year period ending with quarter t-1, and zero otherwise8. We also include an interaction term between this dummy and the sales growth decile rank. We find that both the prior acquisition dummy and its interaction term are insignificant in the regression of current accruals computed using the balance sheet method. However, the interaction term is significantly negative in the regression of total accruals computed using the cash flow method, and at the same time the stock payment dummy becomes insignificant. This simultaneously points to some possibility of over-adjustment in the case of cash flow method and upholds the insignificance of stock payment dummy as a determinant of discretionary accruals in the presence of other relevant variables. The concern is not too strong, however, as the sales growth decile rank remains the most significant variable by far. B.2. Improved measures of discretionary accruals Table 3 shows that the quarterly discretionary accrual model used in extant literature is misspecified as it suffers from an omitted variable bias induced by the annual sales growth. As the omitted variable has been identified and can be easily computed, one solution is to add it to the list of explanatory variables in the Jones model. However, we lack a clear theory that suggests a linear relationship between annual sales growth and quarterly accruals. In fact, our subsequent analysis shows that this relationship is quite nonlinear.

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The prior acquisition dummy (PA) is coded based on information contained in Compustat quarterly footnote 1and the acquisitions line in the cash flow statement.

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In a parallel context, Kothari, Leone, and Wasley (2005) adjust for nonlinearity in the relationship between discretionary accruals and ROA by using a matched firm approach. Using extensive simulations, they demonstrate that the matched firm approach works better than the linear regression approach. Arguably, both ROA and annual sales growth are performance attributes. We therefore extend their procedure to mitigate the effect of annual sales growth. Specifically, we propose that the performance matching procedure should consider both ROA and annual sales growth. The extant matching procedure creates five portfolios by sorting observations into quintiles based on their ROA in the same quarter in the previous year. The performance matched discretionary accrual is then computed as the difference between the discretionary accrual for the sample firm and the median discretionary accrual of the matched portfolio (excluding the sample firm). We modify this extant procedure by creating terciles based on annual sales growth within each ROA quintile for each industryquarter. Thus, in addition to being in the same ROA quintile, we require that firms in the matched portfolio be in the same annual sales growth tercile.9 This modification to the matching procedure should help in controlling for the effect of annual sales growth on accruals. We next proceed to test the procedure on portfolios for which there is no reason to believe that there is earnings management in either direction. Quite simply, these portfolios include all Compustat firm-quarters arranged into annual sales growth decile following the Fama-French procedure. Table 4 shows the results. The rank correlation between sales growth decile and the discretionary current accruals or total accruals computed using the extant ROA adjusted benchmarks is a perfect 1.000 in both cases. This correlation drops to an insignificant 0.042 for current accruals and -0.067 for total accruals using the proposed ROA and sales growth adjusted benchmarks. Figure 1 graphically depicts the results of Table 4. The left panel examines current accruals, and the right panel examines total accruals. As suspected, the relationship between the sales growth decile rank and discretionary accruals computed using ROA adjusted benchmarks is quite steep, but also nonlinear. In particular, the accruals are large negative in the lowest sales growth decile and large positive 9

The construction of terciles based on annual sales growth rather than quartiles or quintiles is an empirical choice necessitated due to sample size restrictions.

17

in the highest sales growth decile. The relationship becomes quite flat when the discretionary accruals are computed using ROA and sales growth adjusted benchmarks. To understand the magnitude effects, we revert to Table 4. A linear fit (despite its limitations) has a slope in the range of 0.11 to 0.14 with ROA adjusted benchmarks and around 0.01 with ROA and sales growth adjusted benchmarks. Overall, Table 4 and Figure 1 point to the effectiveness of our methodology, especially when a sample is partitioned by a variable correlated with the long-term sales growth rate.10 B.3. Do acquiring firms manage earnings? Evidence based on improved measures of discretionary accruals Table 5 lists ROA and sales-growth adjusted discretionary accruals for acquiring firms as of quarters t-2, t-1, and t. We find no evidence that stock acquirers engage in accrual manipulation prior to an acquisition. These results are in stark contrast with those presented by Erickson and Wang (1999), Louis (2004), and Botsari and Meeks (2008). Eleven out of 12 differences between cash and stock acquirers presented in the right-most column of this table are insignificant, while one is significant in the opposite direction at the 5% significance level. This is roughly what one would expect by chance. Henceforth, discretionary current accruals refers to ROA and sales growth adjusted discretionary current accruals where the current accruals themselves are computed using the balance sheet. Similarly, discretionary total accruals refers to ROA and annual sales growth adjusted discretionary total accruals where the total accruals themselves are computed using the cash flow statement. C. Depreciation policy and allowance for uncollectible accounts receivable Tests of earnings management using discretionary current or total accruals lump various accruals together. While comprehensive, they do not explain how earnings are managed through specific accruals (McNichols and Wilson (1988)). In addition, the Jones-type models and matched-firm controls cannot perfectly identify the discretionary component of aggregated accruals. Thus, one can obtain greater insight to earnings management by examining the components of accruals. For example, Marquardt and Wiedman 10

A full illustration of the robustness of our methodology on portfolios partitioned by other variables of interest (such as size, book-to-market, and earnings to price) is beyond the scope of this paper, but it is the subject of continuing research.

18

(2004) find that firms issuing equity have abnormally high levels of accounts receivable, while firms involved in management buyouts have abnormally low levels of accounts receivable. Similarly, Teoh, Wong, and Rao (1998) find that IPO firms adopt more income-increasing depreciation policies and have significantly smaller provisions for uncollectible accounts receivable (bad debts) than non-issuers. We now examine whether acquiring firms also strategically modify their depreciation policy or their allowance for uncollectible accounts in comparison with matched non-acquiring firms. Our matching procedure is as follows. We first restrict the matches to be in the same 2-digit industry and ROA quintile in quarter t-5. The matched firm is then defined from this group as the firm that is the closest to the acquirer in terms of annual sales growth. To identify possible understatement of depreciation expense, we follow Teoh, Wong, and Rao (1998) and group depreciation policy into three categories: accelerated, straight line, and a combination of the two.11 Straight line is the most income increasing, followed by the combination and accelerated methods. The income increasing (decreasing) group contains any case where the acquiring firm uses a more (less) income increasing method relative to the matched firm. The equivalent group contains cases where both the acquirer and matched firm lie in the same depreciation category. The Z-statistics are computed by comparing the frequency of income-increasing cases with income-decreasing cases and ignoring the equivalent cases. Panel A of Table 6 shows that about 80% of acquiring firms have depreciation policy equivalent to that of their matched firm in the year before acquisition. More significantly, the proportion of acquirer firms that adopt an income-increasing deprecation policy relative to their matched firms is not significantly different from the proportion that adopt an income-decreasing depreciation policy. This result differs from the Teoh, Wong, and Rao (1998) result that IPO firms are more aggressive in their depreciation policy. Next, Panel B of Table 6 compares the provision for uncollectible accounts receivable (Compustat annual item 67) as a fraction of total accounts receivable (item 2) for the sample and matched firms. Once again, the differences are insignificant, in contrast with the corresponding results for IPO

11

As in Teoh, Wong, and Rao (1998), depreciation policy is coded using Compustat annual footnote 15.

19

firms. Overall, the evidence continues to discount the possibility of earnings management by acquiring firms.

V. Additional tests of earnings management A. Are relatively large acquisitions preceded by higher discretionary accruals as predicted by the incentives theory of earnings management? The preceding tests find no evidence of earnings management in the aggregate sample of stock acquirers. However, they leave open the possibility that there may be earnings management in subsamples characterized by a stronger potential for wealth expropriation from the target shareholders to the acquirer shareholders. Intuitively, the most natural proxy for such potential should be the relative size of the deal. We formalize this intuition in Appendix 1 and show that the wealth transfer equals

, where f

is the percent overvaluation of the acquirer stock caused by earnings management. For a fixed percent overvaluation, this expression shows that the wealth expropriation increases with Relative Size, defined as the ratio of the observed market values of target and acquirer firms. Thus, as expected, acquisitions with a large relative size offer a greater incentive for earnings management. In previous literature, Erickson and Wang (1999) show that earnings management is increasing with relative size in their sample of public targets while Louis (2004) finds no such relation in his sample of public targets. In contrast, Baik, Kang, and Morton (2007) find that earnings management is increasing with decreasing relative size in their sample of private targets. They argue that a smaller private target poses a greater information asymmetry problem to an acquirer, which in turn takes pre-emptive action of boosting its stock price by inflating the accruals still further. Their evidence is opposite to the theory model presented in Appendix A as well as the evidence of Erickson and Wang with a different sample. A possible resolution to this contrast may emerge when we examine the magnitude of potential wealth expropriation, a variable that has not been examined in the previous literature. We arrange all acquisitions into deciles based on relative size in Table 7. Panel A presents the evidence for all targets, and Panel B presents the evidence for public targets. Each panel reports the median relative size, the median wealth transfer to acquirer shareholders assuming a fixed f = 15%

20

overvaluation of the acquiring firm’s stock price as a result of earnings management and the median discretionary current and total accruals computed using the balance sheet and the cash flow statement respectively. The choice of 15% overvaluation is somewhat arbitrary, but is likely to be a generous estimate of the stock price overvaluation in the aggregate sample. (We specifically examine the magnitude of this overvaluation in the next table.) In the broad cross-section of acquisitions, we find that many targets are of trivial size relative to acquirer. In deciles 1 to 5, the median relative size equals 0.029 for the entire sample and 0.039 when the sample is restricted to public targets. Even assuming an optimistic overvaluation of 15%, the median wealth transfer equals 0.4% of the acquirer stock price for all targets and 0.6% for public targets. Oddly, however, the median discretionary accruals are higher for deciles 1 to 5 compared to deciles 6 to 10 (although both are insignificant). Alternately, the rank correlation between discretionary accruals and relative size decile is close to zero for the aggregate sample. These results are exacerbated for the subset of public targets, but remain statistically insignificant in the opposite direction. In short, if there is earnings management intended to expropriate wealth from target shareholders to acquirer shareholders, it is not related to the most obvious proxy for the underlying incentive effects. It does not show up even in the subset of data where the incentives are stronger. This casts further doubt on the existence of opportunistic accrual management in the anticipation of mergers and acquisitions. While the acquiring shareholders may have a little to gain, they may have much more to lose. Besides the prospects of punitive stock returns when accruals reverse, there is the likelihood of lower earnings quality as a result of engaging in opportunistic accrual management. An extensive accounting literature documents that such lower earnings quality is associated with a higher cost of capital (Francis et al. (2004)) and other negative long-term consequences (Dechow and Schrand (2004)). B. Does earnings manipulation via discretionary accruals have a positive stock price effect? A key assumption underlying strategic accrual management is that such management increases stock prices. We now test this assumption directly by examining the correlation between the performanceadjusted discretionary accruals and excess returns to acquirer stocks over several windows bracketing the

21

earnings announcement date. In an efficient market the correlation would be insignificant. In contrast, the very existence of earnings management depends on an assumed positive correlation. In previous literature, DeFond and Park (2001) show that the earnings response coefficient (ERC) is higher when discretionary accruals suppress the magnitude of a positive earnings surprise and lower when they accentuate the magnitude of a positive earnings surprise. They interpret their results as suggesting that the market partially adjusts for the possibility of accruals management on the earnings announcement date. Baber, Chen, and Kang (2006) confirm the DeFond and Park (2001) results and further document that the ability of market participants to detect earnings management is enhanced when there is additional disclosure. Table 8 arranges our aggregate sample of all cash and stock acquirers into ten deciles formed by discretionary current accruals computed using the balance sheet in Panel A and discretionary total accruals computed using the cash flow statement in Panel B. We examine the market-adjusted excess returns to cash and stock acquirers over several windows, EAD-1 to EAD+1, QEND-11 to MAD-2, and MAD-1 to MAD+1, where EAD is the earnings announcement date, MAD is the merger announcement date, and QEND is the fiscal quarter end date. We find no evidence to suggest that large income-increasing discretionary accruals increase the acquirer stock price over any of the three windows. On the contrary we find some evidence that the rank correlation between discretionary accrual deciles and market adjusted excess returns is negative (especially over EAD-1 to EAD+1). This result is consistent with prior literature, which shows that the market partially discounts earnings numbers associated with income increasing discretionary accruals. We next focus on the window QEND-11 to MAD-2. This is an important window where the entire effect of earnings announcement as well as earnings management is likely to be. Skinner and Sloan (2002) argue that 75% of the earnings preannouncements occur within two weeks on either side of the fiscal quarter end, so this window is also likely to capture a large part of the associated price effects. In Panel A the mean excess return to stock acquirers over QEND-11 to MAD-2 is greater than the mean excess return to cash acquirers in all 10 cases, and in Panel B it is greater in 9 out of 10 cases. However, the rank correlation between the accrual decile and the mean excess return is insignificant for both cash

22

and stock acquirers, and for both the current and total accruals. Finally, following an extensive literature, we document that the mean excess returns to cash deals is greater than the mean excess returns to stock deals over MAD-1 to MAD+1 in 8 out of 10 cases in Panel A and in all 10 cases in Panel B. The evidence in Table 8 has two interpretations. First, larger income increasing discretionary accruals do not increase stock prices, at least preceding mergers and acquisitions. Thus, the value of overvaluation f stemming from earnings management in Section V.A is indistinguishable from zero. Second, higher stock returns preceding merger announcement are associated with stock acquisitions, regardless of the reasons for such returns. In other words, the evidence is simultaneously consistent with Shleifer and Vishny (2003) hypothesis, that premium stock valuations lead managers to make stock acquisitions, and inconsistent with the earnings management hypothesis, that earnings management causes the premium stock valuations. C. Do acquirers expedite merger announcement and completion after presumed earnings management? Any stock price increase caused by accrual manipulation must be temporary, because the firm merely borrows earnings from future periods. Young (2008) therefore argues that acquiring firms which manage earnings would announce the merger agreement quickly after the earnings announcement. This would enable them to capitalize on the temporarily inflated stock price and avoid the inevitable price deflation with the arrival of subsequent adverse information. We test this assertion by sorting the merger sample into deciles based on discretionary total accruals and payment method and examining the mean number of days from the earnings release date to the merger announcement date. The results in Figure 2-A do not support this prediction. It appears that stock acquirers are in no hurry to announce their acquisitions following the quarterly earnings release date. The mean number of days between earnings announcement and merger announcement is a little above 45 for both cash and stock deals. In addition, this duration is not related to the accrual decile rank in either case. We interpret this result as suggesting that the acquiring firms do not expedite the merger announcements to cash in on inflated stock prices before the investors smarten up to the supposed earnings management.

23

Of course, the game does not end with the merger announcement. The acquirer firms must sustain the earnings management until completion. Thus, if discretionary accruals are a proxy for earnings management rather than random noise, then we would expect that they would be inversely related to the number of days between announcement and completion, especially for stock acquisitions. Figure 2-B tests this prediction. In general, it takes significantly longer to complete a stock acquisition than a cash acquisition, possibly because of an extended due diligence and shareholder approval process. However, there is no relation between discretionary accruals and the time to completion.12 D. Are acquirer firms with large discretionary accruals more likely to use stock payment? While we begin our study by replicating the results of other studies that examine the median discretionary accruals across cash vs. stock acquisitions, the investigation of incentive effects casts some doubts on this approach. In particular, this investigation calls into question the assumption that acquirer managers can foresee a stock acquisition and set in place an elaborate earnings management scheme. This assumption underlies all prior studies of earnings management in the context of mergers and acquisitions. We argue that a more meaningful test should examine the choice of stock vs. cash payment as a function of discretionary accruals during the quarter preceding the acquisition announcement. The results of such an investigation are very surprising. Figure 3 arranges all cash and stock acquisitions into deciles formed by discretionary accruals and examines the frequency of stock payment. We examine current accruals computed using the balance sheet method in Panel A and total accruals computed using the cash flow method in Panel B. Both panels present the evidence for the aggregate sample as well as the subset of public targets. In Panel A, the highest frequency of stock acquisitions is in the highest accrual decile, but the second highest frequency is in the lowest accrual decile. In Panel B, this order is reversed, with the highest frequency of stock acquisitions in the lowest accrual decile, and the second highest frequency in the highest accrual decile. Looking across the remaining deciles, we detect a striking U-shape in the relation between the frequency of stock acquisitions and discretionary accruals. This relation is also graphically shown in Figure 3. The fitted curves are based on a quadratic model 12

The results of Figure 2 are robust to sorting by discretionary current or total accruals, performance matching by only ROA or ROA and sales growth, examining only the public targets, or using mean or median number of days.

24

, where Y is the fraction of acquisitions that use stock payment and X is the accrual decile rank. The detailed results of this model are omitted for brevity, but we find that the quadratic term is highly significant in all cases. Table 9 reports a multivariate test of the quadratic form using a logistic regression in which the dependent variable is the stock payment dummy. The control variables are based on Faccio and Masulis (2005) and are described in the table legend. With or without controls, the square term for discretionary accruals is always significant at the 1% level while the linear term is insignificant.13 The finding of a strong relation between the squared (or absolute) value of discretionary accruals and stock payment discounts the possibility of earnings management, but it also raises another question: What explains the U-shape curve? Hribar and Nichols (2007) show that the absolute value of discretionary accruals is correlated with several firm-specific factors, especially the volatility of sales and cash flows. Figure 4 shows that the acquiring firm size, book-to-market, stock return volatility, and age are all related to the absolute value of discretionary accruals in our sample as well. Briefly speaking, we find that small firms, growth firms, volatile firms, and young firms are more likely to have discretionary accruals in the extreme deciles. This suggests that extreme accruals are not a result of strategic choices to expropriate wealth from target shareholders, but rather a by-product of firm characteristics that are associated with stock payment for mergers and acquisitions.

VI. Conclusions This paper re-examines the evidence in favor of earnings management documented by Erickson and Wang (1999), Louis (2004), Baik, Kang, and Morton (2007), Botsari and Meeks (2008), and Gong, Louis, and Sun (2008b). Using multiple tests with a comprehensive sample of 3,135 cash and stock acquisitions during 1989 to 2005, we find that their conclusions are driven by an incomplete specification of the quarterly discretionary accruals model. We identify an omitted variable, propose a methodology to adjust for its effect, and show that it leads to insignificant evidence of earnings management in our sample of acquisitions. This variable is the long-term sales growth rate, measured over a one-year period ending 13

Heron and Lie (2002) also find that the linear term is insignificant. They do not include the square term.

25

before the merger announcement date. The empirical importance of this variable is highlighted by the fact that cash acquirers have a median sales growth rate of 12.1%, compared to 41.1% for stock acquirers. The payment method, the partitioning variable used in studies of earnings management in the context of mergers and acquisitions is thus highly correlated with sales growth. Our proposed methodology computes quarterly discretionary accruals as the difference between residuals from the modified Jones model for sample firms and matching firms chosen to control for both ROA and growth. Using this measure we document an insignificant difference between cash and stock acquirers. We also document an insignificant relation between this measure and the relative size of the target to the acquirer firm. Thus, we find no evidence to suggest accruals manipulation in the aggregate sample or in subsets characterized by a higher economic incentive for manipulation. Several other tests affirm our finding against earnings management by stock acquirers. First, we find that stock acquirers are in no particular hurry to acquire following the earnings announcement and take significantly longer than cash acquirers to complete the transaction. This would not be the case if they were motivated to cash in on a temporary price increase. Second, we examine their depreciation policy and provision for uncollectible accounts and show that they are in line with their peer firms. Third, we find that the market may not even be fooled by higher discretionary accruals in the first place as higher discretionary accruals are uncorrelated with excess stock returns around the corresponding earnings announcements. Finally, in an interesting reversal of the experiment, we find that going forward the acquirer firms in the decile of most negative discretionary accruals are about as likely to choose stock payment (instead of cash payment) as acquirer firms in the decile of most positive discretionary accruals. This contradicts the very notion of strategic earnings management to inflate the stock price and use it as a currency to acquire other firms. In conclusion, we add to the literature by highlighting the relationship between longterm sales growth and accruals and exonerate stock acquirers as a group from having indulged in widespread earnings management.

26

References Agrawal, Anup, and Jeffrey Jaffe, 2000, The post-merger performance puzzle, Advances in Mergers and Acquisitions 1, 7-41. Andrade, Gregor, Mark Mitchell and Erik Stafford, 2001, New Evidence and Perspectives on Mergers, Journal of Economic Perspectives 15, 2. Baber, William, Shuping Chen, and Sok-Hyon Kang, 2006, Stock price reaction to evidence of earnings management: implications for supplementary financial disclosure, Review of Accounting Studies 11, 5-19. Ball, Ray and Lakshmanan Shivakumar, 2008, Earnings quality at initial public offerings, Journal of Accounting and Economics 45:2/3, 324-349. Baik, Bok, Jun-Koo Kang, and Richard Morton, 2007, Earnings management in takeovers of privately held targets, Working Paper. Botsari, Antonia and Geoff Meeks, 2008, Do acquirers manage earnings prior to share for share bid?, Journal of Business Finance and Accounting 35:5/6, 633-670. Burgstahler, David, and Ilia Dichev, 1997, Earnings management to avoid earnings decreases and losses, Journal of Accounting and Economics 24, 99-126. Cai, Jie, and Anand Vijh, 2007, Incentive effect of stock and option holdings of target and acquirer CEOs, The Journal of Finance 62(4), 1891-1933. Dechow, P., Sloan, R, and Sweeney, A., 1995, Detecting earnings management, Accounting Review , 193-226. Dechow, Patricia, and Catherine Schrand, 2004, Earnings quality, Research Foundation of CFA Institute Monograph. DeFond, M and C Park, 2001, The reversal of abnormal accruals and the market valuation of earnings surprises,” Accounting Review, 375-404. Degeorge, Fracois, Jayendu Patel, and Richard Zeckhauser, 1999, Earnings management to exceed thresholds, The Journal of Business 72:1, 1-33. Erickson, Merle, and Shiing-wu Wang, 1999, Earnings management by acquiring firms in stock for stock mergers, Journal of Accounting and Economics 27, 149-176. Faccio, Mara, and Ronald Masulis, 2005, The choice of payment method in European mergers and acquisitions, Journal of Finance 60, 1345-1388. Gong, Guojin, Henock Louis, and Amy Sun, 2008a, Earnings management and firm performance following open-market repurchases, Journal of Finance 63:2, 947-986. Gong, Guojin, Henock Louis, and Amy Sun, 2008b, Earnings management, lawsuits, and stock-for-stock acquirer’s market performance, Journal of Accounting and Economics 46:1,62-77

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Hartzell, Jay, Eli Ofek, and David Yermack, 2004, What's in it for me? Personal benefits obtained by CEOs whose firms are acquired", Review of Financial Studies, 17, 37-61 Healy, Paul, and James Wahlen, 1999, A review of the earnings management literature and its implications for standard setting, Accounting Horizons 13(4), 365-383. Heron, Randy, and Erik lie, 2002, Operating performance and method of payment in takeovers, Journal of Financial and Quantitative Analysis 37, 137-155. Hribar, Paul, and Daniel Collins, 2002, Errors in estimating accruals: implications for empirical research, Journal of Accounting Research 40, 105-134. Hribar, Paul, and Craig Nichols, 2007, The use of unsigned earnings quality measures in tests of earnings management, Journal of Accounting Research 45, 1017-1053. Jones, Jennifer, 1991, Earnings management during import relief investigations, Journal of Accounting Research 29, 193-228. Jensen, Michael, 2005, Agency costs of overvalued equity, Financial Management 34, 5-19. Kothari, S.P, Andrew Leone, and Charles Wasley, 2005, Performance matched discretionary accrual measures, Journal of Accounting and Economics 39, 163-197. Loughran, Tim, and Anand Vijh, 1997, Do long-term shareholders benefit from corporate acquisitions?, Journal of Finance 52, 1765-1790. Louis, Henock, 2004, Earnings management and the market performance of acquiring firms, Journal of Financial Economics 74, 121-148. Marquardt, Carol, and Christine Wiedman, 2004, How are earnings managed? An examination of specific accruals, Contemporary Accounting Research 21:2, 461-491. McNichols, Maureen, and GP Wilson, 1988, Evidence of earnings management from the provision for bad debts, Journal of Accounting Research 26 supplement, 1-31. McNichols, Maureen, 2000, Research design issues in earnings management studies, Journal of Accounting and Public Policy 19, 313-345. Moehrle, Stephen, 2002, Do firms use restructuring charge reversals to meet earnings targets?, Accounting Review 77:2, 397-413. Myers, Stewart, and Nicholas Majluf, 1984, Corporate financing and investment decisions when firms have information that investors do not have, Journal ofFinancia1 Economics13:2, 187-221. Officer, Micah, 2004, Collars and renegotiation in mergers and acquisitions, Journal of Finance 54, 7192743. Rau, Raghavendra, and Theo Vermaelen, 1998, Glamour, value and the post-acquisition performance of acquiring firms, Journal of Financial Economics 49, 223-253. Phillips, John, Morton Pincus, and Sonya Rego, 2003, Earnings Management: New Evidence Based on Deferred Tax Expense, Accounting Review 78, 491-521.

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Richardson, Scott, Richard Sloan, Mark Soliman, Irem Tuna, 2005, Accrual reliability, earnings persistence, and stock prices, Journal of Accounting and Economics 39, 437-485. Roychowdhury, Sugata, 2006, Earnings management through real activities manipulation, Journal of Accounting and Economics 42, 335-370. Shleifer, Andrei, and Robert Vishny, 2003, Stock market driven acquisitions, Journal of Financial Economics 70, 295-311. Skinner, Douglas, and Richard Sloan, 2002, Earnings surprises, growth expectations, and stock returns or don’t let an earnings torpedo sink your portfolio, Review of Accounting Studies 7:2/3, 289-312. Sloan, Richard, 1996, Do stock prices fully reflect information in accruals and cash flows about future earnings?, Accounting Review, 289-316. Teoh, Siew, Ivo Welch, and T. Wong, Earnings management and the underperformance of seasoned equity offerings, Journal of Financial Economics 50, 63-99. Teoh, Siew, T. Wong, and Gita Rao, 1998, Are accruals during initial public offerings opportunistic?, Review of Accounting Studies 3, 175-208.

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Appendix A – Incentive Effects of Earnings Management

Suppose an acquirer has an observed market value of AV and it makes an acquisition with a transaction value of TV. Now suppose that prior to the acquisition the acquirer boosted its stock price by managing earnings by a factor f, from

to AV.

Notice, if there were no earnings management, the target shareholders would get a proportion of the combined firm equal to . However, with earnings management, they only receive a fraction of the combined firm equal to

, Given that the true value of combined firm equals

, the dollar expropriation from target to acquirer shareholders as a result of earnings management is given by

The percent expropriation can be obtained by dividing the dollar expropriation by the true value of acquirer equity, which is

, as follows:

Where relative size is the ratio of transaction value to the observed and possibly inflated acquirer value. For very small relative size, the expression can be simplified to

. The above

expression can also be inverted to give a minimum value of Relative size that would produce a certain percentage benefit p. This minimum value would equal relative size would have to exceed create a 5% benefit.

. Thus, assuming f = 0.20, the

to create a 1% benefit, or exceed

to

30 Table 1 Summary statistics of data Our sample includes all acquisitions from the SDC database that meet the following criteria: 1. The acquisition is announced during 1989-2005. 2. The target is a public, private, or subsidiary firm domiciled in the U.S. 3. The acquirer is a public firm included in the CRSP and Compustat databases with ordinary common shares outstanding (CRSP share code 10 or 11, which excludes ADRs, REITs, units, certificates, and trusts). 4. The acquirer is not a financial firm. 5. The transaction value exceeds $10 million. 6. The transaction form is categorized as deal type 1 (disclosed value mergers and acquisitions). 7. The acquirer owns less than 50% of target shares before announcement and 100% of target shares after completion. 8. The form of payment is all cash or all stock (thus, mixed payment cases are excluded). 9. The acquirer has relevant data on Compustat quarterly file to calculate performance and sales growth adjusted abnormal accruals using the balance sheet and cash flow methods. We obtain the transaction value from SDC and the acquirer total assets and market value from Compustat (as of last quarter-end). We calculate the relative size as the transaction value divided by the acquirer market value, the acquirer book-to-market value as the book value divided by the market value of equity, and the acquirer return on assets as the net income divided by total assets. The prior-year market-adjusted excess returns are calculated by subtracting the cumulative market returns from the cumulative stock returns over a 254-day period ending on MAD-2 (where MAD denotes the merger announcement date). We compute annual sales growth from quarter t-5 to t-1, where t-1 is the quarter with an earnings release date immediately preceding the merger announcement. All statistics in Panel B are medians, except excess returns, which are means. Panel A: Sample distribution by target status and form of payment Target type All Targets Public Private Subsidiary

All targets 3135 866 1337 932

Cash 1998 397 756 845

Stock 1137 469 581 87

Panel B: Summary statistics

Acquirer total assets ($ mil) Acquirer market value ($ mil) Acquirer book-to-market Acquirer return on assets Transaction value ($ mil) Relative size Acquirer prior-year marketadjusted excess returns Acquirer annual sales growth N

Cash 862 1133 0.38 1.64 63 0.07

All targets Stock All 412 681 1131 1133 0.22 0.32 1.69 1.65 83 68 0.09 0.07

Public Cash Stock 2123 782 2614 1467 0.34 0.26 1.80 1.43 180 233 0.08 0.23

Private Cash Stock 561 273 790 965 0.38 0.18 1.74 2.00 43 45 0.06 0.05

Subsidiary Cash Stock 957 439 1122 930 0.39 0.30 1.46 1.03 63 47 0.08 0.11

14.2

72.2

35.2

6.1

49.7

17.6

93.7

15.0

49.6

12.1 1998

41.1 1137

17.7 3135

9.2 397

32.8 469

15.5 756

46.3 581

12.0 932

28.0 87

Panel C: Sample distribution over time Cash Stock Total Cash Stock Total

1989

1990

1991

1992

1993

1994

1995

1996

1997

3 1 4

26 14 40

28 23 51

34 33 67

64 29 93

80 60 140

87 99 186

115 108 223

155 111 266

1998

1999

2000

2001

2002

2003

2004

2005

Total

170 145 315

151 165 316

143 147 290

123 82 205

164 30 194

180 38 218

244 26 270

231 26 257

1998 1137 3135

31 Table 2 Traditional measures of discretionary accruals calculated using ROA-adjusted benchmarks for the sample of acquirers Table 1 describes the sample of acquisitions. The calculation of performance-adjusted abnormal accruals follows a threestep process. First, following Louis (2004), we compute current (or working-capital) accruals as CA-CLCASH+STDEBT, where CA is the change in current assets during quarter t (Compustat quarterly item 40), CL is the change in current liabilities (item 49), CASH in the change in cash and cash equivalents (item 36), and STDEBT is the current maturities of long-term debt and other short-term debt included in current liabilities (item 45). In addition, following Hribar and Collins (2002), we compute total accruals from the cash flow statement as EBXI-CFO, where EBXI is earnings before extraordinary items and discontinued operations (item 76) and CFO is the operating cash flow taken directly from the cash flow statement (item 108) adjusted for the cash portion of discontinued operations and extraordinary items (item 78). Second, following Gong, Louis, and Sun (2008a, 2008b), we estimate discretionary current accruals using the balance sheet method as the residual from a modified Jones model applied to cross-sectional quarterly data for firms belonging to the same two-digit SIC code: . We estimate discretionary total accruals in a similar fashion:

In these expressions, Q1-Q4 are the fiscal quarter dummies, is the quarterly change in sales, is the quarterly change in accounts receivables, LagCA (TA) is the current (total) accrual from the same quarter in the preceding year, and PPE is the property, plant, and equipment in the current quarter. All variables are scaled by lagged total assets. Third, following Louis (2004), Kothari, Leone, and Wasley (2005), and Gong, Louis, and Sun (2008a, 2008b), we calculate the ROA-adjusted discretionary accruals. This equals the difference between discretionary accruals for the sample firm and the median discretionary accruals for the quintile of same-industry firms matched by return on assets during the fourth quarter before the current quarter. Quarter t-1 is the quarter with an earnings release date immediately preceding the merger announcement. However, the quarter t sample includes only acquisitions that were announced but not completed before the next earnings announcement date. The p-values are reported in parentheses and are based on the Wilcoxon sign-rank test. The notations *, **, and *** denote significance at the 10%, 5%, and 1% levels.

32 Table 2 – continued

Cash acquirers Stock acquirers Median accruals Median accruals Difference between Quarter N (p-value) N (p-value) medians (p-value) Panel A: ROA-adjusted discretionary current accruals calculated using the balance sheet method A.1. All targets t-2 1875 -0.004 (0.336) 1009 0.178 (0.001)*** t-1 1998 0.082 (0.116) 1137 0.419 (0.000)*** t 894 0.044 (0.519) 703 0.409 (0.001)*** A.2. Public targets t-2 370 -0.094 (0.399) 434 -0.109 (0.357) t-1 397 -0.084 (0.512) 469 0.304 (0.014)** t 274 -0.013 (0.859) 399 0.252 (0.065) A.3. Private targets t-2 711 -0.148 (0.517) 499 0.346 (0.001)*** * t-1 756 0.127 (0.053) 581 0.512 (0.000)*** t 232 -0.056 (0.417) 253 0.598 (0.002)*** A.4 Subsidiary targets t-2 794 0.092 (0.006)*** 76 0.375 (0.157) t-1 845 0.125 (0.339) 87 0.275 (0.090)* * t 388 0.143 (0.067) 51 0.169 (0.712) Panel B: ROA-adjusted discretionary total accruals calculated using the cash flow method B.1. All targets t-2 1875 t-1 1998 t 894 B.2. Public targets t-2 370 t-1 397 t 274 B.3. Private targets t-2 711 t-1 756 t 232 B.4 Subsidiary targets t-2 794 t-1 845 t 388

0.044 (0.157) 0.105 (0.005)*** 0.091 (0.495)

0.182 (0.021)*** 0.337 (0.001)*** 0.365 (0.001)*** -0.015 (0.292) 0.388 (0.026)** 0.262 (0.113) 0.494 (0.002)*** 0.385 (0.032)** 0.654 (0.002)*** 0.283 (0.539) 0.150 (0.182) 0.026 (0.813)

1009 1137 703

0.038 (0.580) 0.136 (0.092)* 0.209 (0.866)

-0.006 (0.889) 0.031 (0.752) 0.118 (0.932)

-0.067 (0.792) -0.010 (0.862) 0.100 (0.539)

434 469 399

0.000 (0.765) 0.099 (0.456) 0.209 (0.835)

0.067 (0.985) 0.109 (0.838) 0.109 (0.788)

-0.030 (0.880) 0.196 (0.027)** -0.193 (0.032)**

499 581 253

0.038 (0.477) 0.116 (0.173) 0.255 (0.361)

0.008 (0.465) -0.080 (0.988) 0.448 (0.032)**

0.149 (0.012)** 0.087 (0.023)** 0.372 (0.028)**

76 87 51

0.195 (0.347) 0.585 (0.382) -0.186 (0.307)

0.046 (0.804) 0.498 (0.727) -0.558 (0.081)*

33 Table 3 Annual sales growth rate and ROA-adjusted discretionary accruals for the sample of acquirers Table 1 describes the sample of acquisitions, and Table 2 describes the methodology used to compute ROA-adjusted discretionary accruals. This table analyzes the relation between the longer-term annual sales growth rate and the ROAadjusted discretionary accruals for the sample of acquirers. (Note that the quarterly Jones model used to estimate discretionary accruals adjusts for the quarterly sales changes, but not for the annual sales growth rate.) To form annual sales growth decile portfolios, we follow a procedure similar to the Fama-French procedure of forming size and book-to-market decile portfolios. Specifically, we compute annual sales growth rate for all NYSE firms with available data from quarter t-5 to quarter t-1 to ascertain the sales growth decile cutoffs. Using these cutoffs we assign a sales growth decile rank to all acquirers. Panel A presents median ROA-adjusted discretionary accruals by sales growth decile separately for cash and stock acquirers. Panel B presents a regression analysis in which the discretionary accruals used as the dependent variable have been winsorized at the 1% level. These regressions include a prior acquisition dummy that takes the value of one if footnotes to the Compustat quarterly data indicate that the current acquirer made another acquisition during the last four quarters, and zero otherwise. The notations *, **, and *** denote significance at the 10%, 5%, and 1% levels. Panel A: Median ROA-adjusted discretionary accruals by sales growth decile Cash acquirers Sales Median Current accruals Total accruals growth sales using balance using cash decile growth N sheet method flow method N 1 -0.248 162 -0.493 -0.621 96 2 -0.053 135 -0.160 -0.004 34 3 -0.006 130 -0.002 0.016 33 4 0.027 140 -0.148 0.047 27 5 0.061 196 -0.009 0.050 28 6 7 8 9 10

0.095 0.138 0.194 0.296 0.743

179 186 207 282 381

-0.052 0.078 0.368 0.278 0.476

0.072 0.418 0.289 0.105 0.339

Rank correlation with sales 0.903*** 0.915*** growth decile Panel B: Regression analysis of ROA-adjusted discretionary accruals Current accruals using balance sheet method (1) (2) (3) Intercept 0.118 -1.051 -1.065 (1.45) (-6.55)*** (-4.87)*** Stock payment dummy

0.413 (3.04)***

Sales growth decile

0.128 (0.92)

0.125 (0.89)

0.183 (8.43)***

0.183 (5.72)***

Prior acquisition dummy Prior acquisition*Sales growth decile N Adjusted R2

3135 0.003

3135 0.025

47 50 89 166 567

Stock acquirers Current accruals Total accruals using balance using cash sheet method flow method -1.208 -0.986 -0.389 -0.280 0.689 0.589 -0.175 0.167 0.339 0.871 -0.503 1.623 0.917 0.412 0.759 0.661**

(4) 0.157 (-1.80)* -0.136 (-0.94)

-0.053 1.144 0.485 -0.195 0.273 0.345

Total accruals using cash flow method (5) (6) -0.554 -0.796 (-3.21)*** (-3.39)*** -0.309 (-2.08)** 0.112 (4.77)***

-0.237 (-1.58) 0.175 (5.09)***

0.038 (0.12)

0.391 (1.12)

-0.002 (-0.04)

-0.101 (-2.15)**

3135 0.024

3135 0.000

3135 0.007

3135 0.009

34 Table 4 ROA adjusted versus ROA and sales growth adjusted discretionary accruals for the aggregate sample of all Compustat firm-quarters This table first documents a strong monotonic relation between the annual sales growth rate and ROA adjusted discretionary accruals for the aggregate sample of all Compustat firm-quarters with available data. We compute annual sales growth rate for each firm-quarter observation from four quarters before to the current quarter. The procedure of computing ROA adjusted discretionary accruals is described in Table 2, and it follows Louis (2004), Kothari, Leone, and Wasley (2005), and Gong, Louis, and Sun (2008a, 2008b). We then extend this procedure to account for the effect of annual sales growth. Specifically, in addition to being in the same industry and ROA quintile during the fourth quarter before the current quarter, we require firms in the matched portfolio to be in the same annual sales growth tercile. Further, to form annual sales growth decile portfolios, we follow a procedure similar to the Fama-French procedure of forming size and book-to-market decile portfolios. We compute annual sales growth rate for all NYSE firms during each calendar quarter with available data to ascertain the sales growth decile cutoffs. Using these cutoffs we assign a sales growth decile rank to all firm-quarter observations. The last two columns show that the correlation between the annual sales growth rate and the ROA and sales growth rate adjusted discretionary accruals is close to zero. The notations *, **, and *** denote significance at the 10%, 5%, and 1% levels.

Sales growth decile 1 2 3 4 5

N 25606 15250 12624 11848 11593

Median sales growth -0.257 -0.065 -0.008 0.029 0.060

6 7 8 9 10

12132 13208 15835 19374 30668

0.093 0.130 0.186 0.283 0.651

Rank correlation with sales growth decile Slope of median accruals regressed on sales growth decile rank

Median ROA adjusted discretionary accruals Current accruals Total accruals using balance using cash sheet method flow method -0.872 -0.800 -0.383 -0.285 -0.250 -0.135 -0.099 -0.046 -0.029 -0.008 -0.012 0.093 0.197 0.398 0.710

0.082 0.121 0.163 0.281 0.504

Median ROA and sales growth adjusted discretionary accruals Current accruals Total accruals using balance using cash sheet method flow method -0.278 -0.258 0.113 0.129 0.080 0.094 0.040 0.061 0.005 -0.030 -0.044 0.021 -0.013 -0.079 0.145

0.014 0.035 -0.022 -0.029 0.094

1.000***

1.000***

0.042

-0.067

0.137***

0.108***

0.011

0.009

35 Table 5 Improved measures of discretionary accruals calculated using ROA and sales growth adjusted benchmarks for the sample of acquirers This table tests for the presence of earnings management in the sample of acquirers using the new ROA and sales growth adjusted discretionary accruals. It contrasts with Table 2 that does the same with only ROA adjusted discretionary accruals. Table 1 describes the sample of acquisitions, Table 2 describes the procedure for computing ROA adjusted discretionary accruals, and Table 4 describes the procedure for computing ROA and sales growth adjusted discretionary accruals. The notations *, **, and *** denote significance at the 10%, 5%, and 1% levels. Cash acquirers Stock acquirers Median accruals Median accruals Difference between Quarter N (p-value) N (p-value) medians (p-value) Panel A: ROA and sales growth adjusted discretionary current accruals calculated using the balance sheet method A.1. All targets t-2 1840 -0.103 (0.581) 1003 -0.188 (0.621) -0.085 (0.669) t-1 1998 -0.027 (0.694) 1137 -0.113 (0.656) -0.086 (0.638) t 876 0.045 (0.700) 696 0.174 (0.343) 0.129 (0.502) A.2. Public targets t-2 361 -0.246 (0.133) 429 -0.284 (0.263) -0.038 (0.930) t-1 397 -0.218 (0.029) 469 -0.031 (0.567) 0.187 (0.104) t 268 0.016 (0.668) 394 0.052 (0.918) 0.036 (0.757) Panel B: ROA and sales growth adjusted discretionary total accruals calculated using the cash flow method B.1. All targets t-2 t-1 t B.2. Public targets t-2 t-1 t

1840 1998 876

-0.009 (0.816) 0.023 (0.389) 0.170 (0.433)

1003 1137 696

-0.191 (0.039) -0.044 (0.330) -0.041 (0.138)

-0.182 (0.044)** -0.067 (0.234) -0.058 (0.160)

361 397 268

-0.118 (0.205) -0.131 (0.164) 0.139 (0.707)

429 469 394

-0.189 (0.144) 0.033 (0.531) -0.041 (0.136)

-0.071 (0.743) 0.164 (0.626) -0.180 (0.265)

36 Table 6 Depreciation policy and provision for uncollectible accounts receivable for the sample of acquirers Table 1 describes the sample of acquisitions. Following Teoh, Wong, and Rao (1998), we group depreciation policy (Compustat annual footnote 15) into three categories: accelerated, straight line, and a combination of the two. Straight line is the most income increasing, followed by the combination and accelerated methods. In Panel A, the income increasing (decreasing) group contains any case where the acquiring firm uses a more (less) income increasing method relative to the matched firm. The equivalent group contains cases where both the acquirer and matched firm use the same method. To choose a matching firm, we identify firms in the same 2-digit industry and ROA quintile during quarter t-5. From this we choose the one firm with the closest annual sales growth rate as defined in Table 3. The Z-statistics are computed by comparing the frequency of income increasing cases with income decreasing cases and ignore the equivalent cases. Panel B compares the provision for uncollectible accounts receivable (Compustat annual item 67) as a fraction of the gross accounts receivable (Compustat annual item 2) for sample and matched firms during the announcement year. Presumably, earnings management that increases stock price would require acquirer firms to include a lower provision for bad debts. Panel A: Depreciation policy relative to matching firms Income decreasing Income increasing Frequency Percent Frequency Percent A.1. All Targets Cash acquirers Stock acquirers

211 127

10.65 11.24

206 108

10.39 9.56

A.2. Public Targets Cash acquirers 51 13.01 40 10.20 Stock acquirers 51 10.97 44 9.46 Panel B: Median allowance for uncollectible accounts receivable divided by gross accounts receivable (%) Acquirer firms Matching firms Difference (p-value) B.1. All Targets Cash acquirers Stock acquirers

3.648 3.713

3.648 3.722

0.000 (0.608) -0.009 (0.979)

B.2. Public Targets Cash acquirers Stock acquirers

3.451 3.969

3.458 3.579

-0.007 (0.693) 0.390 (0.919)

Equivalent Frequency Percent

Z (income increasing)

1565 895

78.96 79.20

-0.25 -1.24

301 370

76.79 79.57

-1.15 -0.72

37 Table 7 Are relatively large stock acquisitions preceded by higher discretionary accruals as predicted by the incentives theory of earnings management? Table 1 describes the sample of acquisitions, and Tables 2 and 4 describes the methodology used to compute ROA and sales growth adjusted discretionary accruals. This table tests whether discretionary accruals (our proxy for earnings management) are larger in acquisitions which have a higher relative size (transaction value divided by market value of the acquirer) as predicted by the incentives theory of earnings management. Following the model described in Appendix 1, the wealth transfer from target to acquirer shareholders is given by where f is the percentage overvaluation of the acquirer stock as a result of earnings management. We choose one scenario of f = 15% for an illustration of wealth transfer. Panel A consider the aggregate sample of all targets, and Panel B considers the subset of public targets. Both panels report the median ROA and sales growth adjusted discretionary current accruals using the balance sheet method and total accruals using the cash flow method. The Spearman rank correlation coefficient is used to test whether higher relative size deciles are associated with larger accruals. The notations *, **, and *** denote significance at the 10%, 5%, and 1% levels.

Relative size decile

N

Median relative size

Median wealth transfer to acquirer shareholders assuming f = 0.15

Panel A: Stock acquisitions of all targets 1 104 0.003 2 102 0.011 3 106 0.023 4 106 0.038 5 107 0.061 6 7 8 9 10

94 104 114 136 164

0.092 0.132 0.213 0.387 0.971

0.000 0.002 0.003 0.006 0.009

-0.740 -0.189 0.511 0.390 0.159

-1.131 -0.200 0.596 0.294 0.293

0.013 0.018 0.026 0.042 0.074

0.474 -0.704 -0.382 -0.115 -0.079

0.847 -0.109 -0.279 -0.235 0.095

0.006

-0.018

0.004 0.038

0.033 -0.225 -0.258

0.090 -0.152 -0.242

0.000 0.002 0.003 0.006

0.668 0.612 -0.218 0.140

0.017 0.090 -1.525 0.663

0.009 0.013 0.018 0.028 0.042 0.071

-0.669 0.616 0.059 -0.707 -0.115 -0.031

0.309 0.323 -0.030 -0.272 -0.192 -0.150

-0.478

-0.333

0.335 -0.128 -0.463

0.321 -0.154 -0.475

Rank correlation with relative size decile Deciles 1-5 Deciles 6-10 Difference

619 518

0.029 0.341

Panel B: Stock acquisitions of public targets 1 24 0.003 2 25 0.012 3 18 0.021 4 29 0.039 5 6 7 8 9 10

25 41 39 63 94 111

0.061 0.092 0.132 0.231 0.393 0.895

Rank correlation with relative size decile Deciles 1-5 Deciles 6-10 Difference

162 307

0.039 0.407

Median ROA and sales growth adjusted discretionary accruals Current accruals Total accruals using balance using cash sheet method flow method

0.006 0.043

38 Table 8 Measuring f : The likely stock price increase caused by discretionary accruals for the sample of acquirers Table 1 describes the sample of acquisitions, and Tables 2 and 4 describe the methodology used to compute ROA and sales growth adjusted discretionary accruals. Excess returns for the acquirer firms are calculated by subtracting cumulative market returns from cumulative stock returns over various windows. Market returns are measured by the CRSP valueweighted index returns. Equally-weighted mean excess returns are reported. EAD refers to the earnings announcement date, MAD to the merger announcement date, and QEND to the fiscal quarter-end date. The short windows EAD-1 to EAD+1 and MAD-1 to MAD+1 measure the announcement returns, and the long window QEND-11 to MAD-2 measures the cumulative effect of earnings management. (The choice of QEND-11 follows Skinner and Sloan (2002), who argue that 75% of all earnings preannouncements occur within two weeks on either side of the fiscal quarter end.) The Spearman rank correlation coefficient is used to test whether higher discretionary accrual deciles are associated with larger market adjusted excess returns around various windows. The notations *, **, and *** denote significance at the 10%, 5%, and 1% levels. Discretionary accrual decile

N EAD-1 to EAD+1 Cash Stock Cash Stock Panel A: Current accruals using balance sheet method 1 166 147 1.41 0.97 2 208 106 0.64 2.19 3 194 119 0.97 2.25 4 200 113 0.37 1.56 5 218 96 -0.22 1.04 6 7 8 9 10

241 225 202 175 169

73 89 111 139 144

Market-adjusted excess returns QEND-11 to MAD-2 Cash Stock

MAD-1 to MAD+1 Cash Stock

2.42 1.96 1.88 5.22 2.70

11.60 11.32 16.82 19.41 12.42

1.76 0.80 0.84 0.92 1.68

0.26 0.60 -0.15 0.42 1.76

0.25 0.75 0.84 -0.52 -0.17

0.71 1.27 2.86 1.42 0.33

2.39 1.70 1.17 3.52 4.61

10.70 4.54 16.22 13.69 10.94

2.20 0.93 1.52 1.90 2.11

-1.67 1.69 -0.55 1.40 -0.72

-0.58*

-0.21

0.12

-0.20

0.54

-0.15

1.86 3.27 1.63 1.40 1.16

2.73 0.85 0.94 3.92 0.78

18.56 14.37 10.22 14.37 19.24

2.12 1.11 0.88 1.93 1.03

0.45 0.46 -0.35 0.91 0.46

0.73 0.44 1.04 0.07 -1.01

1.61 0.20 1.10 1.81 0.09

5.14 3.05 5.03 2.57 1.32

3.68 9.14 8.76 16.91 10.92

1.11 0.53 1.74 2.30 2.27

0.53 -1.07 1.57 -0.53 0.81

-0.39

-0.68**

0.24

-0.33

0.31

0.15

All Rank correlation with accrual decile

Panel B: Total accruals using cash flow method 1 143 170 0.91 2 196 118 0.35 3 195 119 0.51 4 235 78 1.08 5 224 89 -0.08 6 7 8 9 10

217 223 214 182 169

98 90 99 132 144

All Rank correlation with accrual decile

39 Table 9 Are firms with high discretionary accruals more likely to use stock payment? We extend the Faccio and Masulis (2005) logistic model of the determinants of payment method in acquisitions by including a quadratic function of discretionary accruals. The dependent variable is a dummy that takes the value of one for stock acquisitions and zero for cash acquisitions. Table 1 describes the sample of acquisitions, and Tables 2 and 4 describes the methodology used to compute ROA and sales growth adjusted discretionary accruals. Private target and subsidiary target are dummy variables that equal one if the target is privately held or is a subsidiary of a public corporation, and zero otherwise. We calculate the relative size as the transaction value divided by the acquirer market value. Prior-year marketadjusted excess returns are calculated by subtracting the cumulative market returns from the cumulative stock returns over a 254-day period ending on MAD-2 (where MAD denotes the merger announcement date). The acquirer book-to-market value is given by the book value divided by the market value of equity and acquirer leverage is defined as total liabilities divided by total assets. Acquirer volatility is calculated over a 254-day period ending on MAD-2. Same Industry is another dummy variable that equals one if both the acquirer and the target belong to the same 2-digit industry code, and zero otherwise. Regressions (7) to (10) are run using the discretionary current accruals computed using the balance sheet measure, and regressions (11) to (14) are run using discretionary total accruals computed using the cash flow statement. The notations a, b, and c denote significance at the 10%, 5%, and 1% levels.

Variable Intercept

Logistic analysis of stock payment dummy Current accruals using Total accruals using balance sheet method cash flow method All targets Public targets All targets Public targets (7) (8) (9) (10) (11) (12) (13) (14) -0.669 0.509 -0.024 -0.139 -0.715 0.556 -0.028 -0.134 (-16.06)c (1.58) (-0.30) (-0.28) (-17.12)c (1.72)a (-0.36) (-0.03)

ROA and sales growth adjusted discretionary accruals

0.371 (0.707)

-0.558 (-0.50)

1.897 (0.86)

1.601 (0.69)

-0.477 (-0.48)

-0.569 (-0.51)

0.741 (0.34)

0.278 (0.12)

Square of above

0.711 (5.52)c

0.454 (3.12)c

1.465 (3.91)c

1.014 (2.72) c

0.898 (7.23)c

0.535 (4.26)c

1.302 (4.15)c

0.809 (2.77)c

Private target

-0.812 (-7.68)c

-0.810 (-7.67)c

Subsidiary target

-2.586 (-16.14)c

-2.594 (-16.03)c

Relative size

0.620 (3.74)c

1.125 (3.47)

0.614 (3.71)c

1.122 (3.32)c

Prior-year returns

0.253 (4.49)c

0.524 (3.23)

0.252 (4.56)c

0.530 (3.28)c

Acquirer log assets

-0.068 (-2.23)c

-0.069 (-1.43)

-0.071 (-2.32)c

-0.080 (-1.64)

Acquirer book-to-market

-1.949 (-7.36)c

-1.783 (-5.18)

-1.937 (-7.29)c

-1.779 (-5.10)c

Acquirer leverage

-1.308 (-5.42)c

-1.147 (-2.60)

-1.312 (-5.42)c

-1.108 (-2.55)b

Acquirer volatility

2.654 (11.87)c

2.672 (6.37)

2.563 (11.37)c

2.571 (6.23)c

Same industry

-0.187 (-2.03)b

0.271 (1.67)

-0.192 (-2.08)b

0.260 (1.60)

N

3135

3135

866

866

3135

3135

866

866

40

0.7

0.7

0.5

0.5

0.3

0.3

0.1

0.1

-0.1

1

2

3

4

5

6

7

8

9 10

-0.1

-0.3

-0.3

-0.5

-0.5

-0.7

-0.7

-0.9

-0.9 Annual sales growth decile Median ROA adjusted discretionary current accrual Median ROA and sales growth adjusted discretionary current accrual Figure 1-A

1

2

3

4

5

6

7

8

9 10

Annual sales growth decile Median ROA adjusted discretionary total accrual Median ROA and sales growth adjusted discretionary total accrual Figure 1-B

Figure 1: ROA adjusted versus ROA and sales growth adjusted discretionary accruals for the aggregate sample of all Compustat firm-quarters. This figure graphically depicts the results of Table 4. It analyzes the aggregate sample of all Compustat firm-quarters as described in that table. Current accruals are computed using the balance sheet method whereas total accruals are computed using the cash flow method. The figure shows that the traditional ROA adjusted discretionary accruals are monotonically related to annual sales growth decile rank. It further suggests that the resulting bias imparted to samples of acquirers that differ by annual sales growth rate (specifically, cash acquirers versus stock acquirers) should be mitigated by using the new ROA and sales growth adjusted discretionary accruals.

41

Number of days between Earnings Announcement Date and Merger Announcement Date

60 50 40 30 Cash 20

Stock

10 0 1

2

3

4

5

6

7

8

9

10

Decile rank based on discretionary total accruals

Figure 2-A Number of days between Merger Announcement Date and Merger Completion Date

100 90 80 70 60 50 40

Cash

30

Stock

20 10 0 1

2

3

4

5

6

7

8

9

10

Decile rank based on discretionary total accruals Figure 2-B Figure 2: Do acquirers expedite merger announcement and completion after presumed earnings management to capitalize on the temporarily inflated stock price? We sort our sample of acquisitions into deciles based on ROA and sales growth adjusted discretionary total accruals computed using the cash flow method. Panel A presents the average number of days between the last earnings announcement and the merger announcement, and Panel B presents the average number of days between the merger announcement and completion. The rank correlations between the number of days and the accrual decile ranks are insignificant in both panels.

80 70 60 50 40 30 20 0

1

2

3

4

5

6

7

8

9

Decile rank based on ROA and sales growth adjusted discretionary current accruals

10

Fraction of acquisitions that use stock payment

Fraction of acquisitions that use stock payment

42

80 70 60 50 40 30 20 0

1

2

3

4

5

6

7

8

9

10

Decile rank based on ROA and sales growth adjusted discretionary total accruals

All Targets

Public Targets

All Targets

Public Targets

All Fitted

Public Fitted

All Fitted

Public Fitted

Figure 3: ROA and sales growth adjusted discretionary accruals and payment method – The U-shape distribution. One implication of the earnings management hypothesis is that acquirers who choose to inflate their stock price via earnings management will be more likely to use stock payment. We test this hypothesis by sorting acquisitions into deciles based on ROA and sales growth adjusted discretionary accruals as described in Tables 2 and 4. The current accruals reported in the left panel are computed using the balance sheet method and the total accruals reported in the right panel are computed using the cash flow method. Each panel reports the fraction of acquisitions that use stock payment for the aggregate sample of all targets as well as the subset of public targets. We plot fitted values from a quadratic model of the form , where Y is the fraction of acquisitions that use stock payment and X is the decile rank. All regressions give highly significant values of to show the existence of a U-shape.

1600

0.38

1400

0.36

Book-to-Market ratio (median)

Market value (median)

43

1200 1000 800 600 400

0.34 0.32 0.30 0.28

200

0.26

0

0.24 1

2

3

4

5

6

7

8

9

10

1

2

Decile rank of discretionary accruals

4

5

6

7

8

9

10

Decile rank of discretionary accruals

Figure 4-A

Figure 4-B

0.65

20 18 Firm age (mean)

0.60 Return volatility (mean)

3

0.55

0.50

0.45

16 14 12 10

0.40

8 1

2

3

4

5

6

7

8

Decile rank of discretionary accruals

Figure 4-C

9

10

1

2

3

4

5

6

7

8

9

Decile rank of discretionary accruals

Figure 4-D

Figure 4: Discretionary total accruals and firm characteristics – Explaining the U-shape distribution of Figure 3 and Table 9. We plot actual values and a fitted line from a quadratic model of the form , where Y is a specific firm characteristic and X is the decile rank computed using ROA and sales growth adjusted discretionary total accruals for the aggregate sample of all acquirers as described in Table 1. Y equals the median market value in Panel A, the median book-to-market ratio in Panel B, the mean return volatility in Panel C, and the mean firm age in Panel D. Following the evidence in Hribar and Nichols (2007), this figure confirms that small firms, growth firms, young firms, and volatile firms are more likely to have discretionary accruals in the extreme deciles.

10