Errors in Estimating Accruals: Implications for Empirical Research

 

Daniel W. Collinsa*, Paul Hribarb

 

 

a Henry B. Tippie Research Chair in Accounting

Tippie College of Business, University of Iowa, Iowa City, IA 52242

b Johnson Graduate School of Management, Cornell University, Ithaca, NY 14850

 

 

 

Current Version: July 14, 2000

 

 

 

 

Abstract: This paper examines the impact of measuring accruals as the change in successive balance sheet accounts, as opposed to measuring accruals directly from the statement of cash flows. Our primary finding is that studies using a balance sheet approach to test for earnings management are potentially contaminated. In particular, if the partitioning variable used to indicate the presence of earnings management is correlated with the occurrence of mergers and acquisitions or discontinued operations, researchers are likely to erroneously conclude that earnings management exists when there is none. Additional results show that the bias in balance sheet accruals estimation can confound returns regressions where discretionary and non-discretionary accruals are used as explanatory variables. Moreover, we demonstrate that tests of market mispricing of accruals will be understated due to erroneous classification of "extreme" accruals firms.

 

 


*Corresponding Author. Phone (319) 335-0910; Fax: (319) 335-1956; e-mail: daniel-collins@uiowa.edu.

We gratefully acknowledge the helpful comments and suggestions made by Kevin Den Adel, Mike Cipriano, S.P. Kothari, Nicole Jenkins, Mort Pincus, Scott Vandervelde, Charles Wasley, and workshop participants at the University of Iowa and Tulane University.

Errors in Estimating Accruals: Implications for Empirical Research

I. Introduction

The measurement of accruals plays a central role in a wide body of literature in accounting. This literature includes studies on the relative informativeness or value relevance of cash flows versus accruals [Rayburn (1986), Wilson (1987), Dechow (1994)], tests of earnings management and income smoothing [e.g. Healy (1985), DeAngelo (1986, 1988), Jones (1991), Dechow, Sloan and Sweeney (1995), Rees, Gill and Gore (1996), DeFond and Subramanyam (1998), Teoh, Welch, Wong (1998)], the pricing of discretionary versus nondiscretionary accruals [Subramanyan (1996), Guay, Kothari and Watts (1996), Xie (1999)], and the market's mispricing of accruals [Sloan (1996), Xie (1999), Collins and Hribar (2000)]. The vast majority of these studies use an indirect balance sheet approach to calculate accruals. The balance sheet approach relies on the presumed articulation between changes in working capital balance sheet accounts and accrual components of revenues and expenses on the income statement.

This presumed articulation breaks down when nonoperating events such as reclassifications, acquisitions, divestitures, accounting changes and foreign currency translations occur [Drtina and Largay (1985), Huefner, Ketz and Largay (1989), Bahnson, Miller and Budge (1996) and Revsine, Collins and Johnson (1999)]. Using precise information on accruals from cash flow statements subsequent to SFAS No. 95, Bahnson et al. (1996) estimate that for a broad cross section of Compustat firms approximately 75% of the sample companies presented nonarticulated changes in current accounts.

The purpose of this paper is to provide further evidence on the magnitude and frequency of the nonarticulation problem and assess its implications for empirical studies that have relied on the indirect approach to estimate accruals and operating cash flows. The severity of the mismeasurement of accruals and/or operating cash flows is evaluated for samples comprised of a broad cross section of NYSE and AMEX firms and for samples of firms involved in mergers and acquisitions, divestitures and foreign operations through subsidiaries. We demonstrate the effect of using balance sheet accruals estimates relative to properly measured accruals in three popular applied settings: (1) estimating the discretionary and nondiscretionary component of accruals and tests of earnings management; (2) the relation between security returns and accruals, discretionary accruals, nondiscretionary accruals, and cash flow from operations; and (3) testing for market mispricing of accruals.

Our major findings are that error and bias in balance sheet accruals estimates are pervasive and economically significant across a broad cross section of firms. For NYSE/AMEX firms on Compustat over the ten-year period from 1988 to 1997, the error in estimated accruals under the balance sheet approach exceeds 10% of earnings before extraordinary items for over 78% of the firm-years. Most importantly, the bias contaminates computations of so-called discretionary or abnormal accruals, and can lead to erroneously concluding that earnings management exists when no such opportunistic activity is present. We demonstrate this is especially true in studies where the partitioning event is correlated with either mergers and acquisitions or discontinued operations. Other findings show that when discretionary and non-discretionary accruals based on balance sheet accruals estimates are used as regressors in a second stage regression of returns on earnings components, the resulting coefficient bias is likely to yield incorrect statistical inferences about the equality of parameter estimates. Finally, we demonstrate that tests of market mispricing of accruals calculated under the balance sheet approach tend to understate the true extent of the mispricing by roughly 35% due to misclassification of extreme accruals firms.

The remainder of the paper proceeds as follows. Section two explains the balance sheet approach to estimating accruals and how the presumed articulation between changes in balance sheet working capital accounts and income statement accruals breaks down when nonoperating events like mergers and acquisitions, divestitures and foreign currency translations are present. This section also documents the frequency and magnitude of accrual estimation errors by comparing total accruals taken directly from the cash flow statement to estimates derived using the indirect balance sheet method. In section three we use the modified Jones models to evaluate the effect of nonarticulation on estimates of discretionary and nondiscretionary accruals and tests of earnings management. We compare results for two samples of firms: (a) a broad cross-section of NYSE/AMEX firms; and (b) samples of firms affected by one or more of the nonoperating events that contribute to nonarticulation. We also investigate the potential bias in selected studies on earnings management that are confounded by non-articulation events. Section four investigates the relation between returns, discretionary and non-discretionary accruals, and operating cash flows determined using the balance sheet approach versus the cash flow statement approach. Section five demonstrates the effect of measurement error on tests of market mispricing of accruals using the approach outlined in Sloan (1996). Section six summarizes our findings and discusses the implications for prior and future research.

II. The Nonarticulation Problem: Its Frequency, Magnitude and Contributing Factors

2.1 An example of the nonarticulation problem

Much of the literature to date that focuses on accruals uses a balance sheet approach to determine the accruals component of earnings. Specifically, total accruals (TACCt ) are typically calculated as:

TACCt = (D CAt - D CLt - D Casht + D STDEBTt – DEPTNt) (1)

Total accruals are then subtracted from earnings to estimate cash flows from operations (CFOt ) as follows:

CFOt = EBXIt - TACCt (2)

Where D CAt = the change in current assets during period t (Compustat #4); D CLt = the change in current liabilities during period t (Compustat #5); D Casht = the change in cash and cash equivalents during period t (Compustat #1); D STDEBTt = the current maturities of long-term debt and other short-term debt included in current liabilities during period t (Compustat #34); DEPTNt = depreciation and amortization expense during period t (Compustat #14); and EBXIt = net income before extraordinary items and discontinued operations (Compustat #18). Typically all variables are deflated by lagged total assets (TAt-1) to control for scale differences.

The H.J. Heinz 1997 annual report demonstrates the magnitude of the accrual estimation problem caused by nonarticulation between the balance sheet and the cash flow statement and the kinds of events that contribute to this problem. The first column of numbers in Exhibit 1 shows the operating section of Heinz’s cash flow statement for the year ended, April 30, 1997 and the implied directional changes in the working capital accounts after excluding the effects of acquisitions and divestitures. Note that the net change in working capital and its corresponding effect on earnings is + $253.3 million (i.e., income increasing accruals).

The directional changes in the individual working capital accounts taken from Heinz’s comparative balance sheets for 1996-1997 are presented as the second column of numbers. These numbers are presented analogous to the statement of cash flows in that they represent the adjustment to net income to arrive at cash from operations. Notice that the net change in these working capital accounts is only + $13.1 million. Thus, the indirect approach to calculating accruals based on using comparative balance sheets understates Heinz’s working capital accruals by approximately $240.2 million, or 79.6% of Heinz’s 1997 reported net income of $301.9 million.

The main reason for the understatement of Heinz’s accruals (and associated overstatement of operating cash flows) stems form two major divestitures that Heinz made in fiscal 1997 related to its "Project Millenia" reorganization and restructuring program. As shown on the cash flow statement and detailed in footnotes to their annual report, Heinz divested of its New Zealand ice cream business and its U.K. real estate business in 1997. Accordingly, a portion of the decrease in the working capital balance sheet accounts relates to these divestitures that would erroneously be shown as income decreasing accruals under the balance sheet approach to estimating accruals.

In contrast to divestitures of on-going businesses that introduce a negative bias to estimated accruals, mergers and acquisitions introduce a positive bias to estimated accruals using the approach in eqn. (1). Heinz reported cash outflows (net of cash acquired) of $208.4 million in 1997 for acquisitions of several businesses accounted for under the purchase method. A portion of this "Investing Activity" cash outflow would most likely contribute to a positive increase in working capital accounts that did not have a corresponding positive effect on accrual earnings.

Finally, Heinz has numerous foreign subsidiaries whose statements are translated using the current rate approach specified in SFAS No. 52. If the dollar falls (rises) in relation to the functional currencies of these subsidiaries, this change would result in increases (decreases) in balance sheet accounts that would not have a corresponding effect on accruals [Huefner et al.(1989)]. Unlike divestitures and acquisitions where one can reliably sign the direction of the bias in accruals estimated via eqn. (1), the direction of the bias due to foreign currency adjustments is indeterminate. The bias in estimated accruals under the balance sheet approach would depend on whether the dollar strengthened or weakened relative to the local currency of the countries in which a company operates.

While there are no doubt other reasons for nonarticulation (e.g., accounting changes and reclassifications that affect current accounts), we believe that mergers and acquisitions, divestitures and foreign currency translation of foreign subsidiary account balances are likely to be the most important and most pervasive factors contributing to the nonarticulation problem. Accordingly, the remainder of the paper focuses on understanding how these transactions affect the estimation of accruals and cash flows using the balance sheet approach reflected in eqn. (1) and (2) above, which has been the dominant approach used in the literature to date.

2.2 Estimating the severity of the nonarticulation problem

Our sample is comprised of all NYSE/AMEX firms on the Compustat Primary, Supplementary and Tertiary Annual Industrial File and Research File with requisite balance sheet and earnings data to compute accruals according to eqn. (1). Accruals are determined for each year over the ten-year period from 1988 – 1997 resulting in a total sample of 14,558 firm-years.

To provide some evidence on the severity of the nonarticulation problem, we first calculate accruals using the balance sheet approach (TACCbs) as shown in eqn. (1). We next calculate accruals directly from the cash flow statement as follows (firm and time subscripts are suppressed for convenience):

TACCcf = EBXI – CFOcf (3)

where TACCcf = the total accrual adjustments provided on the cash flow statement under the indirect method; EBXI = earnings before extraordinary items and discontinued operations (Compustat #123); and CFOcf = operating cash flows (from continuing operations) taken directly from the statement of cash flows (Compustat #308 - Compustat #124).

Finally, we calculate the difference in accruals estimated under the balance sheet approach given in eqn. (1) and the correct accrual amount given in eqn. (3) for each firm and scale by alternative deflators as follows:

DIFF = TACCbs - TACCcf / ç Deflatorç (4)

where TACCbs is determined according to equation (1) and the alternative deflators are the absolute value of EBXI, TACCbs, or total assets at the beginning of the year (TAt-1).

Table 1 provides summary statistics for these differences aggregated across the ten-year sample period for the full sample. Because extreme outliers arise when using certain deflators, the top and bottom one percent of each ratio are omitted from the univariate statistics resulting in 14,266 observations. Panel A presents comparisons for total accruals while Panel B provides comparisons for operating cash flows. The mean (median) total accrual based on the balance sheet approach (hereafter, TACCbs) is –3.81% (-3.94%) of lagged total assets (TAt-1). The correct total accruals taken from the cash flow statement (hereafter, TACCcf) have a mean (median) value of –4.64% (-4.49%). As shown in previous research, total accruals tend to be negative (i.e., income decreasing) primarily due to non-current accruals for depreciation and amortization. The mean, median and inter-quartile range of the distribution suggest that the traditional balance sheet approach to estimating accruals introduces a positive bias to accruals and a negative bias to estimated cash flows from operations. At least part of this positive bias arises from the exclusion of non-current accruals in our balance calculation of accruals, which are often special item accruals that are on average negative.

Because some events contributing to nonarticulation are likely to introduce a positive (negative) bias to accrual (cash flow) estimates (e.g.,merger or acquisition) while other events are likely to introduce biases in the opposite direction (e.g., divestitures), we take the absolute value of the difference in accrual (cash flow) estimates scaled by TAt-1, EBXI and TACCbs. The median absolute value of the difference is 1.79% of total assets. This difference may seem small at first glance. But when benchmarked against the fact that total accruals are in the range of 4.0% to 4.5% of total assets, it is clear the balance sheet approach to estimating accruals introduces non-trivial measurement error and bias into accruals estimates. When benchmarked against earnings or total accruals, the error introduced by the balance sheet approach is even more dramatic. The median difference in accrual estimates is 36.44% of EBXI and 38.50% of TACCbs. For operating cash flows, the median difference is 21.79% of CFObs.

Table 2 presents similar comparisons to those in Table 1 for those firm-years affected by one of the three contributing factors to nonarticulation noted earlier. Panel A presents results for those firm-years where a firm was involved in a merger or acquisition, Panel B presents results for firm-years with divestitures (discontinued operations), Panel C presents results for firms with foreign operations, and Panel D presents results for firms without any of the three non-articulation events. To determine observations that are affected by one of the three nonarticulation events, we use proxies that are available on Compustat. Mergers and acquisitions are determined by examining annual footnote code #1, which reflects whether a merger or acquisition impacts current sales. A firm is considered to have discontinued operations if the absolute value of discontinued operations (Compustat #66) exceeds $10,000. Similarly, a firm is considered to have foreign operations if the absolute value of the Foreign Currency Adjustment Account (Compustat #150) exceeds $10,000.

Consistent with our priors, the mean, median and inter-quartile range of TACCbs values for the merger and acquisition sample are less negative (i.e., positively biased) than the properly measured TACCcf amounts. The median positive bias in estimated accruals under the balance sheet approach is 26.78% (37.49%) of EBXI (TACCbs). For one-quarter of the firms in this sample, the bias exceeds 91% (116%) of EBXI (TACCbs).

The results for the discontinued operations sample (Panel B) reveal the expected negative bias in estimated accruals under the balance sheet approach. The mean, median and inter-quartile range values for the scaled TACCbs values are consistently more negative than for the TACCcf amounts. As shown, the median bias is considerably smaller than that for the merger and acquisition sample (-0.25% of TA, -5.60% of EBIX and -5.84% of TACCbs). However, for the bottom quartile of firms, the negative bias is rather substantial measuring –3.81% of TA, -99.90% of EBIX and –60.06% of TACCbs.

At first glance, results for the foreign operations sample in Panel C suggest that the TACCbs estimates tend to be positively biased. The median difference is 0.45% of TA, 7.05% of EBXI and 9.03% of TACCbs. Yet when compared to benchmark firms in Panel D that do not have any of these three events, a Wilcoxan signed rank test shows that there is not a significant difference between these firms and firms with foreign operations. The inter-quartile range in Panel C indicates less skewness in the distribution of differences for this sample than for the other two samples, consistent with our conjecture that foreign currency translation can induce both positive and negative bias in TACCbs estimates depending on how the dollar moves in relation to the local currencies of the countries in which the firms operate.

The univariate results presented in Tables 1 and 2 do not control for the fact that in any given year, firms might have more than one of the three events affecting the articulation between the balance sheet, income statement and the statement of cash flows. Thus, to account for this potential overlap, Table 3 provides multivariate estimates of the average bias in estimated accruals induced by each of the three events noted above. The first model regresses DIFF/TAt-1 on three indicator variables, DMERGER, DDISC-OP, and DFC, each of which equals one in firm-years in which mergers and acquisitions, discontinued operations, or foreign currency translations occur, respectively. The benefit to this approach is that the average bias can be examined after controlling for the other non-articulation events. Model 2 is similar to the first model, but also adds an indicator variable for significant mergers and acquisitions.

Results in Table 3 show first that there is a significantly positive intercept. Thus the balance sheet estimation method tends to induce a positive bias across all firms, before considering non-articulation events. This is likely due to the omission of non-current accruals other than deprecation and amortization when computing total accruals using the balance sheet approach. Turning to the nonarticulation events, mergers and acquisitions induce an upward bias in balance sheet-based estimates of accruals of approximately 1.5% of total assets. In contrast, discontinued operations induce a downward bias of approximately -1.4% of total assets, and foreign currency translations have a smaller negative bias of approximately -0.4% of total

assets. Moreover, Model 2 demonstrates that large mergers and acquisitions induce an incremental bias (relative to ‘small’ mergers and acquisitions) of 3.2% of total assets, for a total bias of approximately 4.64% of total assets. Because of the small number of large merger firms relative to the total merger subsample (56 larger merger firms compared to 2991 merger firms in total), the coefficient on the small mergers in model 2 only drops from 1.47% to 1.42%.

Finally, to provide some sense of the pervasiveness of the nonarticulation problem caused by the three events noted above, Figure 1 plots the percentage of Compustat firms affected by each of these events over the ten-year period from 1988 to 1997. The percentage of Compustat firms involved in a merger or acquisition has increased steadily from a low of roughly 14% in 1991 to slightly over 27% in 1997. The percentage of firms with material foreign subsidiaries has remained fairly steady throughout the sample period ranging from 18% to 21% of Compustat firms. Firms reporting divestitures (discontinued operations) ranges from just over 15% in 1988 to around 9% in 1997.

The percentage of Compustat firms having one or more of the three events that introduce error in TACCbs estimates is shown in the top line of Figure 1a. Clearly, a significant portion of Compustat firms are affected, with the proportion ranging from a low of 38.6% in 1991 to 46.5% in 1997. Using 10% of ê EBXI ê as a materiality threshold, we find that the absolute value of the difference between TACCbs and TACCcf exceeds this threshold for 78.4% of the firms on Compustat over the 1988 to 1997 time frame.

Figure 1b depicts a time series plot of the absolute value of the difference (deflated by total accruals) between accruals measured using the balance sheet and the cash flow statement approach. A cursory examination of the plot reveals that the average error resulting from a balance sheet approach appears to follow the same pattern as the relative frequency of nonarticulation events presented in Figure 1a. Specifically, both the frequency of nonarticulation events in Figure 1a and the degree of measurement error in Figure 1b decrease from 1988-1991, and then follow more of a gradual upward trend until 1997.

Collectively, the results reported in this section suggest that non-operating events or transactions (i.e., mergers and acquisitions, divestitures and foreign operations) can cause significant errors in accruals and cash flows from operations estimated using the indirect balance sheet approach. Moreover, the number of firms affected by one or more of these activities represents a nontrivial proportion of the firms that comprise the Compustat files. Thus, a considerable body of literature to date that utilizes balance sheet-based accruals estimates suffers from a potentially large measurement error problem. The following sections evaluate how the errors embedded in TACCbs estimates affect inferences in studies where accruals are the major object of interest.

III. Estimating Discretionary and Nondiscretionary Accruals and Detecting Earnings Management

3.1 Bias in discretionary accrual calculations

McNichols and Wilson (1988) outline a general discretionary accruals framework that is the foundation for most earnings management studies in accounting. In the model, total accruals are partitioned into a discretionary (DACC*) and non-discretionary (NDACC*) component, such that:

TACC* = NDACC* + DACC* (5)

Since DACC* is unobservable, it is typically estimated using one of several alternative empirical models. The estimate of discretionary accruals (DACC) that emerges from the empirical model inevitably measures the true and unknowable discretionary accruals (DACC*) with error:

DACC = DACC* + h (6)

where h is the measurement error associated with the estimate. Ultimately, the researcher uses this estimate of discretionary accruals to test for earnings management surrounding a particular event. Examples of these events are numerous, but include such diverse events as seasoned equity offerings, proxy contests, stock-for-stock mergers, management buyouts, asset write-downs, and management forecasts. Typically, the test is conducted by regressing discretionary accruals on a partitioning variable (PART), which is a dummy variable equaling one in the period(s) in which earnings management is hypothesized to occur. Thus, a theoretical model to test for earnings management can be represented as follows:

DACC* = a + b PART + e (7)

Where a estimates average discretionary accruals across all firms, and a + b estimates the average discretionary accruals for the experimental group. The significance of b is used to draw inferences about the presence of earnings management (or lack thereof). However, because a discretionary accrual proxy, DACC, is used instead of DACC*, McNichols and Wilson (1988) demonstrate that equation (7) can be rewritten as follows:

DACC = a + g PART + n , (8)

where g = b + r PART, h * s h /s PART

= b + bias in g

Hence, as noted in McNichols and Wilson (1988), given measurement error in DACC, the coefficient used to test for the presence of earnings management will be biased. Moreover, this bias will be (1) increasing in the correlation between h and PART, (2) increasing in the variance of h , and (3) decreasing in the variance of PART. More importantly, with a significant bias in the discretionary accrual estimate, one could erroneously conclude there is earnings management (i.e. observe non-zero values of g ), when, in fact, earnings may not be managed at all (i.e. b = 0). Alternatively, accruals estimates biased in the opposite direction of the hypothesized earnings management could yield insignificant results when, in fact, accruals were used to manage earnings.

3.2 Empirically estimating bias in tests of earnings management

As shown in equation (8), empirically assessing the degree of bias in a test of earnings management requires an estimate of h , the measurement error in the estimate of discretionary accruals. One source of measurement error in DACC is that induced by using a balance sheet approach to estimating accruals versus using the actual accruals available from the cash flow statement. The fact that in the post-SFAS 95 period we can precisely measure the error in TACCbs allows us to estimate the bias arising from the use of balance sheet accruals in tests of earnings managment. Because we only have ten years of post-SFAS 95 data available, a cross-sectional version of modified Jones model is used. Thus, the following models are estimated by year and industry:

TACCbs = a + b 1(D Rev) + b 2PPE + e bs (10a)

TACCcf = a + b 1(D Rev) + b 2PPE + e cf (10b)

The parameters in equations (10a) and (10b) are estimated over sub-samples of firm-years without a specific non-articulation event (for example, all firm-years without a merger or acquisition or divestiture). The proxies for non-discretionary accruals under the balance sheet and cash flow approach are then computed as follows:

Discretionary accruals are simply computed as total accruals less non-discretionary accruals under both the balance sheet (DACCbs) and cash flow (DACCcf) approaches. By comparing the estimates of discretionary accruals under the balance sheet and cash flow approaches, we can estimate the error in discretionary accruals that result from using a balance sheet approach. Specifically,

h = DACCbs - DACCcf (12)

If the error in TACCbs (i.e. DIFF) is uncorrelated with the regressors, the majority of this error will be captured by the residual, DACCbs (Greene, 1991). Empirically, this turns out to be the case as there is a 0.94 correlation between h and DIFF. Thus, much of the error from a balance sheet approach to estimating accruals, which is induced by non-articulation events, transfers to the discretionary accrual proxy in tests of earnings management.

Equation (8) demonstrated that the magnitude and direction of the bias in a test of earnings management depends on the correlation between PART and h . But as we have already demonstrated, there are at least three non-articulation events that contribute to measurement error in balance sheet accruals estimates: mergers and acquisitions, divestitures, and foreign currency translations. Table 4 presents evidence of the bias in tests of earnings management that arises when PART (the dummy variable used to identify periods of expected earnings management) coincides with each of these three non-articulation events. Panel A displays the standard deviations of the measurement error proxy, h , and the three partitioning variables, PARTmerger, PARTdisc-op, and PARTfc, as well as the correlations between h and each of these partitions. Using equation (8), the magnitude of the bias associated with the three non-articulation events can be computed. This is shown in the right-most column of Panel A. The bias associated with PARTmerger is 1.766% of total assets, which is both statistically and economically significant, given accruals are, on average, approximately 4.5% percent of total assets. The bias associated with discontinued operations is similarly large but in the opposite direction, averaging -1.493% of total assets. The bias associated with foreign currency translations also tends to be negative, but is not as large averaging only -0.294% of total assets.

While Panel A shows evidence of a significant bias entering the calculation of discretionary accruals when using DACCbs , it does not provide direct evidence of the potential impact on statistical inferences in tests of earnings management. To address this issue, Panel B of Table 4 provides results of tests of earnings management (see eqn.(8)) using the three previously identified partitions and discretionary accruals computed under both the balance sheet approach and from the statement of cash flows. By testing for significant discretionary accruals under both approaches, we can examine if any statistical inferences change due to measurement error in discretionary accruals under the balance sheet approach. A priori, we have no reason to believe that there will be significant earnings management associated with any of the three non-articulation events used as partitioning variables. Therefore, when accruals are measured correctly from the statement of cash flows, we expect the coefficient on PART to be insignificantly different from zero.

Discretionary accruals are regressed on each of the three partitioning variables on an annual basis. Additionally, the significance across all years is reported by taking the average of the sampling distribution of the ten individual-year parameter estimates. From Panel A, we expect that the balance sheet estimation method biases the coefficient on PART, especially for merger/acquisition firms and discontinued operation firms. More importantly, however, Panel B demonstrates that the researcher’s inference of whether or not earnings management exists actually changes depending on how the accruals are measured. Specifically, the first two columns of Panel B demonstrate that a partition on mergers and acquisitions shows evidence of significant income increasing earnings management (in 10 of 10 individual years and across all years). However, the same partition using accruals from the statement of cash flows shows no evidence of earnings management. Similarly, the next two columns in Panel B demonstrate that a partition on discontinued operations shows evidence of significant income decreasing earnings management (in 8 of 10 individual years and across all years) when using accruals under the balance sheet approach, while a similar partition using accruals from the statement of cash flows shows no evidence of earnings management. Finally, the last two columns of panel B demonstrate that a partition on foreign currency translation is only moderately biased, with statistically significant earnings management indicated in 3 of 10 years and across all years when, in fact, no earnings management is present.

3.3 Implications for extant earnings management literature.

The results of the previous section have significant implications for extant earnings management studies using a balance sheet approach to estimating accruals. Specifically, the bias in total accruals and the discretionary accruals component could lead a researcher to conclude that significant earnings management exists, when in fact there is none. Given the results of the previous section, this will be most problematic for events suspected to give rise to earnings management that are correlated with either mergers/acquisitions or discontinued operations.

For example, Rees, Gill and Gore (1996) investigate the potential for earnings management associated with asset write-downs using a balance sheet approach to measuring accruals (p. 159, equation 1). The authors hypothesize that if the primary motive for an asset write-down is opportunistic, firms are likely to concurrently manage operating accruals downwards. Accordingly, they test for income decreasing discretionary accruals. Yet, as noted by the authors, the majority of write-downs in their sample are part of an overall firm restructuring. Thus, the partition chosen by Rees, Gill, and Gore (i.e. asset write-downs) is likely to be positively correlated with the presence of discontinued operations. Furthermore, as shown above, discretionary accruals determined under the balance sheet approach are negatively biased for firms with discontinued operations. Therefore, it is predicted that this combination will induce a negative bias to their test of earnings management, which is exactly the predicted direction of the alleged earnings management.

To empirically check the impact of this negative bias, we collect a sample of asset write-downs from 1988-1993 using the same data source (NAARS), search string, and selection criteria as Rees et al. (1996, pp.158-159). This procedure results in a sample of 307 firm-year observations. Operating accruals are as defined as in Rees et al. (1996) whereby the definition only encompasses working capital accruals and depreciation expense. Finally, the control sample consists of all firms within the same two-digit SIC code in the year of the write-down. The test for abnormal accruals is then conducted using a separate regression for each sub-sample of observations, where the sub-sample consists of a sample and a control group, as follows:

TACCt = a 0 + a 1(D Revt ) + a 2(PPEt ) +a 3(CFOt ) +b 1(PARTt ) + e t (13)

where PART equals one for firms with an asset write-down, and zero otherwise.

The original results from the Rees et al. study (Table 3, p.164) show that abnormal operating accruals in the year of the write-down (i.e. the average coefficient on PART) are

-3.05% of total assets. Additionally, in their 120 separate cross-sectional regressions run using equation (13), the coefficient on PART is negative 67.5% of the time. Using the balance sheet approach and the current sample, we find results that are very similar to those reported in Rees et al., with estimated income-decreasing abnormal accruals of approximately –3.11% of total assets, and negative abnormal accruals in 66.2% of our 139 cross-sectional regressions. When operating accruals are taken directly from the statement of cash flows, however, the results look dramatically different. In the year of the asset write-down, abnormal operating accruals are only –1.36% of total assets, less than half the size estimated by Rees et al. Moreover, abnormal accruals are negative only 54.4% of the time, which is not significantly different from 50% using a binomial test. Thus, it is evident that the presence of discontinued operations can have a significant impact on the magnitude of income-decreasing discretionary accruals estimated via the balance sheet approach, and can potentially bias tests of earnings management towards rejection of the null.

Other studies of earnings management subject to similar concerns about negative bias in accruals estimates include Perry and Williams (1994) and Defond and Subramanyam (1998). Both of these studies use a balance sheet estimation approach, contain a disproportionate number of financially distressed firms and hypothesize income decreasing earnings management. In these studies, a high proportion of sample firms deemed to be engaged in earnings management are also likely to be divesting of unprofitable segments or divisions. As we have shown, this divestiture activity induces a negative bias to TACCbs estimates that is in the same direction as the hypothesized earnings management, thus confounding their hypothesis tests.

Similar concerns can be raised about studies that test for income-increasing earnings management around events that are positively correlated with mergers and acquisitions. For example, Teoh, Welch, and Wong (1998) and Rangan (1998) examine earnings management in anticipation of seasoned equity offerings (SEOs). These studies investigate whether earnings management might contribute to the long-run underperformance of SEOs previously identified in the finance literature (e.g. Loughran and Ritter 1995). While on the surface, there is no obvious relation between mergers and acquisitions and SEOs, we find that firms listed by Securities Data Corporation as participating in SEOs are 55.1% (64.7%) more likely to be involved in a merger or acquisition in the year prior to (in the year of) an SEO than the population in general. Thus, an estimate of discretionary accruals in this sub-sample of firms is more likely to be upward biased relative to the population in general, due to the fact that there is a higher proportion of merger and acquisition firms in this sub-sample.

To investigate whether this bias impacts any inferences, Table 5 examines the impact of the balance sheet estimation approach for 775 firms conducting seasoned equity offerings from 1988-1997. Teoh, Welch, and Wong (1998) find that, on average, accruals are managed upwards in the year prior to and in the year of a seasoned equity offering. Panel A re-examines this issue by comparing the discretionary accruals of the SEO sample to discretionary accruals of a control sample in the year prior to a seasoned equity offering. The first line of Panel A reveals that under the balance sheet approach, discretionary accruals are significantly larger in period t-1 for the firms that issue a seasoned equity offering in period t as compared to a set of control firms (DACCbs,SEO – DACCbs,Control = 0.73, t=2.90). Using the cash flow approach to measuring accruals, however, reveals no significant difference in discretionary accruals between the SEO firms and the control firms (DACCcf,SEO – DACCcf,Control = 0.04%, t=1.13). Thus, the inference as to whether firms manage earnings upward in the year prior to a seasoned equity offering changes depending on whether the balance sheet or cash flow approach is used to estimate accruals.

Panel B demonstrates that within the sample of SEO firms, it is those with mergers and acquisitions that are causing the measure of discretionary accruals to be significantly positive under the balance sheet approach. For the 251 firms involved in a merger or acquisition, mean abnormal accruals are 1.69% of total assets. Conversely, for the 524 firms not involved in a merger or acquisition, discretionary accruals are –0.03% of total assets. Note that the magnitude of estimated discretionary accruals for the non-merger firms in Panel B is comparable to the discretionary accruals of 0.04% reported in Panel A for the SEO sample as a whole when the cash flow approach is used. Thus, one important implication of this result is that when cash flow statement data are not available to determine accruals (e.g. prior to 1988), a viable alternative is to separately analyze those firms involved in non-articulation events. Comparison of results for these firms with those not impacted by non-articulation events can be used to determine the potential contamination cause by balance sheet accrual estimation.

In summary, our results suggest that inferences regarding the existence and magnitude of earnings management in anticipation of SEOs can change when the balance sheet approach is used to estimate accruals and the sample contains a significant number of firms involved in mergers and acquisitions. Moreover, the underperformance of SEO stocks which Teoh et al. (1998) and Rangan (1998) attribute to the market corrections related to earnings management is likely to be confounded by the well-documented long-run underperformance of firms involved in mergers and acquisitions (see, for example, Agrawal and Jaffe 1999).

IV. Tests Using Discretionary and Non-Discretionary Accruals as Explanatory Variables

Another stream of literature that is potentially affected by measurement error in accruals estimates includes studies using discretionary and non-discretionary accruals as explanatory variables in a second-stage regression with returns as the dependent variable. The basic question addressed by such studies is whether discretionary accruals are priced differently from nondiscretionary accruals or cash flows. For example, Guay, Kothari, Watts (1996) and Subramanyam (1996) regress returns on non-discretionary earnings (operating cash flows plus non-discretionary accruals), discretionary accruals, non-discretionary accruals, and operating cash flows all determined using a balance sheet approach. As shown in the previous section, however, each of these variables will embed some (or all) of the error resulting from a balance sheet estimation approach. When these variables are used as regressors and the measurement errors embedded in these measures are correlated across variables, the resultant coefficient estimates are biased, but the direction of the bias is difficult to predict (Greene 1991, p.284).

To provide some evidence on the impact of this measurement error, we estimate the same series of regressions as those used by Subramanyam (1996). As in the previous section, discretionary accruals are measured using the modified Jones model. Table 6 presents the results of estimating a series of equations using both the balance sheet and cash flow estimation approaches. In should be emphasized that while our approach is the same approach used by Subramanyam, our sample periods are largely non-overlapping (1973-1993 vs. 1988-1997) and hence the results may not be directly comparable.

Panel A of Table 6 shows the basic regression of returns on accruals and cash from operations. Under a balance sheet approach, the coefficient on accruals is upward biased by about 10.4% (1.06 versus 0.96), and the coefficient on cash flows is downward biased by about 7.1% (1.06 vs. 1.12). More importantly, using a balance sheet approach a test of equality of the coefficients would lead the researcher to conclude there is no difference between the coefficients on accruals and cash flows (p-value=0.987), while using a cash flow approach shows a significant difference (p-value = 0.022).

Panel B examines the relation between size-adjusted returns and non-discretionary earnings and discretionary accruals. Here, the coefficient on non-discretionary earnings is downward biased by only 6.9% (1.08 vs.1.16), while the coefficient on discretionary accruals (DACC) is upward biased by approximately 23.5%(1.00 vs. 0.81). Again, a t-test on the equality of coefficients using the balance sheet estimation of accruals yields an insignificant difference between the coefficient on NDE and DACC (p-value = 0.44), while using accruals from the cash flow statement yields a statistically significant difference between these coefficients (p-value < 0.01).

Panel C breaks down earnings into cash flow from operations (CFO), non-discretionary accruals (NDACC), and discretionary accruals (DACC). In this case, the coefficients on NDACC and CFO are not biased by large amounts (8.9% and 6.3% respectively), but the coefficient on DACC is upward biased by approximately 24% (0.98 vs. 0.79). Tests of equality of parameter estimates are largely similar, although a test of the difference between the coefficient on DACC and the coefficient on CFO is insignificant under a balance sheet estimation approach (p-value = 0.34) and statistically significant under a cash flow approach (p-value = 0.002). In summary, when discretionary and non-discretionary accruals based on balance sheet estimates of accruals are used as regressors in a second stage regression, the coefficients are biased to varying degrees and the bias can contaminate statistical inferences made on the basis of these coefficient estimates.

V. Tests of Market Mispricing of Accruals

Tests of market mispricing of accruals [Sloan (1996), Collins and Hribar (2000) and Xie (1999)] are typically implemented by taking portfolio positions based on ranked values of accruals (scaled by lagged total assets). Ten equal sized portfolios are formed by ranking firms from the most negative accruals (Portfolio 1 = PORT1) to the most positive accruals (Portfolio 10 = PORT10). Zero investment hedge portfolios are formed by taking a long position in PORT1 firms and a short position in PORT10 firms. Evidence of market mispricing is indicated if the hedge portfolio yields positive abnormal returns net of transactions costs over the subsequent holding period.

In the present context, we are concerned with how measurement error in TACCbs affects the ranking of firms conditional on accruals estimated under the balance sheet approach, and in particular, firms assigned to the extreme accruals decile portfolios. Panel A of Table 7 provides evidence on the percentage of firm-years that fall into a different decile ranking using TACCbs estimates of accruals compared to the correct TACCcf accruals measurements. Because events causing nonarticulation errors in TACCbs can cause rankings to differ in either direction, we report the percentage of firm-years that change decile rankings irrespective of direction. Results are presented for all firm-years and for firm-years that fall into the extreme deciles only based on TACCbs.

Across all firm-years, we find that only 38.2% of the time do the TACCbs accrual decile rankings agree with the TACCcf rankings. Thus, 61.8% (100% - 38.2%) of the observations fall into a different decile ranking when measured correctly (TACCcf) as compared to using the balance sheet approach (TACCbs) to estimating accruals. Interestingly, 27.9% of the observations shift by at least two deciles when measured by TACCcf compared to TACCbs. More relevant to tests of market mispricing of accruals, we find that 38.7% (100% - 61.3%) of those observations assigned to the extreme accruals deciles (i.e., decile 1 or decile 10) using TACCbs, are misclassified. Thus, we conjecture that studies which rely on TACCbs measures to form hedge portfolios [e.g., Sloan (1996) and Xie (1999)] are likely to understate the extent of market mispricing of accruals because a non-trivial proportion of the firms are misclassified as "extreme" accruals firms.

Panel B of Table 7 examines the accrual portfolio misclassification as a result of the three nonarticulation events described earlier. Given the bias documented for these nonarticulation events, the misclassification is as expected. Specifically, 513 firms involved in a merger or acquisition end up in the highest accrual portfolio, but 284 (55.4%) of those firms are misclassified and fall into a lower accrual decile under the cash flow approach. The misclassification of high accrual firms is larger, both in absolute number and in percentage terms, than is the number of merger firms that are misclassified in the lowest accrual decile (83 firms, 49.7%). The opposite effect is observed for firms with discontinued operations. Here, 314 firms with discontinued operations fall into lowest accrual portfolio under the balance sheet approach, but 190 (60.5%) of these firms are misclassified and are classified into a higher accrual decile under the cash flow approach. Again, the misclassification of large negative accrual firms is greater, both in absolute number and in percentage terms, than the number of discontinued operation firms that are misclassified in the highest accrual decile (61 firms, 49.2%). Firms with foreign operations have a slightly larger proportion of firms in the lowest accrual portfolio, with 253 firms falling into the lowest accrual portfolio. Again, 125 (49.4%) of these firms are misclassified, whereas in the highest accrual portfolio only 82 firms (39.0%) are misclassified.

5.1 Assessing the impact of portfolio misclassification on the accrual anomaly.

To assess the effect of measurement error in TACCbs on tests of accruals mispricing, we replicate the hedge portfolio analysis in Sloan (1996) using annual data and the hedge portfolio analysis in Collins and Hribar (2000) using quarterly data. We construct zero-investment hedge portfolios by taking a short position in PORT10 firms (highest decile of firms with most positive accruals) and a long position in PORT1 firms (lowest decile of firms with most negative accruals). The analysis is repeated twice in both the annual and quarterly settings: once using decile rankings based on TACCbs measures (as in Sloan (1996)), which are contaminated by the nonarticulation problems noted above, and again using the correct TACCcf measures (as in Collins and Hribar (2000)). Our sample is comprised of all NYSE/AMEX firms on the Compustat Primary, Supplementary and Tertiary Annual Industrial File and Research File with required earnings and accruals data over the ten-year period from 1988 to 1997.

Figure 2 replicates Sloan’s (1996) results and displays the average size-adjusted returns accruing to both the TACCbs and the TACCcf hedge portfolios cumulated over the twelve months following the release of the annual report. As conjectured, the average annual size-adjusted return accruing to the TACCcf hedge portfolios is 11.88% and is roughly 36% higher than the 8.72% average return earned by the TACCbs-based strategy. Thus, when measured correctly, the accruals-based hedge portfolio yields much stronger evidence of market mispricing than documented in the previous literature.

Figure 3a replicates the accruals-based hedge portfolio results in a quarterly setting for the 36 quarters from 1988 to 1996 in Collins and Hribar (2000). The average size-adjusted returns are measured over the two quarters subsequent to portfolio formation and are based on using the correct quarterly accruals measures from the statement of cash flows. As shown, the average two-quarter return is 5.56% or an annualized return of 11.12%.

In contrast, the average two-quarter abnormal return accruing to hedge-portfolios based on TACCbs presented in Figure 3b are much smaller and display considerably more variability. As shown, the average two-quarter return is 2.99%, or an annualized return of 5.98%. Note that the TACCbs-based strategy yields negative returns in 12 of the 36 quarters while the TACCcf-based strategy yields negative returns in only 5 quarters and they are much smaller in magnitude. Again, these results indicate that the measurement error introduced when using balance sheet- based accruals estimates can substantially bias tests of market mispricing towards zero.

VI. Summary and Research Implications

Accruals measurement plays a central role in a considerable body of research in accounting. Much of this research relies on estimates of accruals based on the presumed articulation between changes in balance sheet working capital accounts and accrued revenues and expenses on the income statement. However, this presumed articulation breaks down when non-operating events/activities like mergers and acquisitions, divestitures and translation of foreign subsidiary accounts are present. This paper demonstrates that the frequency and magnitude of errors introduced when using balance sheet-based accruals estimates can be substantial.

Our findings have implications for studies designed to detect earnings management, the estimation of discretionary and nondiscretionary accruals, and the market’s pricing (and mispricing) of these accruals components. The most significant finding relates to studies examining earnings management. The prevalence of the balance sheet approach to estimating accruals in these studies suggests that their results should be reevaluated in light of the potential impact of mismeasured accruals. This is especially pertinent in cases where the partitioning variable used to identify instances of earnings management is correlated with mergers and acquisitions or discontinued operations.

Our results suggest that many studies concerned with possible differential pricing implications of discretionary and nondiscretionary accruals are adversely affected by measurement errors introduced by the balance sheet approach to accruals measurement. In particular, tests that discretionary and nondiscretionary accruals are priced the same are less likely to be rejected when accruals are measured using the balance sheet approach as compared to when they are measured correctly from the cash flow statement.

Finally, our findings suggest that tests of market mispricing of accruals suffer from significant classification errors of "extreme accruals" firms when accruals are estimated using the balance sheet approach. Using correctly measured accruals, we find that the degree of mispricing is significantly greater than that documented using balance sheet accruals.

Going forward, we expect that accruals will continue to be the main object of interest in a broad cross-section of literature in accounting. Our results suggest that it would be prudent for researchers to rely on accruals measures taken directly from the cash flow statement. If the research context requires use of pre-SFAS 95 data, additional specification tests should be conducted to control for possible errors in accruals measurements introduced by nonarticulation events. Failing to do so may lead to unreliable tests and unwarranted inferences.

 

 

 

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Exhibit 1. H.J. Heinz Company and Subsidiaries

Comparison of Accruals Determination from Change in

Balance Sheet Accounts versus Cash Flow Statement

Fiscal Year Ending April 30, 1997

 

Fiscal Year Ended April 30,1997

(Dollars in thousands)

Statement of Cash Flows

Income Effect

Adjustments to arrive at CFO based on changes in the Balance Sheet

Income Effect

         

OPERATING ACTIVITIES:

       

Net income

$ 301,871

 

$301,871

 

Adjustments to reconcile net income to cash

provided by operating activities:

       

Depreciation

244,388

¯

 

Amortization

96,102

¯

   

Deferred tax (benefit) provision

(33,450)

­

   

Gain on sale of New Zealand ice cream business and U.K. real estate

(85,282)

­

   

Provision for restructuring

647,200

¯

   

Other items, net

(42,527)

­

   

Changes in current assets and liabilities, excluding effects of acquisitions and divestitures:

       

Receivables

74,445

¯

89,000

¯

Inventories

(5,329)

­

61,452

¯

Prepaid expenses and other current assets

5,094

¯

(36,809)

­

Accounts payable

18,003

¯

(5,183)

­

Accrued liabilities

(182,555)

­

(42,063)

­

Income taxes

(162,962)

­

(79,538)

­

         

Working Capital Accruals

+253,304

+13,141

Cash from Operations

874,998

     
         

 

Table 1. Summary statistics for accruals and operating cash flows computed under the balance sheet approach (bs) versus cash flow statement approach (cf): 14,266 firm-years over the years 1988-1997.

           

Fractiles of

Distribution

Panel A: Total Accruals

Mean

Std.

Dev.

.25

.50

.75

               

TACCbs / TAt-1

   

-3.81%

6.71%

-7.47%

-3.94%

-0.18%

TACCcf / TAt-1

   

-4.64

6.67

-8.15

-4.49

-0.85

ç DIFF / TAt-1 ç

   

3.17

4.06

0.75

1.79

3.83

ç DIFF / EBXI ç

   

112.75

272.68

13.06

36.44

97.22

ç DIFF/ TACCbs ç

   

108.93

250.12

14.66

38.50

96.35

Panel B: Operating Cash Flows

         
                 

CFObs / TAt-1

   

7.80

8.28

3.21

8.19

12.93

CFOcf / TAt-1

   

8.59

7.07

4.23

8.68

13.11

ç DIFF / TAt-1 ç

3.17

4.06

0.75

1.79

3.83

ç DIFF / CFObs ç

   

66.81

147.19

8.31

21.79

61.62

TACCbs (TACCcf) = Total accruals based on the balance sheet (cash flow) statement approach.

DIFF = TACCbs - TACCcf = CFObs - CFOcf

CFObs (CFOcf) = Cash from operations, based on the balance sheet (cash flow) statement approach.

TAt-1 = Total assets at t-1.

EBXI = Earnings before extraordinary items and discontinued operations.

ç * ç = Absolute value operator.

 

Table 2. Summary statistics for accruals computed under the balance sheet approach (bs)

versus cash flow statement approach (cf) by type of nonoperating activity: 1988-1997. 14,266 firm-years over the years 1988-1997.

         

Fractiles of

Distribution

Panel A: Merger & Acquisition Sample (2,991 firm-years)

Mean

Std.

Dev.

.25

.50

.75

TACCbs / TAt-1

 

-1.56%

6.75%

-5.47%

-1.92%

2.23%

TACCcf / TAt-1

 

-3.39

6.18

-6.53

-3.28

0.18

DIFF / ç TAt-1 ç

 

2.02

5.19

-0.58

1.57

4.30

DIFF / ç EBXI ç

 

59.05

241.67

-10.13

26.78

91.59

DIFF/ ç TACCbs ç

 

89.76

248.78

-11.37

37.49

116.56

Panel B: Discontinued Operations Sample (1,277 firm-years)

TACCbs / TAt-1

 

-5.55

7.61

-9.75

-5.31

-1.23

TACCcf / TAt-1

 

-5.07

6.99

-8.61

-4.59

-1.10

DIFF / ç TAt-1 ç

 

-0.46

6.43

-3.81

-0.25

2.75

DIFF / ç EBXI ç

 

-14.20

283.05

-99.90

-5.60

61.64

DIFF/ ç TACCbs ç

 

31.29

229.43

-60.06

-5.84

51.31

Panel C: Foreign Operations Sample (2,812 firm-years)

TACCbs / TAt-1

 

-4.01

6.09

-7.31

-4.00

-0.77

TACCcf / TAt-1

 

-4.57

6.14

-7.85

-4.29

-1.27

DIFF / ç TAt-1 ç

 

0.50

4.27

-1.20

0.45

2.24

DIFF / ç EBXI ç

 

19.76

190.54

-22.68

7.05

46.64

DIFF/ ç TACCbs ç

 

40.27

199.09

-26.09

9.03

56.57

Panel D Firms without a non-articulation event (7,233 firm-years)

TACCbs / TAt-1

 

-4.21

6.62

-7.78

-4.27

-0.67

TACCcf / TAt-1

 

-4.94

6.87

-8.51

-4.83

-1.05

DIFF / ç TAt-1 ç

 

0.74

4.01

-0.69

0.53

2.05

DIFF / ç EBXI ç

 

21.82

192.85

-12.61

8.66

43.03

DIFF/ ç TACCbs ç

 

40.67

186.71

-13.29

10.10

48.10

TACCbs (TACCcf)=Total accruals based on the balance sheet (cash flow) statement approach.

DIFF = TACCbs - TACCcf

TAt-1 =Total assets at t-1.

EBXI =Earnings before extraordinary items and discontinued operations.

ç * ç =Absolute value operator.

Table 3. Multivariate tests of the effect of mergers and acquisitions, discontinued operations, and foreign currency translations on the difference between accruals computed under the balance sheet approach and the cash flow statement approach. Based on 14,266 firm years over the years 1988-1997.

Model 1: DIFF/TAt-1 = a + b 1DMERGER + b 2DDISC-OP + b 3DFC + e

Model 2: DIFF/TAt-1 = a + b 1DMERGER + b 2DDISC-OP + b 3DFC + b 4DLARGE_MERGER + e

Coefficient Estimate

(t-statistic)

Model 1

 

Model 2

 

Intercept

0.0077

(16.15)

 

0.0077

(16.16)

 
           

DMERGER

0.0147

(15.95)

 

0.0142

(15.49)

 
           

DDISC-OP

-0.0146

(-10.62)

 

-0.0147

(-10.67)

 
           

DFC

-0.0044

(-4.38)

 

-0.0043

(-4.64)

 
           

DLARGE_MERGER

   

0.0322

(4.21)

 
           

Adj. R2

2.70%

 

2.82%

 
           

DIFF = TACCbs - TACCcf

TAt-1 = Total assets at t-1.

DMERGER = 1 if firm-year contains a merger or acquisition, 0 otherwise.

DDISC-OP = 1 if firm-year contains discontinued operations, 0 otherwise

DFC = 1 if firm-year contains foreign currency gain or loss, 0 otherwise

DLARGE_MERGER = 1 if firm-year contains a significant merger or acquisition as classified by Compustat,

0 otherwise

Table 4. Annual significance levels of different event partitions under the balance sheet and cash flow approaches to computing accruals. Based on 14,266 firm years over the years 1988-1997.

Panel A: Potential bias in earnings management studies using three different partitions.

   

Standard Deviations (s )

s h / s PART

   

Correlations

(r )

Bias as % TAt-1

(r *s h /s PART)

 

s (h )

0.051

       
 

s (PARTmerger)

0.408

0.1250

r (h , PARTmerger)

0.141

1.766%

 

s (PARTdisc-op)

0.276

0.1848

r (h , PARTdisc-op)

-0.081

-1.493%

 

s (PARTfc)

0.398

0.1281

r (h , PARTfc)

-0.023

-0.289%

Panel B: Tests of earnings management using mergers and acquisitions, discontinued operations, and foreign currency translations as partitioning variables.

BS Model: DACCbs = b 0 + b 1PART + e

CF Model: DACCcf = g 0 + g 1PART + e

   

PARTmerger

PARTdisc-op

PARTfc

 

Year

BS Model (b 1)

CF Model (g 1)

BS Model (b 1)

CF Model (g 1)

BS Model (b 1)

CF Model (g 1)

 

1988

2.09%*

0.37%

-0.16%

0.33%

-1.01%*

-0.39%

 

1989

1.97%**

-0.06%

-2.87%**

-0.19%

-0.37%

0.04%

 

1990

1.84%**

0.23%

-2.35%**

-0.81%

0.41%

0.17%

 

1991

2.12%**

0.31%

-1.37%**

-0.23%

-0.26%

-0.04%

 

1992

1.71%**

0.13%

-1.49%**

0.06%

-0.74%**

-0.37%

 

1993

1.50%**

-0.11%

-2.13%**

-0.42%

-0.91%**

-0.06%

 

1994

1.73%**

-0.20%

-0.72%

0.17%

0.13%

-0.13%

 

1995

1.42%**

-0.28%

-1.08%*

0.33%

0.18%

0.23%

 

1996

2.46%**

0.55%

-0.91%*

0.24%

-0.51%

0.04%

 

1997

1.38%**

-0.19%

-1.46%**

-0.27%

0.67%

0.76%*

               
 

All Years

1.82%**

0.08%

-1.45%**

-0.08%

-0.24%*

0.12%

               

* Significant at the a =0.05 level, two tailed test.

** Significant at the a =0.01 level, two tailed test

 

Table 5. Testing for Income-Increasing Discretionary Accruals in the year prior to a Seasoned Equity Offering (SEO) using the Balance Sheet and Cash Flow Approaches. The sample includes 775 firms involved in SEOs during 1988-1997, and a matched sample of control firms based on year t-1 net income. All values are reported as a percent of total assets.

Panel A: Differences in discretionary accruals between firms involved in an SEO and a control sample of firms that are matched on net income in the pre-offering year.

   

SEO sample

Control

Difference

t-statistic

Balance Sheet Approach

0.63%

-0.10%

0.73%

2.90**

           

Cash Flow Approach

0.04%

-0.19%

0.22%

1.13

           

Panel B: Differences in discretionary accrual calculations using the Balance Sheet Approach when SEO firms are involved in mergers and acquisitions

     

N

DACCbs

t-statistic

Firms Involved in a Merger/Acquisition

251

1.75%

3.95**

           

Firms not Involved in a Merger/Acquisition

524

0.08%

0.09

           
     

Difference

-1.72%

3.59**

           

** Significant at the a =0.01 level.

 

Table 6. Cross-sectional regressions of size-adjusted returns on accruals, discretionary accruals, non-discretionary accruals, and cash from operations. Discretionary accruals as the residual from a modified Jones model. The ‘bs’ subscript refers to accruals computed using a balance sheet approach, while the ‘cf’ subscript refers to accruals computed using a cash flow approach.

Panel A: Returns on Accruals and Cash Flows

Model 1: SRET = a + b 1TACCbs + b 1CFObs + e

Model 2: SRET = a + b 1TACCcf + b 1CFOcf + e

   

a

b 1

b 2

   

Model 1

 

-0.02

(-3.21)

1.06

(14.44)

1.06

(12.50)

   

Model 2

 

-0.03

(-4.42)

0.96

(14.79)

1.12

(11.63)

   

Model 1 Test b 1= b 2: p-value = 0.987 Model 2 Test b 1= b 2: p-value = 0.022

Panel B: Returns on non-discretionary earnings and discretionary accruals

Model 1: SRET = a + b 1NDEbs + b 2DACCbs + e

Model 2: SRET = a + b 1NDEcf + b 2DACCcf + e

   

a

b 1

b 2

   

Model 1

 

-0.02

(-3.97)

1.08

(14.94)

1.00

(10.77)

   

Model 2

 

-0.02

(-4.72)

1.16

(15.71)

0.81

(8.04)

   

Model 1 Test b 1= b 2: p-value = 0.44; Model 2 Test b 1= b 2: p-value = 0.001

Panel C: Returns on non-discretionary earnings and discretionary accruals

Model 1: SRET = a + b 1NDACCbs + b 2DACCbs + b 3CFObs + e

Model 2: SRET = a + b 1NDACCcf + b 2DACCcf + b 3CFOcf + e

   

a

b 1

b 2

b 3

 

Model 1

 

-0.01

(-1.15)

1.33

(9.23)

0.98

(10.47)

1.05

(14.19)

 

Model 2

 

-0.01

(-0.95)

1.46

(10.93)

0.79

(8.73)

1.12

(14.64)

 

Model 1 Test b 1= b 2: p-value = 0.022; Model 2 Test b 1= b 2: p-value = 0.001

Model 1 Test b 2= b 3: p-value = 0.340; Model 2 Test b 2= b 3: p-value = 0.002

Model 1 Test b 1= b 3: p-value = 0.076; Model 2 Test b 1= b 3: p-value = 0.032

             

TACC = Total accruals computed using a balance sheet or cash flow approach

DACC = Discretionary accruals computed as the residual from a modified Jones model

NDACC = Non-discretionary accruals computed as the predicted value from a modified Jones model

NDE = Earnings before extraordinary items – discretionary accruals

CFO = Cash from operations

SRET = Annual size-adjusted abnormal returns

Table 7. Statistics on the difference in rankings between balance sheet and cash flow operational definitions of accruals. Based on 14,558 firm year observations over the years 1988-1997 for NYSE/AMEX firms. BS subscript refers to calculations based on changes in reported balance sheet accounts while CF subscript refers to calculations based on changes reported on the statement of cash flows (see definitions in footnote).

 

Panel A. Differences in decile membership for accruals computed using the balance sheet and accruals from the statement of cash flows

                           
       

Absolute value of the difference in decile

rankings between ACCDCLBS and ACCDCLCF.

       

0

1

2

3

4

5

6

7

8

9

All Firm Years:

                   

Percent (%)

38.2%

33.9

12.9

6.1

3.1

2.0

1.4

1.0

0.7

0.4

Extreme Firm-years:

                   

Percent (%)

61.3%

15.9

5.2

3.6

2.9

2.0

2.0

2.0

1.8

3.2

                           

Panel B. Misclassification in extreme (i.e. first and tenth) deciles.

                           
       

All Firms

 

Merger=1

Disc=1

FC=1

 

ACCDCLbs = 1:

           

Number of firm-years

1451

 

169

314

253

 

Number Misclassified

594

 

83

190

125

 

Percent Misclassified

40.9%

 

49.7%

60.5%

49.4%

 
             

ACCDCLbs = 10:

           

Number of firm-years

1451

 

513

124

210

 

Number Misclassified

529

 

284

61

82

 

Percent Misclassified

36.5%

 

55.4%

49.2%

39.0%

 

Note: ACCBS = (D CA - D Cash) – (D CL - D STD) – Depreciation.

ACCCF = NIBE – Cash from operations.

ACCDCLBS = Decile ranking of ACCBS.

ACCDCLCF = Decile ranking of ACCCF.