Reporting goodwill: are the new accounting standards ...

Journal of Business Research 58 (2005) 1353 – 1361

Reporting goodwill: are the new accounting standards consistent with market valuations? Natalie Tatiana Churyk* Department of Accountancy, College of Business, Northern Illinois University, DeKalb, IL 60115, United States Received 7 July 2003; accepted 23 May 2004

Abstract In 2001, the Financial Accounting Standards Board (FASB) issued a standard that eliminated the amortization of goodwill and instead requires that it be tested annually for impairment. This study examines the appropriateness of the elimination of systematic goodwill amortization by testing market valuations of goodwill. While only weak support for the initial impairment of goodwill is found, strong evidence of subsequent impairment is found. These results support the elimination of goodwill amortization by accounting regulators. D 2004 Elsevier Inc. All rights reserved. Keywords: Goodwill impairment; Hubris; Agency conflict; SFAS 142

1. Introduction Goodwill is measured and recorded as the amount paid to acquire a business in excess of the fair value of its net identifiable assets. While this measurement approach is intended to capture the excess value created by a going concern, it is possible that the amount of goodwill recorded may also reflect an overpayment for the acquired firm. The Financial Accounting Standards Board (FASB) has consistently maintained that goodwill meets the definition of an asset and should be capitalized. However, the subsequent treatment of goodwill has long been an issue. Historically, goodwill has been amortized over a period of not more than 40 years. Statement of Financial Accounting Standard (SFAS) Number 142: Goodwill and Other Intangible Assets (2001) eliminated the systematic amortization of goodwill and instead requires goodwill to be tested annually for impairment. * Tel.: +1 815 753 6210, +1 815 787 7789; fax: +1 815 753 8515. E-mail address: [email protected]. 0148-2963/$ - see front matter D 2004 Elsevier Inc. All rights reserved. doi:10.1016/j.jbusres.2004.05.006

This study examines the appropriateness of the elimination of systematic goodwill amortization by testing market valuations of goodwill, both when initially booked and at subsequent impairment. The Exposure Draft (ED) issued prior to the promulgation of SFAS 142 listed conditions that might signal an initial overstatement of goodwill and also described conditions requiring impairment review in subsequent years. (Financial Accounting Standards Board, 1999). Although this list of conditions was not included in the final standard, it provides evidence of items the FASB considered in drafting the new standard. As such, these items are the basis for my analysis of the market’s valuation of goodwill. The results provide evidence that goodwill is not typically overvalued when initially recorded, supporting the contention that systematic amortization is not warranted. The results also provide strong evidence that goodwill may become subsequently impaired as indicated by identifiable conditions. At that time, it would be appropriate to write down goodwill for impairment charges. Thus, this study lends support to the FASB’s decision to replace goodwill amortization with impairment write-downs.

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N.T. Churyk / Journal of Business Research 58 (2005) 1353–1361

2. Literature review and hypotheses development

2.2. Indications of goodwill impairment at acquisition

2.1. Initial overpayment for goodwill

In its ED, the FASB identified four conditions that, if existing at the time of purchase, would trigger a test for goodwill impairment: (1) the purchaser paid a significant premium over the market value of the acquired firm where market value is measured prior to the start of acquisition discussions, (2) the acquisition involved a bidding or auction process, (3) the amount of goodwill is significant compared to the total acquisition price, or (4) most of the consideration paid is stock of the acquiring firm. Previous academic research sheds light on the conditions under which higher premiums may be paid by the acquiring firm. Weston and Halpern (1983) find that the acquirer may overpay for the target in order to gain control of the target. Myers and Majluf (1984) find that a bidding firm manager will offer to pay in stock when he/she believes his/her firm is overvalued. Similarly, Erickson and Wang (1999) find that bidding firms attempt to manipulate their stock price upward before mergers. Haw et al. (1987) propose that firms are forced to pay a substantial premium when purchasing healthy viable firms. Hayn (1989) proposes that higher premiums may compensate target firms’ shareholders who will face immediate capital gains tax rather than continued deferral of capital gains tax. H2 through H5 examine goodwill impairment conditions at acquisition based on the FASB’s ED guidelines.

Several reasons have been offered to explain why purchasers may overpay for a target firm. The agency motive for mergers recognizes that managers have an incentive to act in their own self-interest to the detriment of stockholders. Malatesta (1983), Walkling and Long (1984), Lewellen et al. (1985), Lang et al. (1989), and Berkovitch and Narayanan (1993) find evidence of an agency conflict in studies of mergers and tender offers. Morck et al. (1990) examine models predicting that managers pursue unrelated diversification at the expense of shareholders and find support for these models. Amihud and Lev (1981) argue that when managers are not properly diversified, they diversify holdings of the firm to reduce the risk of human capital. Donaldson and Lorsch (1983) and Jensen (1993) propose that managers will enter new lines of business in order to assure survival of the firm. When a manager’s job becomes threatened by poor performance, he has an incentive to enter new lines of business at which he might be better (Shleifer and Vishny, 1989). Growth also creates attractive promotion opportunities for junior managers without threatening the jobs of current top-level managers (Donaldson, 1984). Harming shareholders need not be intentional as dictated by agency theory. Hubris, as proposed by Roll (1986), occurs when managers act against shareholders interests by issuing bids founded on mistaken estimates of target firm value or on a mistaken belief in their ability to manage the target firm. Based on these mistakes in judgment, the acquirer overbids. Roll (1986) finds that buyers, on average, pay too much for targets. Morck et al. (1990), Berkovitch and Narayanan (1993), and Zhang (1998) also find support for the hubris hypothesis. Other studies also provide evidence that goodwill can be initially overstated. Henning et al. (2000) decompose goodwill into synergy, going concern and residual components. The residual is measured as the difference between recorded goodwill and the synergy and going concern components. Regressing the market value of equity on the three components indicates that the residual component is negatively related to market value, suggesting that overpayments reduce firm value. If an acquirer pays a premium for a target, it is important to determine if the recorded goodwill represents an asset or overpayment. I examine whether agency conflict and/or hubris is related to the goodwill recorded at the time of acquisition. Stated in the alternative form, hypothesis one is as follows: H1. Goodwill at acquisition is positively related to the extent of agency conflict/hubris in the purchase. Support for this hypothesis would provide evidence that goodwill, on average, is overstated at acquisition and already impaired.

H2. Acquirer market value of equity is reduced when the acquirer pays a significant premium over the market value of the acquired firm. H3. Acquirer market value of equity is reduced when an auction or bidding process precedes the acquisition. H4. Acquirer market value of equity is reduced when the amount of goodwill is significant compared to the total acquisition price. H5. Acquirer market value of equity is reduced when most of the consideration paid is in the form of shares of the acquiring firm. 2.3. Indications of subsequent goodwill impairment In the ED, the FASB also discussed four conditions that, if existing in years after the acquisition, would require goodwill to be tested for recoverability. These are the following: (1) the carrying amount of net assets is greater than the market capitalization at the balance sheet date, (2) a significant decrease in either firm’s stock price since the date of acquisition, (3) a significant change in an event used to set the initial price, or (4) an unfavorable change in the status of or expectations about one or more of the underlying elements of goodwill. The last two conditions are not testable because only management possesses this information. As such, H6 and H7 examine


goodwill in periods after acquisition based on the first two conditions. H6. Acquirer market value of equity is reduced when the carrying amount of net assets is greater than the market capitalization at the balance sheet date. H7. Acquirer market value of equity is reduced when a significant decrease in the acquiring firm’s stock price since the date of acquisition has occurred. Support for any of the hypotheses H2 through H7 would provide evidence useful to financial statement preparers and auditors for identifying the initial overstatement or subsequent impairment of goodwill.

3. Methodology 3.1. Sample selection A sample of 1555 firms was collected from Compustat based on the delisting of these firms due to mergers or acquisitions for the period 1996–1998. Firms with SIC codes between 6000 and 6999 inclusive are eliminated because these firms require specialized accounting treatment and follow different regulations (499 firms in the finance, insurance, and real estate industries). Firms with acquirer companies in this SIC code range are also eliminated (124 firms). Other target firms are eliminated as follows: (1) acquirer companies not identifiable (78 firms); (2) acquisitions treated as pooling-of-interests (225 firms); (3) company is also an acquirer (1 firm); and (4) amount of goodwill resulting from the purchase not determinable due to a combination of multiple mergers, stated reason of immateriality, or nonreporting of details-potential self-selection bias (466 firms). Thus, 162 firms with goodwill details remain. From this group, various subsets are used for hypothesis testing. H2, the analysis of synergy, agency conflict, and hubris, requires daily returns data. Thirty-eight firms are excluded for this reason. The initial impairment hypotheses (H2 H3 H4 H5) require the availability of various specific data items, and not all variables are available for each potential observation. Therefore, the sample size for each of these regressions varies from 144 to 153 observations. Tests of H6 and H7 require yearly information from the acquirer subsequent to the purchase. The sample size is 135 observations one year subsequent to acquisition and 109 observations two years subsequent to acquisition. 3.2. Models 3.2.1. Existence of synergy, agency conflict, and/or hubris in the sample A method similar to Berkovitch and Narayanan (1993) is used to investigate synergy, agency conflict, and/or hubris.

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The market’s assessment of the business combination is examined through three types of returns: target returns, acquirer returns, and total combined returns. Gains, which can be positive or negative under the Berkovitch and Narayanan (1993) definition, are determined for each type of return and are calculated as abnormal returns multiplied by common equity. Correlations between the target and acquirer gains and between the target and total gains aid in explaining which merger motives are present. Synergy implies that both the target and the acquirer gain from the merger resulting in shareholder wealth maximization. Therefore, if synergy exists, both the target and acquirer should have positive gains, and total gains are positive. Agency theory rests on the assumption that managers have an incentive to maximize their personal wealth and will do so even to the detriment of shareholders. The acquirer management identifies a target that will increase management’s welfare. Targets are aware of management’s motives and will insist upon terms whereby the target will capture more of the total value than the acquirer. Agency conflict serves to reduce the overall gain, thereby resulting in an inverse relation between target and total gains. Acquirer gains are also inversely related to the degree of agency conflict implying an inverse relation between acquirer and target gains. Hubris results from mistakes by the acquiring management in estimating the value of the target or its own ability to run the target. It is presumed (Berkovitch and Narayanan, 1993) that the acquirer management is equally as likely to overestimate as to underestimate the value of the target but will acquire the target only when it overestimates. In this case, synergy gains should not exist. Thus, there will be no relation between target and total gains. The result of the acquirer’s mistake in valuing the target is similar to an agency conflict in that the target captures more of the total gain than the acquirer, resulting in an inverse relation between target and acquirer gains. All three motives can exist in a single sample. Furthermore, synergy and agency conflict can offset each other, resulting in a zero correlation between target gains and total gains, making it difficult to distinguish between agency conflict and hubris when examining the correlation between target and total gains alone. Berkovitch and Narayanan (1993) resolve this conflict by splitting the sample between positive total gains and negative total gains and then examining the relation between target, acquirer, and total gains within each subsample. They posit that if synergy is predominant in the sample, it will be more likely to appear in the subsample of positive total gains. Likewise, if agency conflict is predominant in the sample, it will be more likely to appear in the negative total gain subsample. A simple market model is used to estimate gains. ARi;t ¼ Ri;t aˆ i bˆ i Rm;t

ð1Þ

Where ARi,t =abnormal return to firm i, on day t, R i,t = realized return to firm i, on day t, aˆ i , bˆi =market model

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parameter estimates, and R m,t =return to the equally weighted CRSP market portfolio on day t. Following Henning et al. (2000), the market model parameter estimates for the target are obtained using a maximum of 240 trading days of daily returns data beginning 61 days before the announcement of the first bid by the first bidder. The market model parameter estimates for the acquirer are obtained using a maximum of 240 trading days of daily returns data beginning 61 days before the announcement of the first bid by the acquiring firm. With multiple bidders, the estimation interval could be different for the target and acquirer. The cumulative abnormal return (CAR) for the target is calculated from five trading days before the announcement of the first bid through 5 days after the announcement of the successful bid (see Bradley et al., 1988; Lang et al., 1989; Berkovitch and Narayanan, 1993; Smith and Kim, 1994; Henning et al., 2000). The CAR for the acquirer is calculated from 5 days before the announcement of the first bid by the acquirer through 5 days after the announcement of the final bid. The target gain (TARG) is computed by multiplying the difference between the market value of the target equity (MVEtarget) and the market value of the target shares held by the acquirer (MVEacquirer held) as of the end of six trading days prior to the first announcement for the target, by the CAR for the target [TARG=(MVEtargetMVEacquirer held)CARtarget]. The acquirer gain (AG) is computed by multiplying the market value of the acquiring firm as of the end of 6 days prior to the first announcement made by the acquiring firm by the CAR of the acquirer (AG=MVEacquirer CARacquirer). Total gain (TOTG) is the sum of the target gain plus the acquirer gain (TOTG= TARG+AG). To examine if synergy, agency conflict, and/or hubris are present, target gains are regressed on total gains and acquirer gains separately, as did Berkovitch and Narayanan (1993). Eqs. (2) and (3) test for synergy, agency conflict, and/or hubris: TARGi ¼ b0 þ b1 TOTGiTj þ ei

ð2Þ

TARGi ¼ b0 þ b2 AGj þ ei

ð3Þ

Where TARGi =gain to target firm i (cumulative abnormal return multiplied by market capitalization), AGj =gain to acquirer firm j (cumulative abnormal return multiplied by market capitalization), and TOTGi*j =total gain (target gain, firm i, plus acquirer gain, firm j). 3.2.2. Initial overpayment for recorded goodwill due to agency conflict/hubris Because both agency conflict and hubris can result in negative returns to the acquirer, one variable (AG) represents both agency conflict and hubris in hypothesis testing. Including this measure in the model allows the determination of whether a portion of goodwill is impaired

at acquisition. An inverse relation between goodwill and AG is expected if agency conflict and/or hubris result in initial overstatement of goodwill. The model used to test H1, relating initial impairment due to agency conflict and/or hubris is as follows: GDWLiTj;t ¼ b0 þ b3 AGj þ ei;t

ð4Þ

Where GDWLi*j,t =goodwill resulting from firm j purchasing firm i, time t, and AGj =acquirer gain, firm j (cumulative abnormal return multiplied by market capitalization). 3.2.3. Initial impairment of recorded goodwill A market value of equity model is used to test hypotheses 2 H3 H4 H5. The market value of equity is first equated to the book values of assets and liabilities. Assets and liabilities are netted and market values are related to the book value of equity. This leads to Eq. (5): MVEj;t ¼ c0 þ c1 BVEj;t

ð5Þ

Where MVEj =market value of equity, acquiring firm j, time t, and BVEj =book value of equity, acquiring firm j, time t. As in prior research, this model is then modified to separately examine selected assets and liabilities to provide evidence on their value relevance (Barth, 1991; Gopalakrishnan and Sugrue, 1993; Harris and Ohlson, 1987; Shevlin, 1991; Jennings et al., 1996). I modify Eq. (5) by disaggregating goodwill from the book value of equity and by adding independent variables representing the impairment conditions. To control for firm size, a weight function of one over the book value of equity squared is used. Dichotomous variables for multiple acquirer purchases and purchase year also are included as control variables. MVEj;t ¼ c0 þ c1 BVLGWj;t þ c2 GDWLiTj;t þ c3 PREMt þ c4 PREMt GDWLiTj;t þ c5 MBt þ c6 MBt GDWLiTj;t þ c7 GWSIGt þ c8 GWSIGt GDWLiTj;t þ c9 PSt þ c10 PSt GDWLiTj;t þ ej;t ð6Þ where t=acquiring firm’s fiscal year-end date for year of MVEj,t acquisition; MVEj,t = market value of equity, acquiring firm j, time t; BVLGWj,t = book value of equity less goodwill resulting from acquisition of firm i, by acquiring firm j, time t; GDWLi*j,t =goodwill resulting from firm j acquiring firm i, time t; PREMi*j,t = purchase price paid by acquirer (firm j) less target market value 90 days before target acquisition discussions divided by target (firm i) market value 90 days before acquisition discussions; MBi*j,t =1 if the acquisition was the result of a bidding or auction process and 0 otherwise, time t; GWSIGi*j,t = goodwill resulting from firm j acquiring firm i, divided by total purchase price, time t; and PSi*j,t = dollar value of acquirer (firm j) shares used in purchase, divided by total purchase price, time t.


This model tests whether an initial impairment of goodwill is related to a decline in market value. The full model is tested with all impairment conditions included, and then retested with each impairment condition included by itself. If goodwill is value relevant, the coefficient on goodwill will be positive and significant. If only the impairment condition variable (and not its interaction with goodwill) is significant, then I am unable to conclude whether goodwill is affected by the impairment condition. However, if the interaction variable is inversely related to market value, then a decline in market value may be due to the decline in the value of goodwill conditioned on the impairment indicator. 3.2.4. Subsequent impairment of goodwill The model used to test subsequent impairment is similar to Eq. (6) with observations from both 1 and 2 years following the acquisition. MVEj;tþn ¼ h0 þ h1 BVLGWj;tþn þ h2 GDWLiTj;tþn þh3 CVGMtþn þh4 CVGMtþn GDWLiTj;tþn þ h5 SPDtþn þ h6 SPDtþn GDWLiTj;tþn þ ej;tþn

ð7Þ

Where t=acquiring firm’s fiscal year-end date for year of acquisition; n=number of years subsequent to the year of acquisition (1 or 2); MVEj,t+n =the market value of equity, acquiring firm j, time t+n; BVLGWj,t + n =book value of equity less goodwill, acquiring firm j, time t+n ; GDWLi*j,t+n =the goodwill resulting from firm j acquiring firm i, time t+n; CVGMt+n =1 if the carrying value of net assets is greater than market value, 0 otherwise, time t+n; and SPDt+n =1 if a significant decrease (top quartile) in acquirer stock price since acquisition, 0 otherwise, time t+n.

4. Results for initial and subsequent impairment of recorded goodwill 4.1. Descriptive statistics and multicollinearity diagnostics Descriptive statistics for all models appear in Table 1. The mean, minimum and maximum returns to the acquirer and target for synergy, agency conflict, and/or hubris are reported in millions under Panel A. Statistics for the nondichotomous variables for the initial and subsequent impairment models appear under Panels B and C in Table 1, respectively. The mean, minimum and maximum values for the initial impairment model in Panel B relate to the year of purchase. The number of observations ranges from 153 to 162. The values reported for the subsequent impairment model in Panel C are from the first year subsequent to acquisition and the second year subsequent to acquisition and are measured in millions. The number of observations ranges from 109 to 135. Additional tests included t-tests comparing the sample to the population of firms reporting

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Table 1 Sample descriptive statistics: agency conflict/hubris, initial impairment, and subsequent impairment Observations

Mean

Minimum

Panel (A) Synergy/agency conflict/hubris (in US$ millions) Total sample AG 124 70 2730 TARG 124 67 4331 TOTG 124 137 4118 Positive total gain sample AG 85 210 389 TARG 85 117 67 TOTG 85 327 1 Negative total gain sample AG 39 237 2730 TARG 39 41 4331 TOTG 39 278 4118 Panel (B) Impairment BVLGW 155 GDWL 162 MVE 153 PREM 155 GWSIG 160 PS 159

1035 647 6155 3 0.62 0.34

Panel (C) Subsequent impairment First year after acquisition BVLGW 135 1427 GDWL 135 702 MVE 135 10113 Second year after acquisition BVLGW 109 3254 GDWL 109 736 MVE 109 12827

Maximum

3897 1990 3983

3897 1990 3983

212 1221 1

2734 1 17 1 0.00 0.00

21348 29700 131717 238 4 1.00

3183 0 21

22281 28958 198776

2640 2 0.23

44995 28215 198776

TARG=gain to target firm i (cumulative abnormal return multiplied by market capitalization), AG=gain to acquirer firm j (cumulative abnormal return multiplied by market capitalization), TOTG=total gain (target gain, firm i, plus acquirer gain, firm j). MVE=market value of equity, acquiring firm j; BVLGW=book value of equity less goodwill resulting from acquisition of firm i, by acquiring firm j; GDWL=goodwill resulting from firm j acquiring firm i; PREM=purchase price paid by acquirer (firm j) less target market value 90 days before target acquisition discussions divided by target (firm i) market value 90 days before acquisition discussions; GWSIG=goodwill resulting from firm j acquiring firm i, divided by total purchase price; and PS=dollar value of acquirer (firm j) shares used in purchase, divided by total purchase price.

goodwill over the years 1996–1998. The goodwill amount examined is total goodwill rather than goodwill from a specific purchase as in Table 1. Results of t-tests show that the sample and the population are not statistically different for total debt ( p=0.32) and marginally different for total assets ( p=0.07). The sample is larger than the population for book value of equity, goodwill, and market value of equity. Multicollinearity diagnostics, and Pearson and Spearman correlations are performed, although not presented, for the independent variables included in Eqs. (6) and (7). Because

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Table 2 Regressions of target gain on total gain and target gain on acquirer gain with positive and negative subsamples n

R¯ 2

b0

Panel (A) TARG i,t1 =b 0 +b 1 TOTG i*j,t +e i,t1 Total sample 124 0.44 82.03 (0.84) Positive total 85 0.36 31.85 gain sample (0.68) Negative total 39 0.74 544.94 gain sample (1.46) Panel (B) TARG i,t1 =b 0 +b 2 AG j,t1 +e i,t1 Total sample 124 0.21 235.15 (1.45) Positive total 85 0.04 122.40 gain sample (2.07) Negative total 39 0.75 –111.61 gain sample (0.44) Panel (C) GDWL j,t0 =b 0 +b 2 AG j,t1 +e i,t1 Total sample 124 0.40 139.45 (0.16) Positive total 85 0.30 853.43 gain sample (1.86) Negative total 39 0.79 955.18 gain sample (0.70)

b1

b2

0.51 (1.99)c 0.32 (1.78)b 1.33 (1.78)b

– – –

– – –

0.30 (0.69) 0.11 (1.46)a 1.32 (1.82)b

2.77 (1.93)b 0.85 (1.51)a 6.78 (1.60)a

The table shows coefficient estimates with t-statistics in parentheses. OLS estimation is used for the positive gain subsample in Panels B and C. Estimations are based on White’s (1980) consistent covariance estimators for all others. All regression equations are conducted with dollars in millions and include dichotomous variables for multiple acquirer purchases and for purchase year. TARG=gain to target firm i (cumulative abnormal return multiplied by market capitalization), AG=gain to acquirer firm j (cumulative abnormal return multiplied by market capitalization), TOTG=total gain (target gain, firm i, plus acquirer gain, firm j). Target gain is measured over a period beginning 5 days before announcement of first bid and ending 5 days after the successful bid. Acquirer gain is measured over a period beginning 5 days before their first announcement of a bid and ending 5 days after announcement of success. One hundred and twenty-two of 124 acquirer firms have CAR return periods of 11 days. Two acquirer firms have an average CAR return period of 95.0 days due to the acquirer submitting multiple bids. One hundred and eleven target firms have CAR return periods of 11 days. The remaining 13 target firms have an averaged CAR return period of 68.54 days due to multiple bidders. Cut-off values for one tailed t-tests are as follows: t .10=1.29 (a=0.10)a; t .05=1.66 (a=0.05)b; t .025=1.98 (a=0.025)c; t .01=2.37 (a=0.01)d; t .005=2.63 (a=0.005)e

some correlations are high, variance inflation factors (VIFs) are examined. A VIF in excess of 10 indicates multicollinearity and may influence least squares estimates (Neter et al., 1996). The VIFs range from 1.05 to 1.36 for all models, indicating that the results are not influenced unduly by multicollinearity. 4.2. Regression results 4.2.1. Synergy, agency conflict, and/or hubris Table 2 presents the results of regressing target gain on total gain (Panel A) and target gain on acquirer gain (Panel

B) for the entire sample as well as for the positive and negative gain subsamples. Examination for heteroskedasticity reveals that only one regression in Panel B (positive total gain sample) is not heteroskedastic with a White’s (Neter et al., 1996) statistic of 7.86. All other regressions are heteroskedastic (White’s statistics ranging from 38.12 to 123.8) and require the use of White’s heteroskedasticity consistent estimators for these regressions. Panel A of Table 2 indicates that, for the entire sample, the correlation between target and total gains is positive and significant with a coefficient estimate of 0.51 and a significance level (a) of 0.025. This is consistent with synergy. Furthermore, synergy, if it exists, is more likely to be present in the positive total gain subsample. The correlation between the target gains and total gains in the positive subsample and the negative subsample are significant with coefficients of 0.32 (a=0.05) and 1.33 (a=0.05), respectively. This implies that synergy appears to be the dominant motive for the sample acquisitions. Panel B indicates that, for the entire sample and the positive gains sample, the correlations between target and acquirer gains are not statistically different from zero with coefficient estimates of 0.30 (a=0.25) and 0.11 (a=0.10), respectively. This implies that hubris or agency conflict may be negating the effect of synergy. The negative subsample has a coefficient estimate of 1.32 (a=0.05). This implies that agency conflict, in addition to synergy, is present in the sample. 4.2.2. Initial overpayment of goodwill resulting from agency conflict/hubris Because the previous analysis indicates that agency conflict and possibly hubris exist in the negative subsample, Panel C of Table 2 reports the effect they may have on goodwill through a regression of goodwill on acquirer cumulative abnormal returns. This analysis indicates that, on average, purchased goodwill is not initially overstated due to agency conflict/hubris with coefficients on the total, positive, and negative samples of 2.77 (a=0.05), 0.85 (a=0.10), and 6.78 (a=0.10), respectively. 4.2.3. Initial impairment of goodwill using a levels model Table 3 presents estimation results of the model in Eq. (6) and includes regressions for each impairment condition with interactions and a single regression with all impairment conditions. The Breusch–Pagan values range from 64.16 to 85.55, indicating that White’s (1980) correction for heteroskedasticity is necessary. The estimated coefficients on book value of equity less goodwill (c 1) and goodwill (c 2) are significantly positively related to market values as predicted. A means test between the coefficient on goodwill and book value of equity less purchased goodwill indicates that the difference between goodwill and other assets is not significant in the year of purchase ( p=0.18). Thus, the market does not value goodwill differently than


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Table 3 Regression results for initial impairment of goodwill MVEj,t1+n =c 0+c 1BVLGWj,t1+n +c 2GDWLi *j,t1+n +c 3PREMt1+n +c 4(PREMt1+n GDWLi*j,t1+n )+c 5MBt1+n +c 6(MBt1+n GDWLi*j,t1+n )+c 7GWSIGt1+n +c 8(GWSIGt1+n GDWLi *j,t1+n )+c 9PSt1+n +c 10(PSt1+n GDWLi*j,t1+n )+c 11OGWj,t1+n +e j,t1+n n R¯ 2 c0 c1 c2 c3 c4 c5 c6 c7 c8 c9 c 10 c 11 153

0.33

146

0.31

153

0.33

151

0.32

150

0.32

144

0.32

121

0.36

32.09 (1.35) 33.84 (0.93) 25.05 (1.28) 58.46 (0.98) 6.80 (0.13) 114.41 (0.55) 55.42 (1.21)

2.88 (5.74)e 2.87 (5.55)e 2.58 (4.01)e 2.94 (5.69)e 3.08 (5.78)e 2.64 (3.78)e 2.33 (4.14)e

3.68 (6.38)e 3.73 (5.55)e 3.75 (5.39)e 3.99 (5.99)e 3.96 (5.00)e 4.25 (4.34)e 2.76 (6.81)e

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

0.05 (0.24) –

–

–

–

–

–

0.87 (0.70) –

–

–

39.72 (0.20) –

–

–

–

–

–

0.67 (1.74)b –

–

–

107.57 (1.11) –

0.43 (0.38) –

92.28 (0.57) –

0.93 (0.92) –

1.39 (1.55)a 1.09 (1.40)a –

–

168.92 (0.55) –

39.21 (0.80) 171.49 (0.78) –

4.56 (0.22)

2.74 (0.21) –

0.03 (0.21) –

– 3.81 (4.84)e

BVLGW represents the book value less the most recently purchased goodwill except for the final model. In the final model, BVLGW is measured as book value less all goodwill (GDWL=goodwill from the purchase plus OGW=goodwill other than the recent purchase). The table shows OLS coefficient estimates and t-statistics based on White’s consistent covariance estimator in parentheses. Levels variable are reported in millions of dollars. The weight function (1/book value of equity squared) is used to control for firm size and dichotomous variables for multiple acquirer purchases and purchase year are included as control variables. MVE=market value of equity, acquiring firm j; BVLGW=book value of equity less goodwill resulting from acquisition of firm i, by acquiring firm j; GDWL=goodwill resulting from firm j acquiring firm i; PREM=purchase price paid by acquirer (firm j) less target market value 90 days before target acquisition discussions divided by target (firm i) market value 90 days before acquisition discussions; MB=1 if the acquisition was the result of a bidding or auction process and 0 otherwise; GWSIG=goodwill resulting from firm j acquiring firm i, divided by total purchase price; and PS=dollar value of acquirer (firm j) shares used in purchase, divided by total purchase price. Cut-off values for one tailed t-tests are as follows: t-tests: t .10=1.29 (a=0.10)a; t .05=1.66 (a=0.05)b; t .025=1.98 (a=0.025)c; t .01=2.37 (a=0.01)d; t .005=2.63 (a=0.005)e.

other assets. An additional regression, including both the recently purchased goodwill and all other goodwill, is included. A means test between the two goodwill measures indicates that the difference between new goodwill and other goodwill is not significant in the year of purchase ( p=0.14). The estimated coefficients on the impairment conditions are not different from zero. The interaction between GWSIG (goodwill is a significant portion of the purchase price) and

goodwill is significantly negative (cˆ8=0.67, a=0.05) in the regression containing only that impairment condition but is not statistically significant in a regression including all impairment conditions. The interaction between the variable representing consideration in shares, PS, and goodwill is significantly negative with coefficients of 0.99 (a=0.10) and 0.90 (a=0.10) for the regression containing only that impairment event and the regression containing all impairment events, respectively. In summary, the results provide

Table 4 Regression results for subsequent impairment of goodwill MVEj,t1+n =h 0+h 1BVLGWj ,t1+n+h 2GDWLi*j,t1+n +h 3CVGMt1+n +h 4(CVGMt1+n GDWLi*j,t1+n )+h 5SPDt1+n +h 6(SPDt1+n GDWLi*j,t1+n )+e j,t1+n n R¯ 2 h0 h1 h2 h3 h4 h5 h6 Panel (A) First year subsequent to acquisition 135 0.67 11.01 (0.19) 3.17 (6.46)e 134 0.64 32.42 (0.65) 2.71 (6.96)e 134 0.66 7.63 (0.14) 3.10 (7.43)e

2.56 (4.45)e 2.25 (4.48)e 2.63 (5.20)e

217.26 (3.05)e – 211.20 (3.06)e

2.02 (2.75)e – 2.11 (3.16)e

– 0.78 (0.60) 14.32 (0.18)

– 0.51 (0.56) 0.16 (1.15)

Panel (B) Second year subsequent to acquisition 108 0.60 98.53 (0.68) 2.01 (4.97)e 107 0.59 4.24 (0.07) 1.64 (4.41)e 107 0.62 28.20 (0.34) 1.98 (4.93)e

4.75 (3.49)e 4.51 (3.60)e 4.87 (3.91)e

5.65 (0.07) – 85.36 (1.27)

4.54 (3.31)e – 2.85 (3.03)e

– 87.81 (1.02) 92.41 (1.14)

– 3.49 (2.55)d 2.82 (2.42)d

The table shows OLS coefficient estimates and t-statistics based on White’s consistent covariance estimator in parentheses. The weight function (1/book value of equity squared) is used to control for firm size and dichotomous variables for multiple acquirer purchases and purchase year are included as control variables. MVE=market value of equity, acquiring firm j; BVLGW=book value of equity less goodwill resulting from acquisition of firm i, by acquiring firm j; GDWL=goodwill resulting from firm j acquiring firm i, purchased goodwill; CVGM=1 if the carrying value of net assets of the acquirer is greater than market value, 0 otherwise; and SPD=1 if there is a significant decrease (top quartile) in acquirer stock price since acquisition, 0 otherwise. Cut-off values for one tailed t-tests are as follows: t .10=1.29 (a=0.10)a; t .05=1.66 (a=0.05)b; t .025=1.98 (a=0.025)c; t .01=2.37 (a=0.01)d; t .005=2.63 (a=0.005)e.

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weak support for only one of the impairment conditions described in the ED implying that goodwill is not, on average, initially overvalued. 4.2.4. Subsequent impairment of goodwill Table 4 presents results for Eq. (7). Regressions that include each individual subsequent impairment condition and a single regression with all subsequent impairment events are presented. Results for the first year subsequent to acquisition appear in Panel A and results for the second year subsequent to acquisition appear in Panel B. Breusch– Pagan test statistics range from 93.45 to 93.52 for Panel A and 53.45 to 57.83 for Panel B, respectively, indicating that White’s (1980) correction for heteroskedasticity is necessary. If purchased goodwill is subsequently impaired because the carrying value of net assets is greater than the market capitalization at the balance sheet date, then the interaction between purchased goodwill less amortization and the impairment condition will be inversely related to market values. In the first and second years subsequent to acquisition, the estimated coefficients on the interaction (h 4) are 2.02 (a=0.005) and 4.54 (a=0.005), respectively, indicating that for firms with book values greater than market values, goodwill is impaired. If purchased goodwill is subsequently impaired due to a significant decrease in the purchasing firm’s stock price since the date of acquisition, then the interaction between purchased goodwill less amortization and the impairment condition will be inversely related to market values. The estimated coefficient on this interaction (h 6) is not significantly different from zero in the first year after acquisition, but is significantly negative in the second year after acquisition with a coefficient of 3.49 (a=0.01). This result implies that goodwill is impaired in the second year subsequent to acquisition when the acquirer firm’s stock price has declined significantly.

5. Conclusion I test the market’s initial assessment of goodwill based on the guidelines included in the ED that preceded the issuance of SFAS 142. Weak evidence of initial impairment is found for only one condition: when the acquisition is made by payment of the acquirer’s shares. Overall, the results provide evidence that goodwill is not typically overvalued when initially recorded, supporting the contention that systematic amortization is not warranted. I also test the market’s subsequent assessment of goodwill using the ED guidelines. In contrast to the initial impairment findings, goodwill is subsequently impaired in two situations: when there has been a significant decrease in stock price since the acquisition date; and when book value of equity is greater than market value of equity. Although SFAS No. 142 does not

specifically identify these impairment events, they are easily measurable by auditors and could be useful tools for detecting impairment. The ultimate goal of financial reporting is to provide financial statement users with information useful for decision making. Accounting earnings may fail to reflect reductions in the value of recorded goodwill. The resulting overstatement of both assets and net income violates conservative accounting practices. SFAS No. 142 attempts to remedy this. Although limitations, such as correlated omitted variables, are inherent in value relevance research designs, I find that impairment events are associated with stock prices. Thus, financial statement users should use care when valuing a firm’s assets between reporting dates. The FASB’s overall decision to eliminate the periodic amortization of goodwill and instead require impairment reduction appears to be supported by the results of this study.

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