Evidence that Companies are not Analyzing Goodwill for Impairment as Required by SFAS142

Evidence that Companies are not Analyzing Goodwill for Impairment as Required by SFAS142 DAVID E. VANCE Rutgers University School of Business Camden dvance@camden.rutgers.edu Working Paper Series WCRFS: 08-08 1

ABSTRACT: SFAS142 (2001) requires that goodwill be analyzed for impairment annually and written down if impaired. Impairment testing is complex and relies on many subjective factors. To users it is a black box analysis which gives companies an unprecedented opportunity to manage earnings. For example, in 2005 some 2,724 companies with $2.4 trillion of goodwill found only 0.54% of that goodwill impaired and in 2006 some 2697 companies with $2.4 trillion of goodwill found only 0.65% of goodwill impaired. If goodwill has value, it should generate rent comparable to industry norms. A reasonableness test for impairment would be to compare returns of companies with goodwill to these norms. In this study, 38,519 years of company operations for 48 industries were analyzed to develop industry norms. Of 2,730 companies with goodwill, 956 underperformed their industry by at least 10% and 95 underperformed by more than a standard deviation. The contributions of this article are to provide evidence that goodwill is not being properly tested for impairment and to develop a reasonableness test for determining whether a firm s goodwill is impaired. ACKNOWLEDGEMENT: This paper draws heavily on Compustat data in the WRDS data base service. Access to this data base service is funded in part by the David Whitcomb Center for Research in Financial Services. Access to such data is absolutely vital to researchers expanding the frontiers of knowledge in accounting, finance and related disciplines. Keywords: Goodwill, Impairment, Write-off, Intangible Asset 2

I Introduction Statement of Financial Accounting Standards No. 142 Goodwill and Other Intangible Assets, (SFAS 142, 2001) provides that goodwill is not to be amortized, but rather tested for impairment. Proper impairment testing is significant factor in determining a company s financial position. In 2005, the 4,815 largest companies on Compustat had $54.4 trillion of assets and $2.3 trillion of booked goodwill or about 4.23% of total assets. In 2006, the 4,815 largest companies had $62.7 trillion of assets and $2.4 trillion of booked goodwill or about 3.91% of total assets. In 2005, some 256 companies with assets of $1.4 trillion and goodwill of $473 billion would have had zero or negative equity if goodwill were found impaired and written off. In 2006, 241 companies with $1.4 trillion of assets would have had zero or negative equity if $379 billion of goodwill were found impaired and written off. In 2005, another 88 companies with assets of $158 billion had negative equity of $35 billion and yet carried unimpaired goodwill of about $14 billion. In 2006, 83 companies with assets of $682 billion carried unimpaired goodwill of $25 billion. These facts seem at odds with the theoretical reason for goodwill which is to recognize intangibles which lead to superior performance such as management skill and learning. Companies with the attributes ascribed to goodwill should be profitable and profits should build equity. Impairment exists when the carrying value of a reporting unit with goodwill exceeds the fair value of the unit (SFAS142 19 2001). Once impairment has been established, the extent of impairment must be measured. But goodwill only exists as a residual value so it can only be determined by subtracting the fair value of non-goodwill assets from the fair value of a reporting unit (SFAS142 21 2001). The fair value of a reporting unit refers to the amount for which the 3

unit could be bought or sold between willing parties. Market prices are the best evidence of market value (SFAS142 23 2001). Estimating the value of a stand-alone company is complex, and turns on assumptions about future revenue and expenses, industry trends and the market value of comparable companies. While SFAS142 (2001) invests more than 1,900 words describing impairment testing, it raises almost as many questions as it answers. Its complexity provides management with an unprecedented opportunity to manage earnings by writing off goodwill as needed to smooth earnings during good times or to retain goodwill on the books long after it has ceased to create value. This study analyzes 38,519 years of operations for companies with and without goodwill over the period 1995 to 2004. Norms of ROA performance are summarized by industry, based on the Fama and French (1997) classification model. The performance of companies with goodwill in 2005 was compared to these norms to identify companies that probably should have recognized that goodwill was impaired and written it down. The data also show that in 2005, 2,724 companies with $2.3 trillion of booked goodwill found only 0.54% of that goodwill impaired and in 2006, some 2,697 companies with $2.5 trillion of goodwill found only 0.65% of that goodwill impaired. This seems extraordinary if companies are faithfully testing goodwill for impairment as mandated by SFAS142 (2001). SFAS142 (2001) has presented analysts and other financial statement users with a black box impairment standard that gives companies an unprecedented opportunity to manage earning. The contributions of this study are to provide an evidence that companies are ignoring 4

the provisions of SFAS142 (2001) and to suggest a means of reasonableness testing management s impairment decisions. This paper is organized as follows, section II of this paper is the literature review, section III is the methodology, section IV is the empirical analysis and section V is the conclusion. II Literature Review Impairment Testing Goodwill booked pursuant to Statement of Financial Accounting Standards No. 141 Business Combinations, (SFAS 141, 2001 revised 2007) is the difference between the purchase price of a company and the fair value of net assets. As such, it is residual in nature and therefore impairment can only be measured by valuing the reporting unit, and the fair value of its assets at least annually (SFAS 142, 2001). A reporting unit is the lowest level for which financial information is maintained. A reporting unit is an operating segment or one level below a segment (SFAS142 30 2001) as defined in FASB Statement No. 131, Disclosures about Segments of an Enterprise and Related Information. If the carrying value of goodwill is greater than its fair value, then goodwill is impaired and must be written down to its fair value. To compute the fair value of goodwill, the reporting unit must be valued as a stand alone business. The fair value of the reporting unit, less the fair value of its non-goodwill assets, is the maximum value of goodwill (SFAS142, 2001). While these tests sound straight forward, there are numerous opportunities for manipulation. Valuation of a reporting unit as a stand alone entity depends on assumptions concerning revenue and expenses, market size and growth, competitors, new products, evolving technology, the value of services provided by a parent company such as information technology, treasury and 5

legal, as well as the amount of cash which must be reinvested in working capital, plant property and equipment and research and development to remain competitive. Valuation will also depend on the allocation of debt and tax liabilities or credits to the reporting unit. Burden on Goodwill The value of a reporting unit may decline for many reasons, for example a change in the regulatory environment, a technological break through, or unforeseen competition. These factors may or may not impair the value of non-goodwill assets. For example, a change in the regulatory environment may not affect the fair value of a pick-up truck or an office building, but may reduce the value of a business as a going concern. SFAS 142 29 (2001) provides that nongoodwill assets should be tested before impairment before goodwill assets are tested for impairment. If non-goodwill assets are not impaired, the burden of enterprise decline will fall squarely on goodwill. Tracing Reporting Unit Assets Assets purchased with goodwill are rarely static. They are consumed, expanded, replaced and disposed of. Acquired companies are rarely left as purchased. They are split up or merged with other entities within a company. Capital is injected into these entities and withdrawn from them. Liabilities are incurred by reporting units and paid off. Corporate assets and liabilities that benefit the reporting unit must be allocated (SFAS142 33 2001). This makes tracing goodwill and related assets to reporting units problematic (Hayn and Hughes 2006; Massaud and Raiborn 2003; Herz et. al. 2001). 6

Market Value While market price in actively traded markets is the best evidence of fair value, such evidence is rarely available. Even it is available, adjustments must be made for the control premium. If a minority of stock is actively traded, it probably sells at a discount to the value all the stock because the fair value of all the stock would include a premium for control (SFAS142 23 2001). Present Value Methods The fair value of a reporting unit may be estimated using present value methods (SFAS142 23 2001). The dividend discount model (DDM) of Williams (1938) is given in equation (1). This model sums the present value of all future dividends (DIV) using the firm s cost of equity r e as the discount factor. V 0 = E 0 (Div t ) (1) (1 + r e ) t This model assumes a stream of dividends can be forecast indefinitely into the future and also assumes a constant cost of equity. It is not especially useful for firms that don t pay dividends. The discounted cash flow model (DCF) shown in equation (2) is derived from DDM and discounts free cash flow (FCF) available to debt and equity holders to the present using the weighted average cost of capital (WACC). 4 t=1 T t=1 V 0 + net debt 0 = E 0 (FCF t ) + E0(V t + net debt) (2) (1+r WACC ) (1+r WACC ) 7

Forecasting FCF indefinitely into the future is difficult, so as a practical matter it is projected for a number of years at which time it is assumed the company reaches a steady state of growth and WACC is constant. This terminal value is given in equation (3). V t = E 0 [FCF t x (1+ g)] (3) (r WACC g) The residual income method (RIM) is based on DDM, but uses clean surplus accounting. Clean surplus accounting assumes all transactions that affect equity, except those with shareholders, are contemporaneously recognized in the income statement. Residual income shown in equation (4) is net income (NI) less a charge for equity equal to the cost of capital times the beginning period book value. RI t = NI t r e BV t-1 (4) Market value, V 0, is estimated as the sum of the present value of RI through some terminal date as shown in the first term of equation (5). As with free cash flow, it is difficult to compute residual income into the future indefinitely. Therefore, beyond the terminal date, all future value is estimated as the market value (V) at time t, less the book value (BV) at time t, discounted to the present at the cost of equity as shown in the second term of equation (5). T t=1 V 0 = E 0 (RI t ) + E 0 (V t BV t ) (5) (1 + r e ) t (1+r e ) t While Herz, et. al. (2001) laud these models as theoretically correct, they also discuss their limitations at length. For example, they all require forecasting revenue, expenses and reinvested capital over a long period of time. The DCF model requires forecasting a constant growth rate at some time in the future and the RIM model requires estimating market and book value at some time in the future. Terminal value can be a significant fraction of total value, so 8

reporting unit valuation is very sensitive to terminal value assumptions. There is also the question of whether the cost of equity of the parent should be used or the implied cost of equity of the reporting unit. All models are sensitive to estimates of the cost of equity capital and there are at least three different methods of estimating the cost of equity capital (Vance, 2003). Reporting unit WACC will be a function of the liabilities allocated to it including non-interest bearing liabilities such as accounts payable, accrued payroll and deferred taxes. Since present value models are based on so many estimates, management has an unprecedented opportunity to shape the outcome to meet its needs. Multiplier Methods Use of revenue or earnings multipliers may be appropriate if data are available on comparable companies. As a practical matter, this means comparable companies must be publicly traded. Assuming data on companies in the same industry, with a similar economic model are available, another question arises. Are we to assume the reporting unit is to be valued as a privately held or a publicly traded company? This is a significant valuation issue because privately held companies trade at a 25% to 30% discount to comparable publicly traded companies. The reporting unit may never have been public and may not be large enough to go public. Even if it is large enough to go public it may not qualify for listing on a major exchange (NYSE, AMEX or NASDAQ National Market) in which case valuation may be impacted by lack of market makers, thin trading, and it may not qualify for federal pre-emption which means it would be subject to both state and federal securities regulation (Vance 2005). Again, management s assumptions as to which companies are comparable and whether the reporting unit is valued as a public or private company gives rise to considerable management discretion. 9

Black Box Earnings Management These factors make a single, objective, verifiable test of impairment difficult. Another factor which makes evaluation of impairment testing difficult is the paucity and low quality of reporting unit level information (Hayn and Hughes 2006). Esquivel and Gornik-Tomaszewski, 2007) suggests additional disclosure, but even the best disclosure is only likely to document management choices, not the range of alternative choices not taken. A process so highly dependent on management judgment and discretion opens the door to earnings management (Massoud and Raiborn 2003). As a result, the process looks like a black box to analysts and other financial statement users. Francis, et. al (1996) found that management was more likely to game write-offs for hard to measure assets like goodwill than they were to game write-offs of more easily measured assets like inventory, plant, property and equipment. Hayn and Hughes (2006), reported a lag time of 3 to 4 years between economic impairment of goodwill and its recognition. They also reported that for a third of the acquisitions they studied, goodwill impairment was not recognized for six to ten years after a decline in economic value. Their work provides additional support for the idea that earnings are being managed through the goodwill impairment process. Some analysts dismiss goodwill as a mere bookkeeping device. However, Hirschey and Richardson (2003) found goodwill write offs were an important signal of a company s future prospects. For example, impairment announcements were highly correlated with an immediate 3 to 3.5% drop in stock price. More interesting, they found that one year post announcement, stock prices were down an average of 11% implying that investors initially under-reacted to impairment disclosures. Market reaction to impairment decisions provides companies with a strong motive to manage earnings. 10

The objective of this paper is not to criticize or second guess SFAS142 (2001). On the contrary, the issue is whether SFAS142 is being scrupulously implemented. This issue is addressed through a macro analysis of goodwill impairment across a large number of companies. However, a market-wide or even industry-wide analysis of impairment is of little use to analysts or other financial statement users. Therefore, this paper goes one step further and develops a reasonableness tests that can be applied on a company by company basis. This reasonableness test is not meant to replace goodwill impairment testing, but simply identify companies which merit enhanced scrutiny. III Methodology While impairment testing appears like a black box to financial statement users, a reasonableness test can be developed by returning to first principles. Goodwill is presumed to be an asset pursuant to SFAS141 (2001 revised 2007). One characteristic of an asset is that it generates rent. Rent generating capability can be measured by return on assets (ROA) defined as operating income before depreciation and amortization divided by average assets. One expects the ROA of companies with and without goodwill to be distributed around some industry average. If a company s ROA is substantially less than the industry average its assets are not being utilized as productively as those with above average ROA. If goodwill is impaired, it may be a non-productive asset. The ability to generate earnings from assets directly impacts enterprise value. Therefore, ROA can be used as a proxy for relative enterprise value. As discussed previously, if non-goodwill assets are impaired, the burden of enterprise decline falls squarely on goodwill (SFAS142 29 2001). 11

Equation (6) assumes earnings from all reporting units are aggregated in the numerator and goodwill as well as non-goodwill assets from all reporting units are aggregated in the denominator. For many companies, this represents the maximum detail available to investors and analysts. ROA = Earnings before interest, taxes, depreciation and amortization (6) Goodwill + Non-Goodwill Assets If goodwill is so small compared to non-goodwill assets that it does not affect ROA, then it may be immaterial to a financial statement users. On the other hand, if non-rent producing goodwill is great enough to depress ROA, assessment and write down of goodwill to its fair value is more important. Writing down impaired goodwill will tend to raise a company s ROA in subsequent periods. There is no guarantee that the reasonableness test described herein will identify impaired goodwill in every reporting unit. For example, a company with superior ROA could have impaired goodwill in a small reporting unit. The proposed reasonableness test does, however provide a performance threshold below which it is more likely that some or all of a company s goodwill is impaired. The first step in this analysis was to create industry norms by selecting companies from Compustat with at least $20 million in assets, a stock price of at least $1 and sales of at least $5 million. Ten years of operating data (1995 to 2004) were used to develop a baseline consisting of 38,519 years of performance. Companies were then classified into 48 industries using the Fama and French (1997) classification schema provided as Appendix A. The mean, median, quartiles and standard deviation for industry ROA were computed using all companies regardless of 12

whether they had booked goodwill. The ROA performance of 2,730 companies with goodwill for the year 2005 were then compared to industry norms for indications of impairment. IV Empirical Analysis Compustat reported 4,815 companies with assets over $20 million for 2005. At the end of 2005, about 2,730 of those companies had total goodwill of $2.36 trillion. Of the $109 billion of goodwill written off, six firms accounted for $96 billion of write offs. Excluding these six firms, all other firms with goodwill wrote off about $13.2 billion or about 0.54% of recorded goodwill. In 2006 some 2697 firms ahs $2.45 billion of goodwill and found only 0.65% impaired. See Table 1 Impairment Analysis. Such a low percentage of goodwill impairment strains credulity. INSERT TABLE 1 Table 2 Industry Performance is an analysis of ten year historical return on assets for each of 48 industry classifications. For example, return on assets of 13.96% for the Chems industry was based on 733 years of operating performance by companies which met the threshold for inclusion in this study and which were reported on Compustat. The standard deviation of ROA for this industry was 6.13% and the ROA of the first quartile was 17.82%. The median and third quartile performance for this industry were 11.69% and 9.73% respectively. Data in this table provide ROA norms which are used as the basis of reasonableness tests. INSERT TABLE 2 Table 3 Comparison to Industry Norms analyzes individual companies with goodwill against norms for their industry. For example, in 2005, Computstat reported 96 companies in the Chems industry and 74 of those companies had booked goodwill. Of the companies that had 13

booked goodwill, 30 had an ROA at least 10% below the long term industry mean of 13.96% as reported in Table 2. For the Chems industry 12 companies with goodwill were in the lowest quartile for the industry and the ROA for 5 companies with goodwill was more than a standard deviation below industry mean. INSERT TABLE 3 Table 3 also analyzes how firms would move toward the mean ROA if goodwill were written off. For example, if the 30 Chems firms which under performed the industry mean by at least 10% wrote off their goodwill, 8 of the firms would have a return within 10% of the mean. The remaining 22 firms in this category would still under perform the Chems industry by at least 10%. Overall, of the 2,730 companies with goodwill, 956 or about 35% underperformed their industry by at least 10%. These companies had $1.04 trillion in goodwill booked. A fair question is whether this goodwill is impaired. About 418 companies or 15.3% of those with goodwill had an ROA in the lowest quartile of long term industry performance. These companies had $304 billion of booked goodwill. Since the performance of these companies is well below historical norms, a reasonable person might conclude there is a prima facie case that this goodwill has been impaired. A prima facie case means it looks impaired and is presumed impaired, but that presumption can be rebutted by substantial management evidence. About 95 companies had an ROA that was more than a standard deviation below their industry mean. These companies had $41 billion of booked goodwill. A reasonable person might conclude that the performance of these companies is so far below historical norms that enterprise value has significantly diminished. Since the effect of SFAS142 (2001) is to attribute the decline 14

of enterprise value to goodwill impairment, there is a very high probability that the goodwill for these companies has been impaired. Whether a company underperforms industry norms by 10%, or is in the lowest quartile, or underperforms by a standard deviation or more, there is some level at which management s decision to continue to carrying goodwill should be subject to a very high level of scrutiny and justification. The 10% underperformance level might simply be the threshold at which management s burden to justify its actions increases substantially. Questions for future research include the benefits, if any, of codifying reasonableness tests as a standard auditing procedure, the level at which underperformance warrants additional disclosure, the impact of the business cycle on reasonableness testing, and the potential for litigation should users begin reasonableness testing management s impairment decisions. V Conclusion Evidence suggests that a significant number of companies with goodwill are not properly testing it for impairment under the provisions of SFAS142 (2001). Goodwill impairment testing involves comparison of the fair value of goodwill and related assets to their book value. If the fair value of a reporting unit less the fair value of non-goodwill assets is less than booked value of goodwill, then goodwill is impaired and must be written down to its fair value. Tracing goodwill and other assets to reporting units post acquisition and valuing a reporting unit involves many management judgments. The bases of these judgments are rarely disclosed in sufficient detail to allow analysts or investors to critically evaluate management s impairment analysis. Valuation complexity and lack of information means financial statement users are confronted with a black box analysis and companies have a significant opportunity 15

for earnings management. In fact, data in this and other studies provide substantial evidence that goodwill is not being properly tested. In 2005, approximately 2,724 companies with $2.3 trillion of goodwill found only 0.54% of that goodwill impaired. In 2006 some 2697 companies with $2.4 trillion of goodwill found only 0.65% of goodwill impaired. Such a low level of impairment strains credulity. One can construct a reasonableness test of whether goodwill is impaired by comparing a firm s return on assets to historical industry norms. Firm value is related to performance. When return drops below historical industry norms, enterprise value diminishes, and with it, the value of booked goodwill. This article does not attempt to replace the guidance on goodwill impairment outlined in SFAS142 (2001), nor does it purport to identify every instance in which goodwill is impaired. However, it does suggest a reasonableness test that auditors, analysts and others can use to determine whether decisions not to write down goodwill are reasonable. Companies that fall below industry norms should receive enhanced scrutiny when they claim their goodwill is not impaired. 16

Table 1 Impairment Analysis An analysis of the 4,815 largest companies in terms of assets on Compustat for 2005 and 2006 showed that 2,740 had booked goodwill in 2005 and 2701 had booked goodwill in 2006. Most of the dollar value of goodwill impairments for these two years can be attributed to six companies in 2005 and four companies in 2006 that wrote off more than a billion of goodwill each. The remaining 2,724 companies in 2005 wrote off only 0.54% of goodwill and the remaining 2,697 companies in 2006 wrote off only 0.65% of goodwill. Amounts are millions of dollars. In 2005, 2730 companies had $2,361,070.1 million of booked goodwill after $109,011.4 million was found impaired and written off. Description Companies Goodwill Amount Percent of Companies Percent of Goodwill Percent of Impairments Total impairments 246 109,011.4 9.01% 4.41% 100.00% Impairments over $1 billion 6 95,777.1 0.22% 3.88% 87.86% Impairments under $1 billion 240 13,234.3 8.79% 0.54% 12.14% No recorded impairment 2,484 2,361,070.1 90.99% 95.59% Total companies with goodwill 2,730 In 2006, 2701 companies had $2,449,465.7 million of booked goodwill after $29,243.0 was found impaired and written off. Description Companies Goodwill Amount Percent of Companies Percent of Goodwill Percent of Impairments Total impairments 245 29,243.0 9.07% 1.19% 100.00% Impairments over $1 billion 4 13,358.3 0.15% 0.55% 45.68% Impairments under $1 billion 241 15,884.6 8.92% 0.65% 54.32% No recorded impairment 2,456 2,449,465.7 90.93% 100.00% Total companies with goodwill 2,701 17

Table 2 Historical Industry Performance This is an analysis of historical industry performance in terms of return on assets for the ten year period 1995 to 2004. Industry classification is based on the Fama- French (1997) model. Years is the number of years of operating history available for a particular industry over the subject period. Industry Years Mean Std.dev Q1 Median Q3 Industry Years Mean Std.dev Q1 Median Q3 Aero 143 13.72% 5.81% 17.08% 13.80% 10.28% Hlth 555 15.21% 13.17% 21.48% 14.67% 9.58% Agric 125 10.97% 7.60% 15.06% 10.07% 5.08% Hshd 604 15.58% 9.45% 21.38% 15.69% 10.54% Autos 626 13.94% 9.43% 18.28% 13.36% 8.79% Insur 1304 6.38% 8.11% 9.42% 4.25% 1.92% Banks 5146 3.11% 3.20% 3.20% 2.60% 2.09% LabEq 717 9.84% 14.06% 19.11% 11.39% 3.15% Beer 168 15.14% 7.45% 20.56% 14.10% 11.53% Mach 1261 12.36% 11.03% 18.27% 12.46% 7.27% BldMt 671 15.53% 9.76% 20.08% 15.08% 10.99% Meals 660 15.81% 8.52% 21.00% 15.79% 10.24% Books 336 16.26% 11.47% 20.75% 16.01% 11.47% MedEq 857 9.33% 18.21% 20.67% 13.58% 1.82% Boxes 144 15.11% 5.21% 18.65% 14.50% 11.81% Mines 164 15.18% 8.92% 20.24% 14.90% 10.18% BusSv 3749 9.32% 19.78% 19.32% 10.94% 1.96% Misc 261 12.45% 11.62% 18.76% 10.77% 6.43% Chems 733 13.96% 6.13% 17.82% 11.69% 9.73% Paper 503 14.23% 7.48% 18.34% 13.42% 9.18% Chips 2242 9.51% 15.65% 9.40% 1.18% -7.74% PerSv 352 16.21% 12.26% 24.42% 15.10% 8.11% Clths 549 15.11% 12.87% 21.13% 14.41% 8.65% Retail 2003 15.42% 11.13% 20.44% 14.81% 10.46% Cnstr 413 12.17% 8.60% 16.40% 12.25% 6.38% RlEst 300 8.85% 9.02% 13.36% 8.11% 4.05% Coal 46 11.95% 11.27% 21.07% 10.77% 6.69% Rubbr 329 14.17% 7.25% 18.91% 13.96% 10.16% Comps 1340 6.42% 17.90% 16.37% 8.75% -0.29% Ships 80 11.51% 10.04% 15.86% 11.88% 5.63% Drugs 1341 0.57% 24.79% 18.45% 6.47% -16.10% Smoke 62 26.28% 24.44% 32.35% 21.42% 11.79% ElcEq 572 10.61% 15.86% 18.48% 12.94% 6.99% Soda 99 15.01% 7.86% 17.81% 14.21% 11.75% Enrgy 1215 17.24% 12.03% 22.36% 16.71% 10.96% Steel 658 12.11% 7.86% 16.59% 11.37% 9.74% FabPr 132 13.09% 6.87% 16.13% 12.75% -3.81% Telcm 1442 11.38% 13.83% 19.23% 12.63% 3.60% Fin 1056 15.00% 23.09% 17.85% 9.08% 5.45% Toys 268 14.31% 14.96% 19.59% 13.61% 8.45% Food 527 15.03% 9.23% 19.74% 14.88% 10.22% Trans 1099 13.66% 14.96% 18.44% 9.97% 8.73% Fun 440 15.73% 11.77% 18.75% 13.81% 9.61% Txtls 166 13.61% 9.83% 16.41% 12.86% 8.69% Gold 191 5.38% 14.04% 13.53% 8.15% 2.22% Util 1539 10.78% 4.60% 13.08% 11.10% 9.41% Guns 68 13.14% 8.68% 16.21% 12.29% 8.76% Whlsl 1263 10.96% 9.16% 15.56% 12.21% 6.58% 18

Table 3 Comparison to Industry Norms This table is an analysis of companies with goodwill that fall below industry averages. Here n is the number of companies in an industry, and m, it the number of those companies which have booked goodwill. For the columns headed As Reported, 10%+ is the number of goodwill companies that underperformed industry norms by at least 10%, lowest quartile is the number of companies with goodwill that fell in the lowest quartile of industry performance, and 1.0 σ is the number of companies that fell at least 1 standard deviation below the industry mean. For the columns headed If Goodwill written off indicates how many companies would under perform by 10%+, be in the lowest quartile or be 1.0 σ below norms if its goodwill had been written off in a prior period. Industry classification follows the Fama and French (1997) model. -----As Reported----- If Goodwill written -----------off---------- -----As Reported----- If Gooodwill written -------------off----------- 10%+ 1.0 10%+ 1.0 10%+ 1.0 10%+ below Lowest below Lowest below Lowest below Lowest Industry n m mean Quart. σ mean Quart. σ Industry n m mean Quart. σ mean Quart. 1.0 σ Aero 21 18 11 6 1 8 3 1 Hlth 86 76 22 13 2 18 10 2 Agric 12 8 3 0 0 3 0 0 Hshld 60 46 23 13 4 21 8 4 Autos 70 52 30 20 5 29 15 5 Insur 167 94 51 22 1 51 22 1 Banks 755 32 2 1 0 2 0 0 LabEq 84 64 20 6 2 19 6 2 Beer 14 11 4 1 1 3 1 1 Mach 135 114 38 16 4 33 14 4 BldMt 70 53 23 9 1 14 7 0 Meals 91 67 34 14 10 31 12 10 Books 41 38 21 16 3 15 9 3 MedEq 105 77 13 5 0 13 5 0 Boxes 16 14 8 4 4 6 4 1 Mines 23 12 2 2 0 2 1 0 BusSv 463 400 97 24 2 85 23 2 Misc 22 20 10 3 0 8 3 0 Chems 96 74 30 12 5 22 12 5 Paper 55 44 30 15 4 24 14 3 Chips 228 171 56 3 3 56 3 3 PerSv 46 37 17 9 1 16 8 1 Clths 62 42 13 9 1 13 8 1 Retail 221 144 62 33 8 55 28 8 Cnstr 54 42 16 5 3 16 5 3 RlEst 43 17 2 1 0 2 1 0 Coal 12 4 2 0 0 2 0 0 Rubbr 43 36 22 12 7 17 10 6 Comps 126 92 23 11 1 22 11 1 Ships 12 6 0 0 0 0 0 0 Drugs 110 77 4 2 1 4 2 1 Smoke 8 7 5 1 0 4 1 0 ElcEq 54 48 9 7 0 9 5 0 Soda 12 8 3 3 1 3 2 1 Enrgy 188 87 20 8 1 20 8 1 Steel 61 40 11 8 1 10 6 1 FabPr 9 8 2 3 0 2 3 0 Telcm 179 137 34 8 0 29 8 0 Fin 175 79 50 31 1 48 30 1 Toys 27 19 8 4 0 8 2 0 Food 64 46 22 6 3 16 6 3 Trans 149 77 29 9 1 29 9 1 Fun 66 46 28 17 5 26 12 5 Txtls 14 7 1 0 0 1 0 0 Gold 25 5 1 1 0 1 1 0 Util 295 30 12 10 4 12 10 4 Guns 6 3 0 0 0 0 0 0 Whlsl 140 101 32 15 4 31 13 4 19

Appendix A Industry classifications This appendix is based on the Fama and French (1997) industry classifications plus the classification of the omitted SIC code of 3690 classified as electrical equipment, ElcEq. SIC range Code Industry SIC range Code Industry 0100-0799 Agric Agriculture 2850-2899 Chems Chemicals 0800-0899 BldMt Construction Materials 2900-2911 Enrgy Petroleum and Natural Gas 0900-0999 Toys Recreational Products 2950-2952 BldMt Construction Materials 1000-1039 Mines Nonmetallic Mining 2990-2999 Enrgy Petroleum and Natural Gas 1040-1049 Gold Precious Metals 3000-3000 Rubbr Rubber and Plastic Products 1060-1099 Mines Nonmetallic Mining 3010-3011 Autos Automobiles and Trucks 1200-1299 Coal Coal 3020-3021 Clths Apprel 1310-1389 Enrgy Petroleum and Natural Gas 3050-3099 Rubbr Rubber and Plastic Products 1400-1499 Mines Nonmetallic Mining 3100-3111 Clths Apprel 1500-1549 Cnstr Construction 3130-3159 Clths Apprel 1600-1699 Cnstr Construction 3160-3199 Hshld Consumer Goods 1700-1799 Cnstr Construction 3200-3219 BldMt Construction Materials 2000-2046 Food Food Products 3210-3221 Boxes Shipping Containers 2047-2047 Hshld Consumer Goods 3229-3231 Hshld Consumer Goods 2048-2048 Agric Agriculture 3240-3259 BldMt Construction Materials 2050-2063 Food Food Products 3260-3260 Hshld Consumer Goods 2064-2068 Soda Candy and Soda 3261-3264 BldMt Construction Materials 2070-2079 Food Food Products 3262-3263 Hshld Consumer Goods 2080-2085 Beer Alcoholic Beverages 3269-3269 Hshld Consumer Goods 2086-2087 Soda Candy and Soda 3270-3299 BldMt Construction Materials 2090-2095 Food Food Products 3300-3369 Steel Steel Works, etc. 2096-2097 Soda Candy and Soda 3390-3399 Steel Steel Works, etc. 2098-2099 Food Food Products 3400-3400 FabPr Fabricated Products 2100-2199 Smoke Tobacco Products 3410-3412 Boxes Shipping Containers 2200-2295 Txtls Textiles 3420-3442 BldMt Construction Materials 2296-2296 Autos Automobiles and Trucks 3443-3444 FabPr Fabricated Products 2297-2299 Txtls Textiles 3446-3452 BldMt Construction Materials 2300-2390 Clths Apprel 3460-3479 FabPr Fabricated Products 2391-2392 Hshld Consumer Goods 3480-3489 Guns Defense 2393-2395 Txtls Textiles 3490-3499 BldMt Construction Materials 2396-2396 Autos Automobiles and Trucks 3510-3536 Mach Machinery 2397-2399 Txtls Textiles 3537-3537 Autos Automobiles and Trucks 2400-2439 BldMt Construction Materials 3540-3569 Mach Machinery 2440-2449 Boxes Shipping Containers 3570-3579 Comps Computers 2450-2459 BldMt Construction Materials 3580-3599 Mach Machinery 2490-2499 BldMt Construction Materials 3600-3621 ElcEq Electrical Equipment 2510-2519 Hshld Consumer Goods 3622-3622 Chips Electronic Equipment 2520-2549 Paper Business Supplies 3623-3629 ElcEq Electrical Equipment 2590-2599 Hshld Consumer Goods 3630-3639 Hshld Consumer Goods 2600-2639 Paper Business Supplies 3640-3646 ElcEq Electrical Equipment 2640-2659 Boxes Shipping Containers 3647-3647 Autos Automobiles and Trucks 2670-2699 Paper Business Supplies 3648-3649 ElcEq Electrical Equipment 2700-2749 Books Printing and Publishing 3650-3652 Toys Recreational Products 2750-2759 BusSv Business Services 3660-3660 ElcEq Electrical Equipment 2760-2761 Paper Business Supplies 3661-3679 Chips Electronic Equipment 2770-2799 Books Printing and Publishing 3680-3689 Comps Computers 2800-2829 Chems Chemicals 3691-3692 ElcEq Electrical Equipment 2830-2836 Drugs Pharmaceutical Products 3693-3693 MedEq Medical Equipment 2840-2844 Hshld Consumer Goods 3694-3694 Autos Automobiles and Trucks 20

Appendix A continued SIC range Code Industry SIC range Code Industry 3695-3695 Comps Computers 5800-5813 Meals Restaurants, Hotel, Motel 3690-3690 ElcEq Electrical Equipment 5890-5890 Meals Restaurants, Hotel, Motel 3699-3699 ElcEq Electrical Equipment 5900-5999 Retail Retail 3700-3716 Autos Automobiles and Trucks 6000-6099 Banks Banking 3720-3729 Aero Aircraft 6100-6199 Banks Banking 3730-3731 Ships Shipbuilding, Railroad Eq. 6200-6299 Fin Trading 3732-3732 Toys Recreational Products 6300-6399 Insur Insurance 3740-3743 Ships Shipbuilding, Railroad Eq. 6400-6411 Insur Insurance 3750-3751 Hshld Consumer Goods 6500-6553 RlEst Real Estate 3760-3769 Guns Defense 6700-6799 Fin Trading 3790-3792 Autos Automobiles and Trucks 7000-7019 Meals Restaurants, Hotel, Motel 3795-3795 Guns Defense 7020-7021 PerSv Personal Services 3799-3799 Autos Automobiles and Trucks 7030-7039 PerSv Personal Services 3800-3800 Hshld Consumer Goods 7040-7049 Meals Restaurants, Hotel, Motel 3810-3810 Chips Electronic Equipment 7200-7212 PerSv Personal Services 3811-3811 LabEq Measuring and Control Eq. 7213-7213 Meals Restaurants, Hotel, Motel 3812-3812 Chips Electronic Equipment 7215-7299 PerSv Personal Services 3820-3830 LabEq Measuring and Control Eq. 7300-7372 BusSv Business Services 3840-3851 MedEq Medical Equipment 7373-7373 Comps Computers 3860-3879 Hshld Consumer Goods 7374-7394 BusSv Business Services 3900-3900 Misc Miscellaneous 7395-7395 PerSv Personal Services 3910-3919 Hshld Consumer Goods 7397-7397 BusSv Business Services 3930-3949 Toys Recreational Products 7399-7399 BusSv Business Services 3950-3955 Paper Business Supplies 7500-7500 PerSv Personal Services 3960-3961 Hshld Consumer Goods 7510-7519 BusSv Business Services 3965-3965 Clths Apprel 7520-7549 PerSv Personal Services 3990-3990 Misc Miscellaneous 7600-7699 PerSv Personal Services 3991-3991 Hshld Consumer Goods 7800-7841 Fun Entertainment 3993-3993 BusSv Business Services 7900-7999 Fun Entertainment 3995-3995 Hshld Consumer Goods 8000-8099 Hlth Healthcare 3996-3996 BldMt Construction Materials 8100-8199 PerSv Personal Services 3999-3999 Misc Miscellaneous 8200-8299 PerSv Personal Services 4000-4099 Trans Transportation 8300-8399 PerSv Personal Services 4100-4199 Trans Transportation 8400-8499 PerSv Personal Services 4200-4299 Trans Transportation 8600-8699 PerSv Personal Services 4400-4499 Trans Transportation 8700-8748 BusSv Business Services 4500-4599 Trans Transportation 8800-8899 PerSv Personal Services 4600-4699 Trans Transportation 8900-8999 BusSv Business Services 4700-4799 Trans Transportation 9900-9999 Misc Miscellaneous 4800-4899 Telcm Telecommunications 5800-5813 Meals Restaurants, Hotel, Motel 4900-4999 Util Utilities 5890-5890 Meals Restaurants, Hotel, Motel 5000-5099 Whlsl Wholesale 5900-5999 Retail Retail 5100-5199 Whlsl Wholesale 6000-6099 Banks Banking 5200-5299 Retail Retail 6100-6199 Banks Banking 5300-5399 Retail Retail 6200-6299 Fin Trading 5400-5499 Retail Retail 6300-6399 Insur Insurance 5500-5599 Retail Retail 6400-6411 Insur Insurance 5600-5699 Retail Retail 6500-6553 RlEst Real Estate 5700-5736 Retail Retail 6700-6799 Fin Trading 21

References Compustat. Standard & Poor's, a Division of the McGraw-Hill Companies, Inc. New York. 2007. Statement of Financial Accounting Concepts No. 6 Elements of Financial Statements, (SFAC 6) Financial Accounting Standards Board. Norwalk, CT. June 1985, 175. Statement of Financial Accounting Standards No. 131, Disclosures about Segments of an Enterprise and Related Information, (SFAS131). Financial Accounting Standards Board. Norwalk CT. June 1997. Statement of Financial Accounting Standards No. 141 Business Combinations, (SFAS 141 revised 2007) Financial Accounting Standards Board. Norwalk, CT. June 2001. Statement of Financial Accounting Standards No. 142 Goodwill and Other Intangible Assets, (SFAS 142) Financial Accounting Standards Board. Norwalk, CT. June 2001 Statement of Financial Accounting Standards No. 157 Fair Value Measurements. (SFAS157) Financial Accounting Standards Board. Norwalk, CT. September 2006. Esquivel, Omar and Sylwia Gornik-Tomaszewski. 2007. Fair Value Measurements in Impairment Testing: How SFAS No.157 Increases Consistency and Comparability, Review of Business. Vol.27 Iss.4 pp.19-24. Fama, Eugene F. and Kenneth R. French. 1997. Industry Costs of Equity, Journal of Financial Economics. Vol.42 pp.153-193. Franciis, Jennifer J. Douglas Hanna and Linda Vincent. 1996. Causes and effects of Discretionary Asset Write-Offs, Journal of Accounting Research. Vol 34. Supp. pp.117-134. Hayn, Carla and Hughes, Patricia J. 2006. Leading Indicators of Goodwill Impairment, Journal of Accounting, Auditing and Finance. Vol.21 Iss.3 Summer. pp.223-265. Herz, Robert H.; Teresa E. Iannaconi; Laureen A. Maines; Krishna Palepu; Stephen G. Ryan; Katherine Schipper; Cathrine M. Schrand; Douglas J. Skinner; and Linda Vincent. Equity Valuation Models and Measuring Goodwill Impairment, Accounting Horizons. Vol.15 No.2 June. pp.161-170. Hirschey, Mark J. and Richardson, Vernon J. 2003. Investor Under Reaction to Goodwill Writeoffs, Financial Analysts Journal. Vol.59 Iss.6 Nov./Dec. pp.75-84. Lander, G. and A. Reinstein. 2003. Models to Measure Goodwill Impairment, International Advances in Economic Research, Aug. Vol. 9 Issue 3, p227-232 22

Massoud, M. F. and Raiborn, C. A. 2003. Accounting for Goodwill: Are We Better Off? Review of Business, Spring, Vol. 24 Issue 2, 26-32 Vance, David E. 2005 Raising Capital. Springer, New York. pp.150-155. Vance, David E. 2003. Financial Analysis and Decision Making. McGraw-Hill, New York. pp143-154. Williams, J. B. 1938. The Theory of Investment Value. Cambridge, MA. Harvard University Press. 23