The Effect of SFAS 141 and 142 on the Market for Corporate Control

Ashiq Ali and Todd Kravet

Navin Jindal School of Management, University of Texas at Dallas

ashiq.ali@utdallas.edu kravet@utdallas.edu

September 27, 2012

Abstract We investigate the effects of accounting rule changes that eliminate the pooling method (SFAS 141) and goodwill amortization (SFAS 142) on the form of acquisition financing and on a firm’s takeover probability. The primary requirement to qualify for the pooling method is structuring the transaction as a stock-for-stock exchange. We find that before the new accounting rules, target firms’ step-up value is positively associated with the probability of using stock-for-stock as against partial stock financing. After the new rules, this association decreases significantly and is indistinguishable from zero. These results suggest that in the pre SFAS 141 period, greater use of stock-for-stock exchanges for target firms with larger step-up values was motivated by the favorable effect of the pooling method on the reported income of the acquirer, and this motivation to use stock-for-stock exchanges goes away with the elimination of the pooling method. The new rules also resulted in a greater decrease in takeover probability for firms with larger step-up values than for firms with smaller step-up values, presumably due to the elimination of the pooling method. When the step-up value of a firm is composed primarily of goodwill, the above effect is attenuated, consistent with the elimination of goodwill amortization. Overall, the study uses a natural experiment to provide a novel finding that accounting methods have significant effects on the form of acquisition financing and on takeover probability.

We appreciate the helpful comments of Jarrad Harford, Bob Holthausen, and workshop participants at Hong Kong University of Science and Technology, London Business School, London School of Economics, State University of New York at Buffalo, and the University of Houston.

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The Effect of SFAS 141 and 142 on the Market for Corporate Control

I. INTRODUCTION

This study investigates the effects of Statement of Financial Accounting Standard

(SFAS) 141 and 142, enacted in 2001, on the form of financing used for corporate takeovers and

on the probability of a takeover. These standards eliminated the pooling-of-interests method of

accounting for acquisitions (SFAS 141) and amortization of goodwill (SFAS 142), representing

the most significant change to acquisition accounting in at least three decades.1 When these

standards were proposed, there was substantial debate over the effect these standards would have

on financial statements and acquisition activity. Over 500 comment letters were received by the

Financial Accounting Standards Board (FASB) related to the original and revised Exposure

Drafts 201-A and 201-R that preceded these standards. Both houses of the US Congress held

hearings on the elimination of pooling with most congresspersons arguing against its elimination

or concurrently eliminating goodwill amortization (US House 2000; US Senate 2000; Ramanna

2008). While supporters of pooling method elimination argued that the pooling method results in

less useful financial statements, the opposition argued that managers would forgo some business

combinations without the pooling method option.2 We examine the validity of the opposition’s

claim.

Prior literature provides evidence that managers have incentives to structure stock-for-

stock financed acquisitions as pooling acquisitions instead of purchase acquisitions and are

                                                                                                                         1 Hereafter, we refer to the pooling-of-interests method simply as the pooling method and acquisitions using the pooling and purchase method as ‘pooling acquisitions’ and ‘purchase acquisitions’, respectively. The terms acquirer and target refer to the two parties in the acquisition transaction. 2 FASB comment letter from Dennis Powell, CISCO Corporate Controller, states “We believe the retention of pooling of interests accounting is particularly critical considering the adverse impact its elimination will have on the merger activity in the United States ...”  

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willing to incur significant costs to achieve this goal, including paying higher acquisition

premiums and accepting restrictions on stock repurchases (e.g., Lys and Vincent 1995; Aboody

et al. 2000; Ayers et al. 2002; Weber 2004).3 The benefits of pooling method accounting are

shown to be related to the reporting of lower total assets and higher net income relative to the

purchase method. Under the purchase method, acquirers consolidate the financial statements

using the purchase price of the target’s net assets. The target’s identifiable assets and liabilities

are recorded at their fair value and any portion of the purchase price that cannot be specifically

attributable to an identifiable asset or liability is recorded as goodwill. In pooling acquisitions,

the target’s net assets are combined with the acquirer’s financial statements at book value.

Therefore, even if the purchase price exceeds the net book value of assets, pooling acquisitions

result in no goodwill amortization expense and other assets (e.g., fixed assets and inventory) are

expensed at lower amounts relative to purchase acquisitions, leading to higher reported income.

The greater the difference between the purchase price and the target’s book value of net assets,

referred to as the step-up value, the larger is the difference in reported net income between the

two methods.

The primary requirement to qualify for the pooling method is structuring the transaction

as a stock-for-stock exchange as against a partial stock exchange or 100 percent cash payment. If

firms structure acquisitions as stock-for-stock exchanges to satisfy the pooling method

requirements, then we expect that elimination of the pooling method under SFAS 141 would

decrease stock-for-stock financed acquisitions, especially of targets with large step-up values.

We also predict that SFAS 141 and 142 affect a firm’s takeover probability. Elimination

of the pooling method under SFAS 141 makes acquisitions less attractive because compared to

                                                                                                                         3 Stock-for-stock financed acquisitions refer to the use of only common stock as consideration to acquire target firms’ common stock.

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the pooling method, the purchase method results in less favorable financial statements of the

acquirers. On the other hand, replacement of goodwill amortization with annual impairment

testing under SAS 142 would attenuate the unfavorable effect of the elimination of the pooling

method on takeover probability. This is because under SFAS 142 reported income of the

acquirers under the purchase method are likely to be higher given that goodwill amortization

expense is not recorded and managers would have considerable discretion to defer the reporting

of goodwill impairments (Beatty and Weber 2006; Ramanna 2008; Ramanna and Watts 2012).

First, we empirically examine the effect of the new accounting rules on the use of stock-

for-stock financing for acquisitions. We find that before the new accounting rules, target firms’

step-up value is positively associated with the probability of using stock-for-stock as against

partial stock financing, consistent with acquirers’ greater incentive to report the acquisitions

using the pooling method when the target’s step-up value is higher. After the new rules, this

association decreases significantly, consistent with the elimination of the pooling method. The

effect on stock-for-stock financing is also economically significant. Before the new rules, the

interquartile difference in step-up value of target firms is associated with an 18 percent greater

likelihood of stock-for-stock financing. This difference decreases significantly and becomes

indistinguishable from zero after the new rules. Finally, the decrease in the use of stock-for-stock

financing is unlikely to be driven by other incentives related to the use of equity as against cash,

because we do not obtain similar results when we repeat our analysis after replacing the

dependent variable stock-for-stock versus partial stock financing with partial stock versus 100

percent cash financing.

Next, we examine the effect of the new accounting rules on corporate takeovers. We use

a sample consisting of firms that were taken over and control firms matched on industry and firm

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size. We find that the new accounting rules are associated with a significantly greater decrease in

takeover probability for firms with higher estimated step-up values and that this effect is less

pronounced for firms that are likely to report a greater component of their estimated step-up

value as goodwill. These results suggest that the elimination of the pooling method had a

negative effect on takeover probability and the elimination of goodwill amortization attenuated

this effect for firms with estimated step-up values composed primarily of goodwill. The effect on

takeover probability is also economically significant. Before the new rules, the interquartile

difference in expected step-up value of firms is associated with a 2.4 percent lower probability of

a takeover, and after the new rules, it is associated with an additional 3.5 percent lower

probability of a takeover. However firms with estimated step-up value composed primarily of

goodwill experience an insignificant effect on the probability of takeover due to the new rules.

The enactment of SFAS 141 and 142 coincided with the boom period during the latter

half of the 1990s and the market crash in 2001. In order to rule out any related confounding

effects, we perform additional analyses. First, we include several market-wide variables as

controls in our form of acquisition financing and takeover probability models. Second, we allow

for the association between the dependent variable and each of the control variables to differ

before and after the new accounting rules. Third, we repeat our analyses after deleting

observations from 1994 to 2001 in order to rule out the possibility that our results are driven by

the abnormally high stock prices during this period. Finally, we repeat our analyses after deleting

high technology firms from all of our sample periods. These tests rule out the possibility that the

extreme changes in stock prices of high technology firms during our sample period are

responsible for our results. Our results are robust to all of these tests.

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Our study makes the following contributions. It contributes to the literature on the

economic consequences of accounting method changes by documenting that the elimination of

the pooling method option (SFAS 141) affected the form of acquisition financing. Specifically,

SFAS 141 decreased the likelihood that an acquisition is financed by stock-for-stock exchange as

against partial stock exchange or only cash consideration, especially of targets with large step-up

values. Prior related studies do not examine the effect of accounting method changes on the form

of acquisition financing. Aboody et al. (2000) and Ayers et al. (2002) examine the effect of

managerial incentives related to earnings-based compensation plans and debt contracts on the

decision to structure stock-for-stock exchange transactions as pooling acquisitions instead of

purchase acquisitions.4 Their sample consists of only stock-for-stock acquisition transactions.

Hence, it was not possible to examine the effect of accounting method on the form of acquisition

financing in their setting.

Another related study, Lys and Vincent (1995), uses anecdotal evidence to show the

effect of accounting method on the form of acquisition financing. They point out that AT&T

stated in their merger agreement with NCR that if pooling is not allowed, it would change the

payment form from 100 percent stock to only 60 percent stock. Our study contributes beyond

Lys and Vincent (1995) by using a large sample and a natural experiment of mandated

accounting rule changes to provide a more generalized conclusion that acquisition accounting

method influences the form of acquisition financing.

Our study contributes further to the literature on the economic consequences of

accounting method changes by documenting that the elimination of the pooling method (SFAS

                                                                                                                         4 Earlier literature, such as Gagnon (1967), Copeland and Wojdak (1969), and Anderson and Louderback (1975), limit their sample either to only stock-for-stock acquisitions or where stock makes up at least 80% of the consideration offered and test the incentive to make pooling versus purchase acquisitions. Hence, it was not possible to examine the effect of accounting method on the form of acquisition financing in their setting as well.

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141) and the elimination of goodwill amortization (SFAS 142) have affected the likelihood of

takeover of a firm. Specifically, elimination of the pooling method decreased the likelihood of

takeover, particularly for firms with large estimated step-up values, and the elimination of

goodwill amortization attenuated this effect, particularly for firms with estimated step-up values

composed largely of goodwill.5 To date, there has been little evidence in the literature on the

effect of acquisition accounting methods on takeover probability. Prior studies show that

managers are willing to incur significant costs, such as higher acquisition premiums and

restrictions on stock repurchases, to structure stock-for-stock financed acquisitions as pooling

acquisitions instead of purchase acquisitions (e.g., Aboody et al. 2000; Ayers et al. 2002; Weber

2004). However, no prior study has examined whether accounting method effects are strong

enough to affect the decision to acquire or not.

Finally, our study contributes to the finance literature on the determinants of the

likelihood of a takeover and on the determinants of the form of acquisition financing. Prior

studies have focused on fundamental economic factors, e.g., operational synergies and riskiness

of the combined firm. Betton et al. (2008) provide a survey of this literature. Our study is the

first to show that acquisition accounting methods also play a significant role in the takeover

decision and in the decision on the form of acquisition financing.

The remainder of the paper is organized as follows. Section 2 describes the old and new

acquisition accounting rules, discusses the related prior literature, and then presents our

hypotheses. Section 3 reports results of the analyses of the effect of the changes in accounting

rules on acquisition financing. Section 4 presents results of the analyses of the effect of the

                                                                                                                         5 We are silent on whether acquisition decisions are more or less efficient after the implementation of SFAS 141 or 142. It is an interesting issue, but would require a rather detailed analysis. Thus, we leave the examination of this issue for future research.

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changes in accounting rules on takeover probability. Section 5 discusses the robustness of our

results and Section 6 concludes.

II. HYPOTHESIS DEVELOPMENT

Accounting Principles Board (APB) Opinion 16 was issued in 1970 and established the

criteria for the pooling and purchase method of accounting, until SFAS 141 became effective on

June 30, 2001.6 To qualify for the pooling method under APB 16, the acquirer needed to issue

voting common stock in exchange for at least 90 percent of the outstanding voting common

shares of the target firm (AICPA 1970a) and had to satisfy 13 other restrictions. These

restrictions mostly relate to changes in equity interests of the target and acquirer for two years

before the acquisitions.7 The acquirer was also restricted from agreeing as part of the transaction

to issue or repurchase equity after the acquisition.8 However, there are no requirements that the

target should be of a similar size to the acquirer. Transactions not satisfying the requirements of

the pooling method had to be accounted for using the purchase method.

The pooling method reports the assets and liabilities of the acquirer and target at their

book values. The assets of the target firm are expensed at their historical cost. In addition, target

net income from the beginning of the fiscal year is included in the net income of the combined

firm. The purchase method reports the assets and liabilities of the target firm at their fair value

and the difference between the purchase price and the fair value of the identifiable net assets is

                                                                                                                         6 Leftwich (1981) describes the development of these two standards which similar to SFAS 141 and 142 involved substantial controversies with the APB initially arguing for the elimination of the pooling method and then backing down because of political pressure. 7 The standard does allow for dividends to be paid that are consistent with previous regular dividend payments and for repurchases directly related to stock option, compensation plans, and the part of a repurchase plan that began two years before the acquisitions’ initiation. 8 SAB 96 restricted firms from repurchasing shares for up to two years following pooling acquisitions.

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recorded as goodwill. Also, target net income from the acquisition date onwards is included in

the net income of the combined firm.

SFAS 141 eliminated the pooling method and required all business combinations to be

accounted for using the purchase method. This standard primarily carries forward the majority of

APB Opinion 16’s implementation of the purchase method with a few changes, such as the fair

value of stock payments is determined on the acquisition date rather than at managers’ discretion

any date between the acquisition agreement and completion date.9

SFAS 142 superseded APB Opinion 17 and certain parts of SFAS 121. Under APB

Opinion 17 goodwill is amortized over its useful life or 40 years whichever is smaller.

Impairment tests under SFAS 121 are not required regularly, but are triggered by impairments in

the underlying assets and only recorded when the undiscounted cash flows of the assets are less

than the carrying value. The principal changes SFAS 142 instituted are elimination of goodwill

amortization and the requirement of annual impairment testing of goodwill.10 For fiscal years

beginning after December 15, 2001, firms are required to annually test for goodwill impairment

at the reporting unit level by first comparing the reporting unit’s fair value with the carrying

amount of net assets. If the fair value is less than the carrying amount of net assets, the reporting

unit’s fair value of goodwill is compared with the book value, and that determines if impairment

is recorded.11 This standard creates the potential for managers to use their discretion to avoid

                                                                                                                         9 SFAS 141(R) replaced SFAS 141 for acquisitions completed in fiscal years with beginning dates after December 15, 2008. Two important changes under SFAS 141 (R) are recognizing non-controlling interests at fair values and disallowing the immediate write-down of capitalized in-process research and development costs. While these changes generally make the financial reporting effect of the purchase method less favorable, they apply to only a small number of acquisitions in our sample. This standard also changed the official terminology from “purchase method” to “acquisition method” due to a longstanding argument that the former is a misnomer (see footnote 2 of APB Opinion 16).  10 SFAS 142 also eliminated amortization of intangible assets with indefinite useful lives. 11 Accounting Standards Update 2011-08 (FASB 2011) allows firms to use qualitative factors to assess whether a goodwill impairment is more likely than not, and if the answer is yes then the firm should perform the quantitative two-step goodwill impairment test instituted in SFAS 142. This standard is effective for fiscal years beginning after

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recording impairment losses because the implied fair value of goodwill is estimated. Several

studies present evidence consistent with managers using their discretion to defer the reporting of

goodwill write-downs under SFAS 142 (e.g., Beatty and Weber 2006; Ramanna 2008; Li and

Sloan 2010; Bens et al. 2011; Li et al. 2011; Ramanna and Watts 2012). With no goodwill

amortization expense and considerable discretion to defer the impairment of goodwill, the effect

of SFAS 142 on reported income is expected to be favorable.

The primary incentive to qualify for the pooling method is to increase reported net

income. If the fair value of target firms’ assets exceeds book values, that is, the step-up value is

positive, then the expenses recorded related to those assets are greater under the purchase method

than the pooling method. The fair values of liabilities are generally not expected to be

systematically biased in any direction relative to their book values. Overall, target firms with

positive step-up values will report a smaller net income of the combined firm using the purchase

method relative to the pooling method. Ayers et al. (2000) show that the pro-forma net income

effect of eliminating the pooling method on acquisitions from 1992 to 1997 is economically

significant. They estimate that step-up values of targets make up approximately 66 percent of the

purchase price. Furthermore, eliminating the pooling method decreases these firms’ earnings per

share and return on equity by 13 and 22 percent, respectively.

Prior studies provide results consistent with managers having incentives to structure

stock-for-stock transactions as pooling acquisitions rather than purchase acquisitions because of

higher reported income. Aboody et al. (2000) and Ayers et al. (2002) find that managers are

more likely to use the pooling method for stock-for-stock financed acquisitions when the step-up

value of the target is larger. Several earlier studies, based on relatively small samples of stock-

                                                                                                                                                                                                                                                                                                                                                                                                       December 15, 2011, which is after our sample period, and therefore does not apply to our sample. In any case, this accounting standard update does not affect the direction of our predicted relations.  

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for-stock financed acquisitions over various periods, from the 1950s to the 1980s, also find that

the likelihood of a pooling acquisition is positively associated with step-up values (e.g., Gagnon

1967; Copeland and Wojdak 1969; Anderson and Louderback 1975; Nathan 1988). Aboody et

al. (2000) also shows that among stock-for-stock financed acquisitions, incentives related to

earnings-based compensation plans and debt contracts are determinants of the pooling

acquisition choice. However, none of these studies examine how acquisition accounting

standards influence the choice of acquisition financing. Their sample consists of only stock-for-

stock financed acquisitions; hence it was not possible for them to examine the effect of

accounting method on the form of acquisition financing. Our study addresses this issue by

examining the effect of the mandated acquisition accounting rule changes on the form of

acquisition financing, 100% stock, versus partial stock or all cash. Prior studies have also shown

that firms incur significant costs to structure a stock-for-stock financed acquisition as a pooling

acquisition. Ayers et al. (2002) and Robinson and Shane (1990) find that among stock-for-stock

financed acquisitions, managers pay higher acquisition premiums for pooling acquisitions than

for purchase acquisitions. Hong et al. (1978) and Davis (1990) find that investors do not react

favorably to pooling acquisitions. Finally, Weber (2004) investigates the effect of SAB 96,

which disallows share repurchases in the two years following pooling acquisitions, on firms with

pending pooling acquisitions. He finds that managers generally elected to use the pooling method

and forgo share repurchases and that investors view this decision as costly. However, none of

these prior studies has examined whether the cost associated with the choice of accounting

method are substantial enough to influence the decision on whether to acquire or not. Our study

addresses this issue by examining the effect of the mandated acquisition accounting rule changes

on takeover probability.

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Overall, prior studies indicate that there are strong incentives to structure stock-for-stock

transactions such that they qualify for the pooling method. We argue that these same incentives

may influence managers to use stock-for-stock exchanges rather than partial stock exchanges or

only cash consideration, in order to qualify for the pooling method. These incentives are

expected to be stronger when the difference in net income under the pooling method versus the

purchase method is greater, and this occurs when the step-up value of the target firm is larger

than when it is smaller. Hence incentives related to reported income are likely to influence

managers to a greater extent in the use of stock-for-stock exchanges rather than partial stock

exchanges or only cash consideration when target firms have larger step-up values. Accordingly,

we propose the following hypothesis:

Hypothesis 1: The elimination of the pooling method under SFAS 141 led to a greater decrease in stock-for-stock exchanges in acquisitions of target firms with higher step-up values than of target firms with lower step-up values.

The elimination of the pooling method is likely to decrease management incentive to

acquire firms, because reported income under the purchase method tends to be lower. This

concern is expressed by parties opposing the elimination of the pooling method, including US

Senators (Abraham 2000) and corporate executives, such as Cisco’s Corporate Controller

(Powell 1999) and Goldman, Sachs & Co.’s Vice President of Accounting Policy (Mills 1999).

In response to this concern, FASB proposed that goodwill amortization be replaced with

annual impairment testing and recording of impairment losses if needed (FASB 2001a). The

elimination of goodwill amortization removes an unconditional periodic expense, mitigating the

negative effect on reported income from pooling method elimination (Ramanna 2008; Li and

Sloan 2010; Ramanna and Watts 2012), and thereby attenuates the negative effect of the

elimination of the pooling method on acquisition activity. Moreover, for acquisition transactions

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that would not have qualified for the pooling method before the new rules, elimination of

goodwill amortization is likely to affect reported income favorably, and thereby contribute

favorably to management incentive to acquire firms.

The decrease in takeover probability of a firm due to the elimination of the pooling

method is likely to be greater for firms with larger predicted step-up value, because the acquirers

of these firms would experience a greater decrease in reported income due to this accounting

method change. Furthermore, this effect is likely to be attenuated to a greater extent by the

elimination of goodwill amortization, when more of the predicted step-up value is made up of

goodwill. Accordingly, we propose the following hypothesis:

Hypothesis 2: The new acquisition accounting rules led to a greater decrease in the takeover probability of firms with higher predicted step-up values, and this effect is less pronounced for firms in which more of the predicted step-up value is made of goodwill.

III. STOCK-FOR-STOCK FINANCING OF ACQUISITIONS

Research Design

To test the effect of elimination of the pooling method under SFAS 141 on firms’

acquisition financing choice (hypothesis 1), we estimate a model of stock-for-stock financed

acquisitions versus partially stock-financed acquisitions.12 This method allows us to test that

conditional on a firm deciding to finance an acquisition at least partially with stock, did the

elimination of pooling decrease the likelihood of using a 100 percent stock-for-stock exchange

                                                                                                                         12 We classify acquisitions as stock-for-stock financed when the consideration is 100% common stock. However, APB 16 allows use of the pooling method in certain situations when the consideration includes at least 90% common stock. Pooling acquisitions with consideration including less than 100% common stock are classified as partial stock acquisitions in our sample and, therefore, bias against our predicted results. In any case, there are only 17 observations out of 269 with the percentage of stock consideration between 90% and 100% in our sample.

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differentially across target firms with high and low step-up values. Specifically, we estimate the

following logistic regression to test this hypothesis:

100% STOCKi,t = β0 + β1D_POSTi,t + β2STEPUPi,t + β3STEPUPi,t*D_POSTi,t + β4ACQUIRER_BTMi,t + β5ACQUIRER_RETi,t + β6ACQUIRER_INSTi,t + β7Ln(ACQ_CASH)i,t + β8ACQ_LEVERAGEi,t + β9ACQUIRER_MVi,t + β10TARGET_MVi,t + β11REL_DEALSIZEi,t + β12TARGET_ROAi,t + β13ΔS&P500i,t + β14TARGET_INSTi,t + εi,t (1)

where 100% STOCKi,t is an indicator variable equal to one if an acquisition is 100% stock-for-

stock financed and zero if it is a partial stock financed acquisition. Step-up in book value,

STEPUPi,t, is calculated as the difference between the transaction value, obtained from the SDC

database, and the book value of the target firm’s common equity, deflated by the combined total

assets of the acquirer and target firm as of the end of the fiscal quarter before the acquisition

announcement. D_POSTi,t, is an indicator variable which is equal to one if the acquisition is

announced after the effective date of SFAS 141, June 30, 2001, and is zero otherwise. Before

SFAS 141, we expect acquisitions of target firms with higher step-up values are more likely to

be financed with stock-for-stock exchanges, so that they could qualify for the pooling method

and thereby avoid the larger negative impact on the acquirer’s reported net income that would

arise under the purchase method. Therefore, we predict a positive coefficient on STEPUP. We

use the interaction of STEPUP and D_POST to test whether the adverse effect of SFAS 141 on

the use of stock-for-stock exchanges for acquisitions is greater for target firms with higher step-

up values than for target firms with lower step-up values. Since the benefit from using the

pooling method is greater for acquisitions of target firms with higher step-up values, the

incentive to finance acquisitions with stock-for-stock exchanges is greater. Consequently,

elimination of the pooling method is expected to result in a greater reduction of stock-for-stock

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financing for such acquisitions. Hence, we predict a negative coefficient on the interaction of

STEPUP and D_POST.

Based on the prior literature (e.g., Jung et al. 1996; Martin 1996; Erickson 1998; Ayers et

al. 2004; Dong et al. 2006), we include several control variables in equation (1).

ACQUIRER_BTMi,t is the ratio of book value of equity to market value of equity at the end of the

fiscal quarter prior to the acquisition announcement. ACQUIRER_RETi,t is firms’ 12-month buy-

and-hold stock return over the period ending at the end of the fiscal quarter prior to the

acquisition announcement minus the average 12-month buy-and-hold return for that firm’s size

decile. ACQUIRER_INSTi,t and TARGET_INSTi,t are the acquirer’s and target’s percentage of

institutional investors at the end of the calendar quarter prior to the acquisition announcement.

Ln(ACQ_CASH)i,t is the acquirer’s inflation-adjusted natural logarithm of total cash and short-

term investments at the end of the fiscal quarter prior to the acquisition announcement.13

ACQ_LEVERAGEi,t is the acquirer’s ratio of long-term debt to total assets at the end of the fiscal

quarter prior to the acquisition announcement. ACQUIRER_MVi,t and TARGET_MVi,t are the

acquirer’s and target’s inflation-adjusted market value, respectively, at the end of the fiscal

quarter prior to the acquisition announcement. REL_DEALSIZEi,t is the transaction value of the

acquisition divided by the market value of the acquiring firm at the end of the fiscal quarter prior

to the acquisition announcement. TARGET_ROAi,t is the target firm’s net income divided by total

assets for the last fiscal quarter prior to the acquisition announcement. ΔS&P500i,t is the change

in the Standard and Poor’s (S&P) 500 index over the 12 months preceding the acquisition

announcement. We also include year fixed effects which control for any year-specific macro

factors affecting the financing of acquisitions, including the capital gains tax rate. Industry fixed

                                                                                                                         13 To adjust for inflation we use the consumer price index for all urban consumers (CPI-U), where the base period for the adjustment factor is 1982-1984.

15    

effects at the 2-digit SIC level are also included. Continuous variables are winsorized at the 1st

and 99th percentile, except for variables bounded between zero and one.

Sample

Our sample consists of all completed acquisitions for the period 1983 to 2009 reported in

the Securities Data Company’s (SDC) Mergers and Acquisitions database, meeting the following

criteria: transaction value is available, acquirer is a public company, and SDC identifies the

acquisition as a merger (M) or acquisition of assets (AA). The sample begins in 1983 because

SDC has limited coverage of acquisition data in prior years. We also limit our sample to

acquisitions for which acquirers and target firms are public companies and we exclude

acquisitions where SDC indicates the type of financing is unknown. We exclude acquisitions

where the transaction value divided by the market value of the acquirer as of the end of the fiscal

quarter prior to the acquisition announcement is less than 5 percent, ensuring a sample of

acquisitions that are economically important to the acquirer. We also exclude financial firms.

Our final sample consists of 994 acquisitions made by 725 unique firms.

Panel A of Table 1 presents the frequency of acquisitions by year. The number of

acquisitions increases in the mid-1980’s and the late 1990’s. There are 395, 269, and 330

acquisitions that have stock-for-stock, partial stock, and 100 percent cash financing, respectively.

We also provide in parenthesis the average percentage stock component for partial stock

acquisitions. For the full sample, 56 percent of acquisition value is paid in the form of stocks,

suggesting that the stock component is substantial in partial stock acquisitions.14 Panel B

presents descriptive statistics of the variables in equation (1). D_POST has a mean value of

                                                                                                                         14 SDC does not provide the percentage of stock used for 18 observations they indicate as including a partial stock payment.

16    

0.336, indicating that around 34 percent of the acquisitions in our sample are announced after the

effective date of SFAS 141. STEPUP has a mean (median) value of 0.300 (0.170), indicating the

average step-up of the target firms’ net book value is 30 percent of the pre-acquisition total assets

of the combining firms. REL_DEALSIZE has a mean (median) value of 0.497 (0.294), indicating

that the acquisitions are on average economically significant events for acquiring firms.

Results

The regression results from estimating equation (1) are presented in Table 2. Column 1

results are based on the sample consisting of acquisitions with REL_DEALSIZE greater than 5

percent, and Column 2 results are based on a sample consisting of acquisitions with

REL_DEALSIZE greater than 25 percent. The second sample ensures that the acquisitions are

clearly important investments for the acquiring firms. In column 1, the coefficient on STEPUP is

significantly positive, suggesting that in the pre-SFAS 141 period the likelihood of stock-for-

stock financed acquisitions is greater for target firms with greater step-up values, presumably to

qualify as pooling acquisitions. The coefficient on STEPUP*D_POST is significantly negative,

supporting the hypothesis that after the elimination of the pooling method, the positive

association between the likelihood of stock-for-stock financed acquisitions and target step-up

values decreased significantly. Column 2 results are consistent with the results in Column 1, and

are stronger, as expected. The coefficient on STEPUP is significantly positive and the coefficient

on STEPUP*D_POST is significantly negative.15 Overall, the above results suggest that the

                                                                                                                         15 Several events occurred around the enactment of SFAS 141, such as the market crash during 2000 and 2001 and the passage of the Sarbanes-Oxley Act of 2002. A priori it is not clear that these other events would influence the coefficient on the variable STEPUP*D_POST. Nevertheless, as a sensitivity test we also include in the model interactions of each variable with D_POST to control for any change in the association of the likelihood of stock-for-stock financing with any of the control variables between pre- and post-SFAS 141 periods. On including these additional interactions in the model, the results remain qualitatively the same. Specifically, the coefficients (un-

17    

changes in accounting method for acquisitions had a significant effect on the form of acquisition

financing.

To illustrate the economic significance of the results, we report the change in the

probability of a stock-for-stock acquisition due to an increase in each independent variable from

the 1st to 3rd quartile (from 0 to 1 for indicator variables), holding the other variables at their

mean value. For the sample REL_DEALSIZE >25%, before SFAS 141, an increase in STEPUP

from the first to third quartile is associated with an increase in the use of a stock-for-stock

acquisition financing by 18 percent. The magnitude of the coefficient on STEPUP*D_POST is

about the same as that of the coefficient on STEPUP, suggesting that the effect of STEPUP on

the use of stock-for-stock acquisition financing essentially disappears after SFAS 141. Thus, the

change in accounting standards had an economically significant effect on the form of acquisition

financing.16

Focusing on the control variables, we observe that for coefficients that are significant, the

signs are in general consistent with the prior evidence in the literature. The coefficient on

institutional ownership is negative. This result suggests that institutional monitoring prevents

managers from making poor acquisition decisions, and stock-for-stock financed acquisitions are

poor decisions as they tend to experience negative announcement and post-acquisition stock

returns (Martin 1996; Agrawal and Jaffe 2000; Andrade et al. 2001; Fuller et al. 2002). The

negative coefficient on leverage in column 1 is consistent with Harford et al. (2009) who explain

that acquirers paying with equity are more likely to have larger growth opportunities and, thus be

                                                                                                                                                                                                                                                                                                                                                                                                       tabulated) on STEPUP and STEPUP*D_POST are 1.775 (p-value < 0.001) and -2.037 (p-value = 0.043), respectively. 16 Ai and Norton (2003) provide an alternative computation for calculating the directional effect and statistical significance of interactions in nonlinear models. However, Greene (2010) concludes that an overall statistical inference cannot be obtained from the Ai and Norton (2003) measure. Furthermore, Kolasinski and Seigel (2010) argue that it is appropriate to draw inferences from the interaction term in nonlinear models. Therefore, we use the interaction coefficient reported in Table 3 to assess the directional effect and economic significance of our results.

18    

less leveraged. The negative coefficient on acquirer firm size is consistent with Erickson (1998),

who argues that firm size captures access to debt markets (Rajan and Zingales 1995). The

positive coefficient on target firm size is consistent with the notion that the acquirer’s risk from

the acquisition increases with target firm size, and stock financing makes the target shareholders

bear some of the risk of the combined firm (Hansen 1987; Martin 1996; Ayers et al. 2004).

Finally, the coefficient on relative transaction size is negative. This result is consistent with the

univariate evidence in Martin (1996) and Eckbo et al. (1990), however, they do not provide any

explanation for it.17

To provide further support that the change in the association between step-up value and

stock-for-stock exchanges is driven by the elimination of pooling acquisitions rather than by

change in managers’ preference for equity-based financing due to some other factor18, we

compare partially stock-financed versus 100 percent cash-financed acquisitions. Because firms

cannot qualify for the pooling method with partially stock-financed acquisitions we do not

expect to find similar results as above, if elimination of pooling is driving the results.

Table 3 reports regression results of a model for which the dependent variable is

PARTIAL_STOCK, an indicator variable equal to one if the acquisition is financed partly with

common stock and zero if it is 100 percent cash financed. For this estimation, we use the sample

of acquisitions that are either partially stock-financed or 100 percent cash financed. As in Table

                                                                                                                         17 We also use alternative control variables for acquirers’ incentive to use equity financing when stock prices are overvalued (Shleifer and Vishny 2003; Rhodes-Kropf et al. 2005; Ang and Cheng 2006; Dong et al. 2006) by replacing the acquirers’ book to market ratio with both industry-adjusted book to market ratio and Rhodes-Kropf et al.’s (2005) firm-specific overvaluation measure and our conclusions remain the same. We also control for firm’s deviation from target leverage and our conclusions remain the same (Harford et al. 2009). 18  There are alternative explanations for an association between equity financing and step-up value. Martin (1996) finds that target firms with higher Tobin’s Q (which is positively correlated with step-up value) are more likely to be acquired with stock, because this results in risk-sharing between the acquirer and target. Dong et al. (2006) find a positive association between the target’s market to book ratio (also positively correlated with step-up value) and the use of stock-financing arguing that acquirers are more likely to use equity when target firms are overvalued. However, why this preference for equity financing would change coincident with the new accounting rules is not clear.  

19    

2, column 1 and 2 results are based on the sample of acquisitions with REL_DEALSIZE greater

than 5 and 25 percent, respectively. In both the columns, the coefficient on STEPUP is not

significant. This result suggests that the positive association between step-up value and stock-

for-stock financing in the pre-SFAS 141 period is driven primarily by the incentive to qualify for

pooling accounting and not by some other incentive to use equity financing for acquisitions of

firms with large step-up values. Furthermore, the coefficient on STEPUP*D_POST is not

significant in both the columns. This result indicates that the decrease in the association between

step-up value and stock-for-stock financed acquisitions after SFAS 141, observed in Table 2, is

not explained by a general decrease in the incentive to use stock for acquisitions of firms with

large step-up values, but is more likely due to the elimination of the pooling method for 100

percent stock-for-stock exchange transactions.

IV. PROBABILITY OF TAKEOVER

Research Design

We examine whether SFAS 141 and 142 decreases the takeover probability of firms with

larger predicted step-up values relative to firms with smaller predicted step-up values and

whether this effect is less pronounced for firms that have a greater component of predicted step-

up value as goodwill (hypothesis 2). From the SDC sample of completed acquisitions from 1983

to 2009 described above, we identify public firms that receive takeover bids. We use a matched

control sample, which consists of all firms in Compustat in the same 4-digit SIC code that have a

market value between 50 percent and 150 percent of the market value of the takeover firm at the

fiscal year end prior to the acquisition announcement. Firms that are acquired at any point are

excluded from the control sample.

20    

Our takeover probability model is based on the findings of prior studies (e.g., Dietrich

and Sorensen 1984; Palepu 1986; Ambrose and Megginson 1992; Cremers et al. 2009; Cai and

Tian 2009; Edmans et al. 2012). Specifically, we estimate the following logistic regression to test

our hypothesis:

TAKEOVERi,t+1 = β0 + β1D_POSTi,t + β2PRED_STEPUPi,t + β3PRED_STEPUPi,t*D_POSTi,t + β4D_GOODWILLi,t + β5D_GOODWILLi,t*PRED_STEPUPi,t + β6D_GOODWILLi,t*PRED_STEPUPi,t*D_POSTi,t + β7 Ln(MV)i,t + β8LEVERAGEi,t + β9ROAi,t + β10PPEi,t + β11Ln(CASH)i,t + β12SALES_GROWTHi,t + β13BLOCKHOLDERi,t + β14SIZE_ADJ_RETi,t + εi,t (2)

where TAKEOVERi,t+1 is an indicator variable which equals one if firm i receives a completed

takeover bid within one year of the end of fiscal year t, and equals zero otherwise. D_POSTi,t,

defined slightly differently than in equation (1) because this analysis is at the firm-year level,

equals one if fiscal year t ends after the implementation of SFAS 141 and 142, June 30, 2001,

and zero otherwise. The predicted step-up of firm i, PRED_STEPUPi,t, is calculated as the

difference between the market value of equity of firm i and the book value of common equity,

deflated by total assets at the end of fiscal year t. We expect a negative coefficient on

PRED_STEPUP consistent with acquirers avoiding takeover targets with high step-up values,

because of the adverse financial reporting effect of purchase accounting or the cost of qualifying

for the pooling method. D_GOODWILLi,t is an indicator variable equal to one if firm i is in an

industry characterized by high goodwill levels. We expect that firms in high goodwill industries

are more likely to have their step-up value be primarily composed of goodwill. To define high

goodwill industries we first rank each four-digit SIC industry by the industry-level percentage of

firm-year observations where the ratio of goodwill to total assets is greater than or equal to 10

percent during the pre-SFAS 141/142 period (1983-2000). We use all firm-year observations in

Compustat with non-negative values of goodwill for this calculation. We then define

21    

D_GOODWILLi,t equal to one if the industry is ranked in the top tercile, and equal to zero

otherwise.19

We use the interaction of PRED_STEPUP and D_POST as our main test variable. A

negative coefficient on PRED_STEPUP*D_POST indicates that for firms not in high goodwill

industries the elimination of the pooling method is associated with a greater decrease in takeover

probability for firms with larger step-up values than firms with smaller step-up values. We

interact D_GOODWILL with PRED_STEPUP*D_POST to test whether the more negative

association between step-up values and takeover probability due to the new acquisition

accounting rules will be less pronounced for firms with step-up values comprised primarily of

goodwill. We expect a positive coefficient, indicating that the new accounting rules led to a more

positive effect on the association between takeover likelihood and step-up value for firms in high

goodwill industries than for other firms.

Based on prior literature, we use several control variables. Ln(MV)i,t is the natural

logarithm of inflation-adjusted market value of equity of firm i at the end of fiscal year t.

LEVERAGEi,t is the ratio of long-term debt to total assets of firm i at the end of fiscal year t and

ROAi,t is net income before extraordinary items for fiscal year t divided by total assets at the

beginning of fiscal year t. PPEi,t is property, plant, and equipment of firm i scaled by total assets

at the end of fiscal year t. Ln(CASH)i,t is the natural logarithm of inflation-adjusted cash and

short term investments of firm i at the end of fiscal year t and SALES_GROWTHi,t is the

percentage change in sales from fiscal year t-1 to t. BLOCKHOLDERi,t is an indicator variable

                                                                                                                         19 Industries in the top tercile have at least 28.6% of firm observations with a goodwill to total assets ratio of 10% or greater. As a robustness test we also defined high goodwill industries based on whether firms’ goodwill to total assets ratio is 5% or greater and our conclusions remain the same. For this robustness test, the top tercile includes industries having at least 42.6% of firm observations with a goodwill to total assets ratio of 5% or greater. As a further robustness test we also defined high goodwill industries as those in the top tercile when ranking industries by their mean goodwill to total assets ratio and our conclusions remain the same.

22    

equal to one if firm i has at least one institutional shareholder with a minimum of 5 percent of

total common shares outstanding (Thomson-Reuters Institutional Holdings Database), and zero

otherwise. SIZE_ADJ_RETi,t is the difference between the firms’ buy and hold return over fiscal

year t-1 minus the buy and hold return for the CRSP value-weighted portfolio of

NYSE/AMEX/NASDAQ firms in the same size-decile. Continuous variables are winsorized at

the 1st and 99th percentile, except for variables bounded between zero and one. We also include

year and industry (2-digit SIC level) fixed effects.

Results

Panel A of Table 4 presents descriptive statistics for the variables used in the takeover

probability model. The sample includes 2,308 takeover firms and 8,427 control firms. Panel B

presents the regression results from estimating equation (2). We first present the results in

column 1 without allowing for differing effects based on whether a firm is in a high goodwill

industry by excluding D_GOODWILL and its associated interaction terms. The coefficient on

PRED_STEPUP is significantly negative, consistent with acquirers avoiding takeover targets

with high step-up values because of the adverse financial reporting effect of purchase accounting

or because of the cost of qualifying for the pooling method. The coefficient on

PRED_STEPUP*D_POST is significantly negative, indicating that the association between

takeover probability and step-up value of the target becomes significantly more negative after the

new accounting rules. This result is likely driven by the elimination of the pooling method,

which has taken away the option of using book values to report target firm’s assets on the

combined firm’s financial reports.20

                                                                                                                         20 PRED_STEPUP, market to book ratio, and Tobin’s Q are highly correlated because the components for all these variables are very similar. Prior studies have examined the association between the likelihood of takeover and both

23    

When we estimate the full model in column 2 we find similar results for the coefficients

on PRED_STEPUP and PRED_STEPUP*D_POST. These results indicate that for firms not in

high goodwill industries there is a significantly negative association between step-up value and

takeover probability before the elimination of pooling and this association became more negative

after its elimination. The coefficient on D_GOODWILL*PRED_STEPUP*D_POST is

significantly positive, as expected. This result suggests that the increase in the negative

association between takeover probability and step-up value due to the elimination of pooling is

attenuated when the step-up value is primarily comprised of goodwill. 21 This effect is

presumably due to the elimination of goodwill amortization.

The effect of the new accounting rules on takeover probability is also economically

significant. Focusing on the full model in column 2, before the new rules, the interquartile

change in PRED_STEPUP is associated with a 2.4 percent lower takeover probability. After the

new rules, the interquartile change in PRED_STEPUP is associated with an additional 3.5

percent lower takeover probability for firms not in high goodwill industries, which represents a

16 percent decrease relative to the unconditional takeover probability of 21.5% (= 2,308 /

10,735) in our sample of takeover and control firms. For firms in high goodwill industries the

interquartile change in PRED_STEPUP after the new rules is associated with an incremental 6.3

                                                                                                                                                                                                                                                                                                                                                                                                       market to book ratio and Tobin’s Q. Palepu (1986) argues that a negative association between the market to book ratio and takeover is consistent with acquirers perceiving high market to book ratio target firms being overvalued targets. However, he does not find a significant association between the market to book ratio and takeover. Using a larger and more current sample, Cai and Tian (2009) find a negative association between Tobin’s Q and takeover, but do not provide any explanation for this result. Thus, while there are other factors potentially affecting the association between step-up values and takeover probability (other than the adverse effect of high step-up value of the targets on the combined firm’s net income), they would need to explain a significant change in this association coinciding with the implementation of SFAS 141 and 142. 21 The results are consistent when D_POST is interacted with each of the independent variables in equation (2). There is no ex ante reason for including these additional interaction variables besides providing further assurances that the effect of other, coincident events on other variables in the equation is not confounding the results. In this specification, the coefficient on PRED_STEPUP*D_POST is also negative and significant, -0.136 (p-value = 0.012), and the coefficient on D_GOODWILL*PRED_STEPUP*D_POST is also positive and significant, 0.300 (p-value = 0.008).

24    

percent higher takeover probability when compared to firms not in high goodwill industries. The

combined coefficient on PRED_STEPUP*D_POST +

D_GOODWILL*PRED_STEPUP*D_POST, 0.135, is not significant (p-value = 0.214) which

suggests the elimination of goodwill amortization attenuated the decrease in takeover probability

due to elimination of the pooling method but did not necessarily result in a net increase in

takeover probability for firms in high goodwill industries.

Focusing on the control variables, we observe that for coefficients that are significant, the

signs are in general consistent with the prior evidence in the literature. The positive coefficient

on leverage is consistent with the results in Cremers et al. (2009) and Cai and Tian (2009) and

suggests that distressed firms that have limited resource availability due to excessive leverage are

more likely to be takeover targets (Palepu 1986). The positive coefficient on blockholders is also

consistent with the results in Cremers et al. (2009) and Cai and Tian (2009) and suggests that the

greater influence of blockholders than non-blockholders over managers and corporate

governance increases the likelihood of acceptance of takeover bids (Shleifer and Vishny 1986;

Cremers et al. 2009). Fixed assets are significantly negatively associated with takeover

probability. This result is consistent with the notion that it is costlier to combine firms with fixed

assets than with intangible assets. Prior evidence on the association between fixed assets and

takeover probability is mixed (e.g., Ambrose and Megginson 1992; Cai and Tian 2009). Cash

holdings are significantly negatively associated with takeover probability consistent with the

finding of Pinkowitz (2000). While Jensen (1986) argues that firms that do not pay out free cash

flow are more likely to be takeover targets, Pinkowitz (2000) argues that high cash holdings

entrench managers by providing them protection from unwanted takeover attempts.

25    

V. Sensitivity Analyses

Sensitivity of Results to the Sample Period 1994-2001

A potential concern related to our acquisition financing and takeover probability results is

that they could be driven by the boom period of the 1990s, when equity values experienced large

increases and there was a merger wave. Moreover, the end of this period coincides with the year

of the acquisition accounting rule changes. To rule out this concern, we repeat our analysis after

excluding observations with fiscal years ending in 1994-2001.

Panel A of Table 5 presents results for the acquisition financing model, stock-for-stock

versus partial stock, using the restricted sample period. Consistent with our earlier results, the

coefficient on STEPUP is significantly positive and the coefficient on our main variable of

interest, STEPUP*D_POST, is significantly negative. The marginal effects of these two variables

are slightly greater than in the full sample. Panel B of Table 5 reports the results for the takeover

probability model using the restricted sample period. Consistent with our earlier results, the

coefficient on PRED_STEPUP is significantly negative and the coefficient on our main variable

of interest, PRED_STEPUP*D_POST, is significantly negative. The coefficient on

D_GOODWILL*PRED_STEPUP*D_POST is not significantly positive using a two-tailed p-

value, however, given our signed prediction for this variable the use of a one-tailed p-value is

appropriate which would indicate the coefficient is marginally significant at the 10% level. The

marginal effects for these variables are also of a similar size to the earlier results. Overall, Table

5 results suggest that our full sample results are not driven by the boom period of the late 1990s.

26    

Sensitivity of Results to High-Technology Industries

High-technology industries were the main drivers of the boom period of the 1990s and

subsequent drop in equity values. Therefore, as an additional robustness test to rule out that our

results are not driven by macro-economic factors affecting primarily high-technology firms we

repeat our analysis after excluding observations with firms in high-technology industries.

Following Field and Hanka (2001), we classify high-technology firms as those firms with

primary three-digit SIC codes in computer and office equipment (357), electronic components

and accessories (367), miscellaneous electrical machinery, equipment, and supplies (369),

laboratory apparatus and analytical, optical, measuring, and controlling instruments (382),

surgical, medical, and dental instruments and supplies (384), and computer programming, data

processing, and other computer-related services (737).

Panel A of Table 6 presents results for the acquisition financing model, stock-for-stock

versus partial stock, using the restricted sample. Consistent with our earlier results, the

coefficient on STEPUP is significantly positive and the coefficient on our main variable of

interest, STEPUP*D_POST, is significantly negative. The marginal effects of these two variables

are also slightly higher than in the full sample. Panel B of Table 6 reports the results for the

takeover probability model using the restricted sample. Once again consistent with our earlier

results, the coefficient on PRED_STEPUP*D_POST is significantly negative and the coefficient

on D_GOODWILL*PRED_STEPUP*D_POST is significantly positive. The marginal effects for

these variables are also of a similar size to the earlier results. Overall, Table 6 results suggest that

our full sample results are not driven by high-technology firms.

27    

VI. CONCLUSION

We investigate the effects of the accounting standard changes that eliminate the pooling

method (SFAS 141) and goodwill amortization (SFAS 142) on the form of financing used for

corporate takeovers and on a firm’s takeover probability. The primary requirement to qualify for

the pooling method is structuring the transaction as a stock-for-stock exchange. We find that

before the new accounting rules, target firms’ step-up value is positively associated with the

probability of using stock-for-stock as against partial stock financing, suggesting that acquirers

have greater incentive to report the acquisitions using the pooling method when the target’s step-

up value is higher. After the new rules, this association decreases significantly. We also examine

whether SFAS 141 and 142 affected a firm’s takeover probability. We find that firms with larger

step-up values experienced a significantly greater decrease in takeover probability due to the new

accounting rules than did firms with smaller step-up values. This result is consistent with the

notion that the elimination of the pooling method has reduced the incentive for making

acquisitions that would have used the pooling method before the new accounting rules. We also

show that the adverse effect of the new rules on the probability of a takeover is attenuated when

the step-up value is composed primarily of goodwill, suggesting that elimination of goodwill

amortization has a favorable effect on a firm’s takeover probability. Finally, we document that

the effects of the new acquisition accounting rules on the form of acquisition financing and on

takeover probability are not just statistically significant, but are also economically significant. In

sum, our study makes use of a natural experiment, mandatory changes in acquisition accounting

rules, to provide a novel finding that accounting methods are important determinants of the form

of acquisition financing as well as of takeover probability.

28    

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Table 1 Acquisition Financing: Descriptive Statistics

Panel A: Frequency of Different Types of Acquisition Financing

Year Number of

Acquisitions Stock-for-

Stock

Partial Stock (Mean Stock Component) 100% Cash

1983 10 5 5 ( - ) 0 1984 8 2 6 ( - ) 0 1985 20 3 1 (49%) 16 1986 35 8 2 (75%) 25 1987 18 6 2 (78%) 10 1988 20 2 3 (35%) 15 1989 19 9 1 (15%) 9 1990 17 10 2 (76%) 5 1991 17 10 4 (43%) 3 1992 11 3 2 (80%) 6 1993 10 3 3 (42%) 4 1994 32 23 3 (57%) 6 1995 51 30 7 (43%) 14 1996 53 34 9 (60%) 10 1997 84 37 25 (60%) 22 1998 81 43 22 (68%) 16 1999 80 26 32 (59%) 22 2000 65 32 18 (56%) 15 2001 55 22 19 (55%) 14 2002 37 12 13 (56%) 12 2003 47 20 14 (51%) 13 2004 44 14 12 (60%) 18 2005 43 10 20 (52%) 13 2006 35 11 5 (47%) 19 2007 45 5 19 (53%) 21 2008 24 4 6 (57%) 14 2009 33 11 14 (46%) 8

Total 994 395 269(56%) 330

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Panel B: Descriptive Statistics of the Acquisition Financing Model Variables

N Mean Median Std Dev Q1 Q3 D_POST 994 0.336 0.000 0.473 0.000 1.000 STEPUP 994 0.300 0.170 0.402 0.072 0.383 ACQUIRER_BTM 994 0.483 0.420 0.350 0.258 0.616 ACQUIRER_RET 994 0.192 0.049 0.718 -0.187 0.355 ACQUIRER_INST 994 0.593 0.618 0.258 0.418 0.791 Ln(ACQ_CASH) 994 3.896 4.021 1.942 2.676 5.126 ACQ_LEVERAGE 994 0.191 0.164 0.164 0.042 0.296 ACQUIRER_MV 994 6.814 6.799 1.728 5.697 7.911 TARGET_MV 994 5.102 4.956 1.713 3.942 6.208 REL_DEALSIZE 994 0.497 0.294 0.575 0.122 0.646 TARGET_ROA 994 -0.003 0.009 0.053 -0.006 0.021 ΔS&P500 994 0.112 0.131 0.178 0.034 0.235 TARGET_INST 994 0.479 0.471 0.263 0.269 0.686

Notes to Table 1:

This table presents descriptive statistics for the variables used to test the effect of the new acquisition accounting rules on the form of acquisition financing. Panel A presents by year the frequency of acquisitions and the payment form. SDC does not provide the percentage of stock used for the observations in years 1983 and 1984, but indicates that common stock is a component of the payment. Panel B includes the descriptive statistics of the variables used in the acquisition financing model (equation 1 of the text). D_POSTi,t is an indicator variable that is equal to one if the acquisition announcement occurs after June 30, 2001, and zero otherwise. STEPUPi,t is the step-up in target book value calculated as the difference between the transaction value and the book value of the target’s common equity deflated by the combined total assets of the acquirer and target. ACQUIRER_BTMi,t is the acquirer’s ratio of book value of equity to market value of equity at the end of the fiscal quarter prior to the acquisition announcement. ACQUIRER_RETi,t is the size-adjusted abnormal return of the acquiring firm over the 12-month period ending at the end of the fiscal quarter prior to the acquisition announcement. ACQUIRER_INSTi,t is the percentage of acquirers’ shares owned by institutions (source Thomson Reuters Institutional Holdings) as of the calendar quarter before the acquisition announcement. Ln(ACQ_CASH)i,t is the natural logarithm of the acquirers’ cash and short term investments at the end of the last fiscal quarter prior to the acquisition announcement adjusted for inflation. ACQ_LEVERAGEi,t is the acquirer’s ratio of long-term debt to total assets at the end of the last fiscal quarter prior to the acquisition announcement. ACQUIRER_MVi,t is the market value of the acquirer at the end of the last fiscal quarter prior to the acquisition announcement adjusted for inflation. TARGET_MVi,t is the market value of the target firm at the end of the last fiscal quarter prior to the acquisition announcement adjusted for inflation. REL_DEALSIZEi,t is the transaction value of the acquisition divided by the market value of the acquiring firm at the end of the fiscal quarter prior to the acquisition announcement. TARGET_ROAi,t is the target firm’s net income divided by total assets for the last fiscal quarter prior to the acquisition announcement. ΔS&P500i,t is the change in the S&P 500 index over the 12 months preceding the acquisition announcement. TARGET_INSTi,t is the percentage of target firms’ shares owned by institutions (source Thomson Reuters Institutional Holdings) as of the calendar quarter before the acquisition announcement.

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Table 2 Probability of Stock-for-Stock versus Partial Stock Financing of Acquisitions:

Logistic Regressions

100% STOCKi,t = β0 + β1D_POSTi,t + β2STEPUPi,t + β3STEPUPi,t*D_POSTi,t + β4ACQUIRER_BTMi,t + β5ACQUIRER_RETi,t + β6ACQUIRER_INSTi,t + β7Ln(ACQ_CASH)i,t + β8ACQ_LEVERAGEi,t + β9ACQUIRER_MVi,t + β10TARGET_MVi,t + β11REL_DEALSIZEi,t + β12TARGET_ROAi,t + β13ΔS&P500i,t + β14TARGET_INSTi,t + εi,t

REL_DEALSIZE > 5% REL_DEALSIZE > 25%

Variables

Coefficients (p-value) Marginal Effects

Coefficients (p-value)

Marginal Effects

Intercept 3.675 6.349 (0.005) *** (

34    

Notes to Table 2:

This table tests the effect of the new acquisition accounting rules on the probability of a 100% stock-for-stock financed acquisition versus a partially stock financed acquisition. 100% STOCKi,t is an indicator variable equal to one if an acquisition is 100% stock-for-stock financed and zero if it is a partial stock financed acquisition. D_POSTi,t is an indicator variable that is equal to one if the acquisition announcement occurs after June 30, 2001, and zero otherwise. STEPUPi,t is the step-up in target book value calculated as the difference between the transaction value and the book value of the target’s common equity deflated by the combined total assets of the acquirer and target. ACQUIRER_BTMi,t is the acquirer’s ratio of book value of equity to market value of equity at the end of the fiscal quarter prior to the acquisition announcement. ACQUIRER_RETi,t is the size-adjusted abnormal return of the acquiring firm over the 12-month period ending at the end of the fiscal quarter prior to the acquisition announcement. ACQUIRER_INSTi,t is the percentage of acquirers’ shares owned by institutions (source Thomson Reuters Institutional Holdings) as of the calendar quarter before the acquisition announcement. Ln(ACQ_CASH)i,t is the natural logarithm of the acquirers’ cash and short term investments at the end of the last fiscal quarter prior to the acquisition announcement adjusted for inflation. ACQ_LEVERAGEi,t is the acquirer’s ratio of long-term debt to total assets at the end of the last fiscal quarter prior to the acquisition announcement. ACQUIRER_MVi,t is the market value of the acquirer at the end of the last fiscal quarter prior to the acquisition announcement adjusted for inflation. TARGET_MVi,t is the market value of the target firm at the end of the last fiscal quarter prior to the acquisition announcement adjusted for inflation. REL_DEALSIZEi,t is the transaction value of the acquisition divided by the market value of the acquiring firm at the end of the fiscal quarter prior to the acquisition announcement. TARGET_ROAi,t is the target firm’s net income divided by total assets for the last fiscal quarter prior to the acquisition announcement. ΔS&P500i,t is the change in the S&P 500 index over the 12 months preceding the acquisition announcement. TARGET_INSTi,t is the percentage of target firms’ shares owned by institutions (source Thomson Reuters Institutional Holdings) as of the calendar quarter before the acquisition announcement. We also include year and industry fixed effects. The sample for the regression in column one (664 observations) consists of acquisitions that were 100% stock-for-stock financed (395) and partial stock financed (269). The sample for the regression in column 2 consists of only those observations with REL_DEALSIZEi,t greater than 25%. Standard errors used to calculate p-values, presented in parentheses, are White adjusted and clustered by firm. The marginal effects column presents the change in the probability of a stock-for-stock financed acquisition for an interquartile change in the variable, or an indicator variable equal to 1, with all other independent variables taking the mean value. *, **, and *** denote two-tailed statistical significance at 10%, 5%, and 1%, respectively.

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Table 3 Probability of a Partial Stock versus All Cash Financing of Acquisitions: Logistic Regressions

PARTIAL STOCKi,t = β0 + β1D_POSTi,t + β2STEPUPi,t + β3STEPUPi,t*D_POSTi,t

+β4ACQUIRER_BTMi,t + β5ACQUIRER_RETi,t + β6ACQUIRER_INSTi,t + β7Ln(ACQ_CASH)i,t + β8ACQ_LEVERAGEi,t + β9ACQUIRER_MVi,t + β10TARGET_MVi,t + β11REL_DEALSIZEi,t + β12TARGET_ROAi,t + β13ΔS&P500i,t + β14TARGET_INSTi,t + εi,t

REL_DEALSIZE > 5% REL_DEALSIZE > 25%

Variables Coefficients

(p-value) Marginal Effects

Coefficients (p-value)

Marginal Effects

Intercept 1.181 -4.291 (0.404) (0.007) *** D_POST -1.433 -35.1% 0.814 18.7% (0.069) * (0.467) STEPUP 1.685 12.8% 1.373 9.8% (0.168) (0.430) STEPUP*D_POST 1.55