The use of escrow contracts in acquisition agreements*

Sanjai Bhagat

Leeds School of Business University of Colorado

Boulder, CO 80309-0419 303.492.7821

sanjai.bhagat@colorado.edu

Sandy Klasa Eller College of Management

University of Arizona Tucson, AZ 85721

520.621.8761 sklasa@eller.arizona.edu

Lubomir P. Litov

Eller College of Management University of Arizona

Tucson, AZ 85721 520.621.3794

litov@email.arizona.edu

November, 2012

Abstract:

Many private firm and subsidiary acquisition deals make use of escrow contracts, whereby a fraction of the total sale proceeds are placed in an escrow account. These contracts give the bidder the opportunity to lay claim on these funds subsequent to the acquisition if the seller fails to meet specific terms of the acquisition agreement or it is found that negative information about the target was hidden from the bidder. We hypothesize that escrow contacts are an efficient contracting mechanism that helps bidders and targets to manage acquisition-related transaction risk and mitigate information asymmetry problems. Supporting our hypothesis, we show using hand-collected data that the likelihood an escrow contract is used in a private firm or subsidiary acquisition is higher when bidder transaction risk or information asymmetry about the value of the target is larger. Further, we document that escrow contracts enable the seller to obtain a higher sale price and that the use of these contracts positively impacts the extent to which a private firm or subsidiary acquisition results in value creation for the bidder.

* For helpful comments and suggestions, we thank seminar participants at the brown bag series at the University of Arizona, Washington University in St. Louis, and Arizona State University. We also thank Thomas Bates, Andra Ghent, Laura Lindsey, Claudia Custodio, Sreedar Bharath, Eric Kelley, Rick Sias, Daniel Levin, and Kevin Ryan. We thank J.P. Morgan Escrow Services for providing access to their proprietary data on the use of escrow contract in private target acquisitions. We recognize research assistance from Jordan Neyland, D.J. Fairhurst, Matthew Serfling and Jason Lunn.

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1. Introduction

Most acquisitions made by publicly traded firms consist of acquisitions of private firms or

subsidiaries of other firms (e.g., Fuller, Netter, and Stegemoller (2002) and Netter, Stegemoller, and

Wintoki (2011)). However, there is only limited empirical evidence on private firm and subsidiary

acquisitions in prior work, which restricts our understanding of these types of acquisitions. In this

paper we study escrow contracts, which are employed in a large number of private firm and

subsidiary acquisitions. When these contracts are used the bidder firm sets aside a percentage of the

total purchase price in an escrow account, which is held for a negotiated period of time after the

completion of the acquisition. Bidders can lay claim to the funds in the escrow account in the event

the target fails to meet specific terms of the acquisition agreement or it is found that negative

information about the target was hidden from the bidder prior to the sale. We hypothesize that the

use of escrow contracts in private firm and subsidiary acquisitions is an efficient contracting

mechanism that facilitates the completion of these acquisitions by allowing buyers and sellers to

overcome information asymmetry problems and manage acquisition-related transaction risk.

For a sample of 569 private firm acquisitions and 374 subsidiary acquisitions made by

publicly traded firms over the 1994-2009 period we hand-collect from bidder firms’ DEF 14M-14A

and 8-Ks filings data on whether an escrow contract is used in the context of the acquisition, and if

so, what fraction of the total purchase price is placed in the escrow account, and how long are the

funds kept in the account. We find that escrow contracts are employed in 52.1% of the acquisitions

we study and that for the deals with an escrow contract, on average, 12.2% of the sale proceeds are

placed in an escrow account and the funds are held in the escrow account for nearly 17.4 months.

We first investigate whether the likelihood that an escrow contract is employed in the

context of an acquisition is greater in instances in which it should be more important for bidders to

manage their transaction risk. We compare the use of escrow contracts in subsidiary versus private

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firm acquisitions. In the case of subsidiary acquisitions, a bidder would have legal recourse post deal

closure against both the parent firm that sold the subsidiary and the principal shareholders of the

selling firm, while for private firm acquisitions the bidder would only have recourse against the

principal shareholders of the target. Consequently, we expect escrow contracts to be used more

often in the case of private firm acquisitions than subsidiary acquisitions. Our findings are consistent

with this proposition. Specifically, we document that escrow contracts are used in 65.2% of private

firm acquisitions, but that these contracts are used in only 32.1% of subsidiary acquisitions. Further,

in multivariate tests we show that whether an acquisition is a private firm acquisition positively

impacts the likelihood that an escrow contract is used in the context of a given acquisition.

We turn next to the relative size of the target to the bidder as a determinant of the likelihood

of the use of an escrow contract. When the relative size of the target to the bidder is greater it

should be more important for the bidder to manage acquisition-related transaction risk. Thus, in

these instances buyers and sellers should be more likely to rely on escrow contracts to reduce this

risk for the buyer. Supporting this prediction, we find that the relative size of the target to the bidder

has a positive effect on the likelihood of using an escrow contract.

Because in cases when there is greater information asymmetry between the bidder and target

about target firm value it will be riskier for a bidder to make an acquisition, in these cases it should

be more beneficial for a bidder to have the target agree to an escrow contract. We consider five

cases in which information asymmetry about a target firm’s value is likely to be greater. First, we

assume there is more information asymmetry about the value of a target if it operates in an industry

in which earnings volatility is higher. Second, we expect that if analyst coverage is lower in the

target’s industry then there is more information asymmetry about its value. Third, we consider if the

target firm operates in a different industry than does the bidder, assuming that if so, then

information asymmetry problems will be larger. Fourth, we look to a target’s total accruals, as

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measured by the difference between its earnings and its free cash flows and follow prior work (e.g.,

Dechow and Dichev (2002)) that assumes that when total accruals for a firm are greater it can be

more difficult for investors to infer a firm’s financial performance and its value from its earnings.2

Finally, we expect that there is greater information asymmetry about the value of the target when it

is financially distressed. Here, we consider a target’s interest coverage ratio to proxy for the

likelihood it is financially distressed. Consistent with expectations, our results show that the

likelihood an escrow contract is used in a private firm or subsidiary acquisition is positively

associated with earnings volatility in the target’s industry, whether analyst coverage is low in this

industry, whether the target operates in a different industry that does the bidder, the target’s total

accruals, and if a target’s interest coverage ratio is low.

If a target firm has a dominant shareholder an escrow contract can be particularly useful to

manage this shareholder’s acquisition-related transaction risk because if there is an escrow contract

in place all target shareholders would bear pro rata costs of bidder recourse actions subsequent to an

acquisition (i.e., be jointly and severally liable for any breaches of the representations and warranties

section of the acquisition agreement). In contrast, if such a contract is not in place bidder recourse

actions subsequent to an acquisition could result in the target firm’s dominant shareholder being

held liable and sued by the bidder.3 Supporting the proposition that an important motif for escrow

contracts is that they help reduce the transaction risk of the major shareholder of a target firm, we

find that the extent to which a target firm is controlled by a dominant shareholder is positively

associated with the likelihood an escrow contract is used.

2 Specifically, prior work argues that if a firm has large accruals and it is difficult to map its accruals into its future cash flows then it can be more difficult for investors to infer the firm’s financial performance and value from its earnings. In the case of private firm or subsidiary targets, it should be difficult for the bidder to map accruals into future cash flows given that this would require the bidder to study the financial statements of the target over a significant period. 3 The bidder could herself seek recourse from each of the remaining shareholders by starting individual lawsuits with each such shareholder. It is important to remark that such recourse’ cost is hence increasing in the number of remaining shareholders.

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To examine whether escrow contracts in acquisitions are consistent with efficient

contracting, we also consider how several other forms of contingent payment mechanisms are

associated with the use of an escrow contract. We find that in 86% of the deals we study that the

bidder firm agrees to a cap on the amount it could sue the target subsequent to the acquisition. If

the bidder agrees to such a cap this should make it easier to persuade the target to agree to an

escrow contract, which suggests a complement relation between the existence of a cap and the use

of an escrow contract. Supporting this notion, we show that if the bidder agrees to put a cap on how

much future compensation it could seek from the target this has a positive effect on the likelihood

an escrow contract is used in conjunction with the acquisition. Also, given that prior related work

has studied earnout contracts, which provide for future payments to target firm managers contingent

on some observable measure of performance (e.g., Kohers and Ang (2000) and Cain, Denis, and

Denis (2011)), we examine the relation between the use of earnout and escrow contracts in private

firm and subsidiary acquisitions. We find that 12.4% of the deals we study include earnout contracts.

However, we document that the presence of an earnout contract is not associated with the use of

escrow contracts in private firm and subsidiary acquisitions. This is potentially not surprising given

that earnout contracts and escrow contracts serve different purposes. Whereas earnout contracts are

meant to increase the bidder’s upside return from an acquisition, escrow contracts protect bidders

from downside risk.

We next examine if the use of escrow contracts in private firm and subsidiary acquisitions

creates value for the buyer and seller parties. The use of these contracts could reduce bidder costs in

three ways. First, because the use of these agreements should reduce bidder losses in the event that

the seller fails to meet specific terms of the acquisition agreement or it hides negative information

about the target, escrow contracts should truncate potential post-deal-closure negative outcomes for

bidders resulting from private firm and subsidiary acquisitions. Second, the use of an escrow

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contract can potentially reduce the need for a bidder to incur significant information gathering costs

about a target firm so that a precise estimate for the value of the target can be determined. Finally,

employing an escrow contract can allow a bidder to avoid financial and time costs that would be

incurred if the bidder had to sue target firm parties subsequent to an acquisition in order to obtain

recourse.

We expect that the reduction in bidder costs resulting from the use of an escrow contract

should lead to a higher price paid for the target firm. Given the evidence in Officer (2007) that in

private firm and subsidiary acquisitions the target firm is typically sold at a discount relative to

comparable public targets, we examine if the use of an escrow contract reduces this acquisition

discount. After controlling for the endogeneity of having an escrow contract in place and potential

costs to the target if the bidder ends up receiving some of the funds in the escrow account, we show

that the use of these contracts reduces the discount in the final price paid for a private or subsidiary

target. Specifically, we find that the use of these contracts reduces the discount in final price by

approximately 6.3% (see Figure 1). We examine if this effect is more pronounced in instances when

reductions in bidder costs stemming from the use of an escrow contract would be greater, when the

relative size of the target to the bidder is larger and when the target operates in an industry in which

there is likely greater information asymmetry about firms’ future prospects, as measured by earnings

volatility in an industry and whether analyst coverage for the firms in the industry is low. Consistent

with the use of escrow accounts creating more value for targets in these instances, we find that the

extent to which escrow contracts reduce the discount in the final price paid for a private or

subsidiary target is greater when the relative size of the target to the bidder is larger, earnings

volatility in the target’s industry is higher, or analyst coverage in the target’s industry is lower.

Lastly, we examine whether reductions in bidder costs in private firm and subsidiary

acquisitions resulting from the use of escrow contacts lead to more positive market reactions to the

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announcement of an acquisition deal. Suggesting this is the case, we find that bidder firm abnormal

stock returns at the time of this announcement are positively associated with whether an escrow

contract is used in conjunction with the acquisition, and also show this result is robust to controlling

for the endogeneity of having an escrow contract in place. Further, we find that this effect is more

pronounced when the reduction in bidder costs from using an escrow contract would be greater, as

proxied for by a higher value for the relative size of the target to the bidder, greater earnings

volatility in the target’s industry, or lower analyst coverage in the target’s industry

Overall, our paper contributes to the literature on mergers and acquisitions in several ways.

First, we document widespread use of escrow contracts in private firm and subsidiary acquisitions

and the results of our tests on the determinants and effects of these contracts provide insights on

how the participants in these transactions resolve contracting problems. This is important because

although much is known about acquisitions of public targets, our understanding of private firm and

subsidiary acquisitions is limited. Second, our findings contribute to the literature on the method of

payment used in mergers and acquisitions. Prior work in this area shows that the method of

payment is determined by factors such as firm financing policies (e.g., Bharadwaj and Shivdasani

(2003) and Harford, Klasa, and Walcott (2009)), taxes (e.g., Kaplan (1989), Brown and Ryngaert

(1991), and Erickson (1998), and a firm’s ownership structure (e.g., Amihud, Lev, and Travlos

(1990), Martin (1996), and Ghosh and Ruland (1998)). Our findings indicate that the method of

payment used by a bidder can also be a function of bidders and targets trying to manage acquisition-

related transaction risk. Finally, our paper contributes to the literature on how financial contracting

can solve problems associated with information asymmetry and moral hazard. Related work in this

area examines venture capital financing agreements (e.g., Kaplan and Stromberg (2003)). Our

findings provide insights on how financial contracting can also help to overcome valuation

uncertainty and moral hazard in the context of acquisitions.

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The remainder of the paper is organized as follows. Section 2 discusses our sample and

methodology, and provides the results of univariate tests. Section 3 presents our main empirical

results. Finally, Section 4 presents our conclusions.

2. Sample and methodology

We compile data for this paper from several sources. Our initial sample of acquisitions is

identified from the Securities Data Corporation (SDC) U.S. Mergers and Acquisitions database for

acquisitions announced and completed over the 1994-2009 period and it includes transactions that

meet the following criteria: the target is unlisted (either stand-alone or subsidiary) company that is

included on the Pratt’s Statistics (discussed below) and the acquirer is a public company that is

included on the Compustat and CRSP databases. We further require that the size of the deal be at

least 25 million dollar, that there is less than 50% pre-acquisition ownership of the target by bidder,

and that the bidder acquires full ownership of the target post-acquisition. We also require of all

transactions to have available data on consideration structure (stock, cash, hybrid payment structure)

Having imposed these requirements, we obtain a total of 943 transactions.

We use the Pratt’s Statistics database, maintained and distributed by the Business Valuation

Resources LLC, as our main source of detailed accounting data about the targets in our sample. The

data on private target acquisitions by public firms is compiled in this database through DEF 14,

DEF14A and 8-K searches. As this is a new database, not frequently used in prior academic

research, we randomly check its quality by comparing data on target accounting characteristics from

Pratt’s Statistics to data which is hand-collected from disclosures available from the SEC on

EDGAR for 100 observations. We find more than 95% matching data for these test observations.

We hand-collect data on escrow contracts that are used in some of the transactions we study

through a review of the relevant merger or acquisition agreements in bidders’ DEF14, DEF 14A or

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8-Ks. Specifically, we collect information on the dollar size of the escrow, its maturity, and structure

of the deposit (e.g., stock, cash or a mixture of both). We also hand-collect data on the use of caps

that limit the amount that a bidder could sue the target for and on the ownership structure of the

private target from these sources.

Tables 2 and 3 provide descriptive statistics for our sample and compares deals with and

without escrow contracts. Panel A of Table 2 shows that 52.1% of the deals we study include an

escrow contract. For deals with an escrow contract, on average, 12.2% of the deal proceeds are

placed in an escrow account, which represents about $11.7 million dollars. The average length of

time that the funds are kept in the escrow account is 17.4 months. Panel A also shows that, on

average, the number of days between the announcement of a deal and the completion date is 57.5

days for the entire sample, but only 35 days for the subsample of deals using an escrow contravct.

Panel B of Table 2 reports additional deal characteristics for acquisitions in our sample and

also reports evidence on how these characteristics differ between deals with and without escrow

contracts. This panel shows that 12.2% of the deals in our sample also use an earnout contract.

However, there is no significant difference between the use of an earnout contract between deals

with or without an escrow contract. This finding potentially reflects the fact that earnout contracts

and escrow contracts serve different purposes. Whereas earnout contracts are meant to increase the

bidder’s upside return from an acquisition, escrow contracts protect bidders from downside risk.

Panel B also shows that in 73.7% of the deals we study the bidder agrees to a cap on the dollar

amount that the sellers of the target could be sued for subsequent to the acquisition. Further, this

panel shows that the fraction of deals that use caps is significantly greater among the deals using an

escrow contract (85.3% versus 61.1%). This result is consistent with the notion that if a bidder

agrees to a cap this should make it easier to persuade the target to agree to an escrow contract.

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Panel B also documents that 73.7% of the deals are stock purchase transactions in which

the bidder becomes responsible for the target’s liabilities, and that within the group of deals with

escrow contracts there is a significantly higher fraction of deals that are stock purchase transactions

(80.0% versus 66.8%). This result supports the argument that in stock purchase deals because a

bidder faces additional risk compared to asset purchase transaction that bidders will be more likely

to request that an escrow contract be used in conjunction with the acquisition. As well, Panel B

shows that 60.3% of the deals we study are for stand-alone targets rather than for subsidiaries and

that this fraction is notably higher in deals that make use of escrow contracts (75.6% versus 43.8%).

This result likely reflects the fact escrow contracts are more useful for bidders in the case of private

firm acquisitions than subsidiary acquisitions because in the case of a subsidiary acquisition, a bidder

would have legal recourse post deal closure against both the parent firm that sold the subsidiary and

the principal shareholders of the selling firm, while for private firm acquisitions the bidder would

only have recourse against the principal shareholders of the target.

Finally, Panel B of Table 2 shows that in 36.7% of the deals we study the target firm has a

dominant shareholder, defined as a shareholder that owns at least 20% of the firm’s stock, but not

all of the firm’s stock. In deals that use escrow contracts the fraction of the deals with a dominant

target firm shareholder is significantly higher than it is for the deals that do not use an escrow

contract (48.3% versus 24.1%). This finding is consistent with the notion that in target firms with a

dominant shareholder an escrow contract can be particularly useful to manage this shareholder’s

acquisition-related transaction risk because if there is an escrow contract in place all target

shareholders would bear pro rata costs of bidder recourse actions subsequent to an acquisition (i.e.,

be jointly and severally liable for any breaches of the representations and warranties section of the

acquisition agreement). However, if such a contract is not in place bidder recourse actions

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subsequent to an acquisition could result in the target firm’s dominant shareholder being held liable

and sued by the bidder.

Panel C of Table 2 reports statistics on target firm characteristics for all the deals in our

sample, as well as for the subsamples with or without an escrow contract. Targets tend to be smaller

for the deals with an escrow contract than without (median target price of $68.1 million versus $80.0

million), and target firms also tend to have a lower interest coverage ratio in deals that use an escrow

contract (3.89 versus 1.93).

Panel D of Table 2 compares the usage of an escrow contract between deals with or without

an earnout contract, deals that use caps versus deals without caps, deals that are asset sales versus

deals that are stock purchase transactions, deals that are private target sales versus subsidiary sales,

and deals in which there is a target firm dominant shareholder. Consistent with the Panel A results,

this panel shows that the use of escrow contracts is more frequent in deals with a cap, that are asset

sales, that are the sale of a private target, or in which there is a dominant target firm shareholder.

Table 2, Panel E provides evidence on the discount in the price of an unlisted target relative

to that of a public target for the deals that we study. Officer (2007) documents discounts of

approximately 28% and 17% in the price paid for subsidiary, and private target firm acquisitions. To

calculate the discount in the price of an unlisted target we use the price to sales multiple and follow a

matching criteria similar to that in Officer (2007) to choose comparable public target transactions:

we require that both targets are in the same two-digit SIC code industry, that the transactions are at

most three years apart (the three years window is centered around the acquisition announcement of

the private target), and that the value of the transactions differ at most by 20%.4 We calculate the log

ratio of the private target multiple to the public target multiple. The private target premium is then

interpreted as the percentage difference between the two multiples. Panel E in Table 2 shows that

4 We use the price-to-sales multiple to calculate the unlisted target firm discount rather than the price-to-EBITDA multiple because in a number of instances the EBITDA value of the target firms in our sample is negative.

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the average unlisted target discount for our sample is 24.3%. Further, consistent with Officer (2007),

we find that the discount is larger for subsidiary than private firm acquisitions. Specifically, we find

that the average discount in the price paid for the target is 33.3% and 17.1% for these two types of

acquisitions.

Table 3 reports information on the fraction of the deals with escrow contracts that appear

in each of the Fama-French 49 industries, as well as the fraction of the deals we study in each of

these industries. This table shows that the use of escrow contracts does not seem to be clustered

within particular industries. Thus, the findings of our paper are unlikely to be driven by a few select

industries.

3. Empirical findings

3.1 The determinants of the use of an escrow contract

Table 4, Panel A provides the results of the determinants of the use of an escrow contract.

The first model in this table reports the marginal effects from a probit model where the dependent

variable takes a value of one if an escrow contract is used in the context of an acquisition, and zero

otherwise. Because we use the predicted values from this model later in second stage models

examining how the presence of an escrow contract affects the discount in the price paid for a private

target relative to public targets and how the existence of such a contract affects bidder firm

acquisition announcement returns, we also include two variables used as instruments in the Table 4,

Panel A probit model. These two variables are the percent of private firm and subsidiary deals in a

target’s four-digit SIC industry that used an escow contract during the previous year and an indicator

variable for the previous use of hybrid securities as a method of payment by the acquirer. Finally,

because Officer (2007) shows that the discount in the price paid for private and subsidiary targets

relative to public targets is accentuated when credit conditions are tight as measured by the spread of

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the average commercial and industrial loans rate relative to the federal funds rate it could be that

credit conditions will also impact the propensity of bidder and target firms to make use of escrow

contracts. Consequently, in the Table 4, Panel A probit model we control for the spread of the

average commercial and industrial loans rate relative to the federal funds rate.

The results for the first model show that the Table 2 univariate finding that escrow contracts

are used more often in private firm than in subsidiary acquisitions is robust to examining this issue

in a multivariate context. Specifically, the findings from this table imply that if an acquisition is a

private firm rather than a subsidiary acquisition this increases the likelihood than an escrow contract

is used by 27.0%. Because a bidder would have legal recourse against both the parent firm that sold

it a subsidiary and the principal shareholders of this firm, while for a private firm acquisition the

bidder would only have recourse against the principal shareholders of the target, this finding is

consistent with escrow contracts being used to mitigate a bidder’s acquisition-related transaction

risk.

The Table 4, Panel A probit model results also provide evidence on how the ratio of the size

of the target to the bidder impacts the likelihood that an escrow contract is used in an acquisition

transaction. Presumably, the larger is the value for this ratio, the more important is should be for a

bidder to manage acquisition-related transaction risk. Consistent with this notion, the Table 4, Panel

A findings show that this ratio positively impacts the probability that an escrow contract is used.

To evaluate the economic importance of this result, we calculate the change in this probability for an

increase from the 25th to the 75th percentile of the ratio of target to bidder firm value. We find that

such an increase would result in a 0.8% higher likelihood that an escrow contract is used.

Table 4, Panel A also provides evidence on whether when there is greater information

asymmetry about the value of a target firm, if it is more likely that an escrow contract is used as part

of the acquisition deal. This table uses five different measures to proxy for information asymmetry

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between the bidder and target about target firm value. Specifically, we consider whether 1) a target

operates in an industry in which earnings volatility is higher, 2) analyst coverage is lower in the

target’s industry, 3) the target firm operates in a different industry than does the bidder, 4) the target

has greater total accruals, as measured by the difference between its earnings and its free cash flows

(e.g., Dechow and Dichev (2002)), 5) the target is financially distressed, as measured by a lower

interest coverage ratio. We find strong evidence supporting the notion that when there is more

information asymmetry between a bidder and target about the target’s value, this increases the

likelihood that an escrow contract is used. Specifically, the Table 4, Panel A results show that this

likelihood is positively associated with an indicator variable for if earnings volatility in the target’s

four-digit SIC industry is in the top sample quintile, whether analyst coverage for the public firms in

a target’s four-digit SIC industry is not in the top sample quintile, whether the target operates in a

different four-digit SIC industry that does the bidder, and the target’s total accruals.5 Also, we find

that the likelihood an escrow contract is used is negatively associated with a target’s interest coverage

ratio. These results are for the most part economically important. Specifically, we find that if a target

operates in an industry with higher earnings volatility, lower analyst coverage, or its four-digit SIC

industry is different than the bidder’s four-digit SIC industry this leads respectively to a 0.9%, 5.4%,

or 2.0% increase in the probability that an escrow contract is used. Likewise, we find that an increase

from the 25th to the 75th percentile value of total accruals or the interest coverage ratio would result

respectively in a 4.3% or -0.3% change in the probability that an escrow contract is used.

Table 4, Panel A also provides evidence on the prediction that if a target firm has a majority

shareholder, who is not the single shareholder of the firm, an escrow contract can be particularly

useful to manage this shareholder’s acquisition-related transaction risk because if there is an escrow

5 For the low analyst coverage indicator variable, we consider whether analyst coverage in a target’s industry is in the bottom four quintiles of the distribution of this variable rather than the bottom quintile of this distribution because for 42% of the targets in our sample none of the public firms in their four-digit SIC industry are covered by analysts.

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contract in place all target shareholders would bear pro rata costs of bidder recourse actions

subsequent to an acquisition. In contrast, if such a contract is not in place bidder recourse actions

subsequent to an acquisition could result in the target firm’s major shareholder being personally sued

by the bidder. Consistent with the notion, that an important motive for escrow contracts is that they

help reduce the transaction risk of the dominant shareholder of a target firm, we find that if a target

firm has such a dominant shareholder this reduces the probability that an escrow contract is used by

21.0%.

Further, Table 4, Panel A documents evidence on the association between the likelihood of

using an escrow contract and several other forms of contingent payment mechanisms are associated

with the use of an escrow contract. We find that if a bidder agrees to a cap on the amount it could

sue the target subsequent to the acquisition this increases the likelihood that an escrow contract is

used by about 32.0%. This finding is supports the notion that if a bidder agrees to such a cap this

would make it easier to persuade the target to agree to an escrow contract, suggesting a complement

relation between the existence of a cap and the use of an escrow contract. The Table 4, Panel A

probit model results also show that the use of escrow contract is unrelated to the use of an earnout

contract. This finding can be explained by earnout contracts and escrow contracts serving different

purposes. Whereas earnout contracts are meant to increase the bidder’s upside return from an

acquisition, escrow contracts protect bidders from downside risk.

Finally, the Table 4, Panel A probit model results also provide evidence on if an acquisition

occurs in the context of an asset sale whether this decreases the likelihood that an escrow contract is

used. This could potentially be the case because bidders do not assume target firm liabilities in asset

sales, which should reduce bidder transaction-related risk. Although the table results show that the

association between whether an acquisition occurs in the context of an asset sale is indeed negatively

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associated with whether an escrow contract is used, this association is not statistically significant at

conventional levels.

The second model in Panel A of Table 4 is an OLS model, in which the dependent variable

is the ratio of the funds placed in an escrow account relative to the total purchase price for the

target. For this model the dependent variable takes a value of zero for deals that do not use an

escrow contract. The results for this model show that all of our findings from the first model are

robust to using a continuous measure for the extent to which bidder and target firm make use of

escrow contracts.

3.2 Escrow contracts and the time-to-completion of acquisition deals

Table 5 provides evidence on how the time-to-completion of acquisition deals, the number

of days between the announcement of a deal and its closing, is related to the use of an escrow

contract.6 If the use of escrow contracts helps to reduce bidder’s due diligence costs then the use of

these contracts would reduce the time-to-completion of acquisition deals. The models we use in

Table 5 include as controls the independent variables from the Table 4 models. The first model in

Table 5 shows that, as expected, whether an escrow contract is used in the context of an acquisition

agreement is negatively associated with the time-to-completion of an acquisition deal. The

coefficient estimate on the escrow agreement dummy variable indicates that the use of an escrow

contract reduces the time-to-completion by 20.5 days, or by nearly 36% (= 20.5/57.5).

In the second model we replace the escrow agreement dummy with the instrumented escrow

agreement dummy calculated from Table 4. Here also, we find a negative effect of an escrow

contract on the time-to-completion of a deal. Multiplying the coefficient estimate of -52.925 with the

mean value for the instrumented escrow dummy variable, we find that the results for the second

6 For a detailed review of the process of firm acquisition, please see Boone and Mulherin (2007).

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model indicate that the use of an escrow contract is associated with a 28.5 day decrease in the time-

to-completion of a deal. This represents nearly a 50% reduction in the time-to-completion for a deal.

Finally, the third model in Table 5 reports the findings for only deals with an escrow contract. In

this model the escrow indicator variable is replaced with the ratio of the dollar amount of the sale

proceeds placed in an escrow account to the total selling price of the target. The negative coefficient

on the escrow size variable indicates that among deals with an escrow contract, the time-to-

completion of the deal is decreasing in the amount of the sale proceeds placed in an escrow account.

3.3 The effect of the use of an escrow contract on the discount paid for an unlisted target

Officer (2007) shows that unlisted targets are typically sold at discounts of about 15% to

30% relative to acquisition multiples for comparable publicly traded targets. It is possible that

because the use of escrow contracts reduces bidder acquisition-related transaction risk that the use

of these contracts reduce the discount in the price paid for an unlisted target. Table 6 provides

evidence on this issue. The first model in this table regresses the discount in the price paid for a

private firm or subsidiary on an indicator variable for whether an escrow contract is used. The

second model in this table controls for the endogeneity in the decision to use an escrow contract by

replacing the indicator variable for whether an escrow contract is used with the fitted value from

Model 1 of Table 4, Panel A. We control for the following acquisition characteristics, whether a deal

is an asset sale, whether the target is a stand-alone private firm, whether the target and acquirer are

in the same industry, the relative size of the target to the bidder, and the size of the bidder. To

control for asymmetric information concerning the value of the target firm, we include in the Table

6 models the indicator variable for whether the target and bidder firms operate in the same industry,

as well as the indicators for if the target operated in an industry with high earnings volatility or low

analyst coverage. Finally, because Officer (2007) shows that discounts for unlisted targets are larger

17

when credit conditions are tighter, as measured by the spread between the average commercial and

industrial loans rate and the federal funds rate, and also when IPO volume is higher, we control for

these two variables.

The first model in Table 6, Panel A shows that price paid for a target firm is 8.2% higher

when an escrow contract is used. These estimates of the valuation impact are slightly higher if

instead we apply the estimate in the second model of Table 6, Panel A, Model (2) (i.e., a coefficient

of 0.166). Given this coefficient, the implied effect onto the unlisted target discount evaluated at the

expected probability of using an escrow agreement (from Table 4, Model (1)) is 0.166*0.539 = 0.089.

That is, our calculations show a reversal of the unlisted target discount of 8.9% if an escrow

agreement is included as part of the transaction. We offer an economic interpretation of this effect

as documented in Figure 1, Panel B. Assuming the effect is calculated for a unlisted target with sales

of $100 million that -- absent an escrow agreement -- would sell for a price of $165 million (or 1.65

times sales, representing the median deal to sales multiple for our sample of transactions), and also

assuming the average size of an escrow of 12.2% and the typical recapture rate of 60% of the escrow

deposit, we calculate a net benefit for the unlisted target from using an escrow contract of $10.4

million.7 That estimate implies that agreeing to include an escrow contract in the transaction

contributes nearly 6.3% ($10.4 /$165) to the value of the unlisted target.

7 Our example evaluates the effect of the escrow agreement on target value assuming an average private target discount of 24.3% (the average in our study), an average size of escrow of 12.2% (based on descriptive statistics in Table 2) and on an assumed recapture rate of the escrow deposit of 60% (noted in the 2009 J.P. Morgan escrow services proprietary data sample). The calculation proceeds as follows. We assume that the target firm would sell at 1.65 times its sales if there is no escrow agreement included in the transaction (this is the median such multiple in our sample). We then calculate the deal value to sales multiple of a comparable public target firm with identical sales, based on the assumed average unlisted target discount of 24.3%. Using the deal value-to-sales multiple for the comparable public target deal, we next calculate the new deal value to sales multiple for the same unlisted target, if the transaction included an escrow agreement. To obtain the new multiple, we multiply the public counterpart target multiple calculated above by the reduced private target discount in the presence of an escrow agreement. Based on the so-calculated multiple, we are able to determine the new sales price for the unlisted target, which we adjust for the recapture rate of the escrow deposit that is included in it, in order to arrive to the final price for the transaction and the consequent net gain to the target.

18

Table 6, Panel B provides evidence on whether the extent to which the use of an escrow

contract reduces the discount in the price paid for a unlisted target is more pronounced when

information asymmetry about the value of the target is greater, as measured by whether the target

operates in an industry with high earnings volatility or low analyst coverage. The second model in

this table shows that using the instrumented value for whether there an escrow contract is used we

find that the extent to which an escrow contract reduces the discount paid for an unlisted target is

more pronounced when the target operates in an industry with earnings volatility. Using the estimate

from this model, we calculate that the benefit of using an escrow contract is 0.0847 * 0.235 =

0.0199, or 2% higher if the unlisted target operates in an industry with high earnings volatility. Based

on the valuation example presented in Figure 1, Panel B, this estimate corresponds to a marginal

increase of 1.26% into the sales price of the unlisted target. That is, if a target in high earnings

volatility industry uses an escrow agreement that would add additional 1.26% to its value, as

compared to firms that are not in high volatility industry.

Similarly, we evaluate the effect of using an escrow contract for targets in industries that

have low analyst coverage. The fourth model in Table 6, Panel B shows that the degree to which an

escrow contract reduces this discount is more pronounced in these industries. Using the coefficient

estimate on the interaction variable in this model, we estimate that in terms of impact on the

underlying price as presented in the example of Figure 1, Panel B, the use of an escrow contract in

industries with low analyst coverage would add an incremental $7.3 million, or 4.4% (=$8.1/$165) to

the unlisted target’s value.

Next, because Officer (2007) shows that when the spread of the average commercial and

industrial loan rate relative to the federal funds rate this increases the discount in the price paid for

an unlisted target, we examine whether the extent to which an escrow contract reduces this discount

is more pronounced when this spread value is larger. The coefficients on the interaction variables in

19

the first two models of Table 6, Panel C provide evidence that this is the case. From the coefficient

estimates for the second model in this table, we estimate than an increase in the spread value from

the 25th to the 75th percentile value would result in an escrow contract reducing the discount in the

price paid for an unlisted target by 9.09%.

Similarly, we evaluate whether for targets that are large relative to the bidder the positive

effect of an escrow contract on the price paid for the target is more pronounced. The third and

fourth models in Table 6, Panel C provide evidence supporting this proposition. We use the

coefficient estimate on the interaction variable in the fourth model to calculate that a movement

from the 25th to the 75th percentile of target to bidder relative size would result in a 8.0% increase in

the sales price of the unlisted target.

3.4 The effect of the use of an escrow contract on bidder acquisition announcement returns

The use of escrow contracts could reduce bidder costs in three ways. First, because the use

of these agreements should reduce bidder losses in the event that the seller fails to meet specific

terms of the acquisition agreement or it hides negative information about the target, escrow

contracts should truncate potential left tail negative outcomes for bidders resulting from private firm

and subsidiary acquisitions. Second, the use of an escrow contract can potentially reduce the need

for a bidder to incur significant information gathering costs about a target firm so that a precise

estimate for the value of the target can be determined. Finally, employing an escrow contract can

allow a bidder to avoid financial and time costs that would be incurred if the bidder had to sue target

firm parties subsequent to an acquisition in order to obtain recourse.

As such, we examine whether reductions in bidder costs in private firm and subsidiary

acquisitions resulting from the use of escrow contacts lead to more positive market reactions to the

announcement of an acquisition deal. Table 7, Panel A, provides evidence on this issue and shows

20

that indeed the use of an escrow agreement results in higher bidder acquisition announcement

returns. If we evaluated the economic impact of such announcement returns using Model (1)

estimates in Table 7, Panel A, it is an increase in bidder’s market capitalization of nearly 89 cents for

every dollar deposited by seller into the escrow contract fund.8 If we use the estimates from Model

(2) in in Table 7, Panel A, the effect on bidder market capitalization is almost $1.26 increase for

every dollar deposited in the escrow contract fund. Panels B and C in Table 7 show further that this

effect is more pronounced in instances when it would be more important for a bidder to reduce

acquisition-related transaction risk. Specifically, the results from these panels document that this

effect is more pronounced when earnings volatility in a target’s industry is greater, analyst coverage

in this industry is lower, the relative size of the ratio of target to bidder firm value is larger, or credit

conditions are tighter.

4.0 Conclusion

Although many private firm and subsidiary acquisition deals make use of escrow contracts,

whereby a fraction of the total sale proceeds are placed in an escrow account, there is scant empirical

evidence on these contracts. Escrow contracts give the bidder the opportunity to lay claim on these

funds subsequent to the acquisition if the seller fails to meet specific terms of the acquisition

agreement or it is found that negative information about the target was hidden from the bidder. We

hypothesize that escrow contacts are an efficient contacting mechanism that help bidders and targets

to manage acquisition-related transaction risk and mitigate information asymmetry problems. To test

this hypothesis, we study 569 private firm acquisitions and 374 subsidiary acquisitions made by

publicly traded firms over the 1994-2009 period and hand-collect data on escrow contract usage.

8 We calculate that effect by multiplying the coefficient estimate of 0.013 on the escrow dummy by the dollar value

deposited in the escrow and divide it by the market value of the acquirer. We then average these across all observations in our sample to obtain the estimate above.

21

Supporting our hypothesis, we show that the likelihood an escrow contract is used in a private firm

or subsidiary acquisition is higher when bidder transaction risk or information asymmetry about the

value of the target is larger. Further, we document that escrow contracts enable the seller to obtain a

higher sale price and that the use of these contracts positively impacts the extent to which a private

firm or subsidiary acquisition results in value creation for the bidder.

22

References Amihud, Y., Lev B., and Travlos N., 1990. Corporate Control and the Choice of Investment Financing: The Case of Corporate Acquisitions. Journal of Finance 45: 603-616. Bharadwaj, A., Shivdasani, A., 2003. Valuation Effects of Bank Financing in Acquisitions. Journal of Financial Economics 67: 113-148. Boone, A., Mulherin, J. H., 2007. How Are Firms Sold? Journal of Finance 62: 847 – 875. Brown, D., Ryngaert, M., 1991. The Mode of Acquisition in Takeover, Taxes and Asymmetric Information. Journal of Finance 553-569. Cain, M.D., Denis, D.J., Denis, D.K., 2011. Earnouts: A Study of Financial Contracting in Acquisition

Agreements. Journal of Accounting and Economics 51, 151-170. Dechow, P.M., Dichev, I.D., 2002. The Quality of Accruals and Earnings: The Role of Accrual

Estimation Errors. Accounting Review 77, 35-59. Erickson, M., 1998. The Effect of Taxes on the Structure of Corporate Acquisitions. Journal of Accounting

Research 36, 279-298. Fama, E., French, K., 1992. The Cross Section of Expected Stock Returns. Journal of Finance 47, 427-465. Fuller, K., Netter, J., Stegemoller, N., 2002. What Do Returns to Acquiring Firms Tell us? Evidence

from Firms that Make Many Acquisitions. Journal of Finance 57, 1763-1793. Ghosh, A., Ruland, W., 1998. Managerial Ownership, the Method of Payment for Acquisitions, and Executive Job Retention. Journal of Finance 53: 785-798. Harford, J., Klasa, S., Walcott, N., 2009. Do Firms Have Leverage Targets? Evidence from Acquisitions.

Journal of Financial Economics 93, 1-14. Kaplan, S., 1989. Campeau's Acquisition of Federated: Value Destroyed or Value Added. Journal of Financial Economics 25: 191-212. Kaplan, S.N., Stromberg, P., 2003. Financial contracting theory meets the real world: An empirical

analysis of venture capital contracts. Review of Economic Studies 70, 281-316. Kohers, N., Ang, J., 2000. Earnouts in Mergers: Agreeing to Disagree and Agreeing to Stay. Journal of

Business 73, 445-476. Martin, K., 1996. The Method of Payment in Corporate Acquisitions, Investment Opportunities, and

Management Ownership. Journal of Finance 51: 1227-1246. Netter, J., Stegemoller, M., 2011. Implications of Data Screens on Merger and Acquisition Analysis: A

Large Sample Study of Mergers and Acquisitions from 1992 to 2009. Review of Financial Studies 24, 2316-2357.

23

Officer, M., 2007. The Price of Corporate Liquidity: Acquisition Discounts for Unlisted Targets. Journal of Financial Economics 83, 571-598.

Officer, M., Paulsen, A., Stegemoller, M., Wintoki, M.B., 2009. Target‐Firm Information Asymmetry and

Acquirer Returns. Review of Finance 13, 467‐493. Travlos, N., 1987. Corporate Takeover Bids, Method of Payment, and Bidding Firms’ Stock Returns.

Journal of Finance, 943-963.

Figure 1. TPanel A. T

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24

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disbursed to sen written instru

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25

Figure 1. The Mechanism of an Escrow Agreement. Panel B. An Example of an Escrow Agreement Impact on the Value of the Target. In this example we assume that a private target with sales of $100 M is purchased without an escrow contract in the sale process. Allowing for a unlisted target discount of 24.3% (sample average), a price-to-sales multiple of 1.65 (sample median), a relative escrow contract deposit to deal value of 12.2% (sample average), a recapture rate of escrow agreement deposit of 60% (J.P. Morgan Escrow Services estimate) and escrow agreement reversal in the unlisted target discount of 8.9% (2SLS estimate in Table 4, Model (2)), we calculate the net value effect to target shareholders if an escrow contract is used in the sale. We assume in the example that escrow contract funds earn no interest while being placed with the escrow services agent.

PRICE: WITH NO ESCROW

WITH ESCROW

ESCROW SHARE

OTHER CONSIDERATION

TOTAL PRICE W/ ESCROW

NET EX- POST ESCROW GAIN

($M) ($M) ($M) % Escrow

Private T 12.2% 87.8% New Price w/ Escrow

($M) Escrow

T. Price ($M) $165.0 $184.4 → $22.5 →  $161.9 → $175.4 →  $10.4

T. Sales ($M) $100.0

↓ ↑ % ESCROW

RECAPTURED ↓

Price/Sales 1.65 1.844 Economic

Effect

Public T ↓ ↑ 60% 6.30%

T. Price ($M) $218.0

T. Sales ($M) $100.0

Imputed Price/Sales9 2.18 2.18

↓ ↑

Priv. T. Discount

-0.243 -0.154

↓

Escrow Impact 0.089

(Table 4, Model (2))

9 Public target sales multiple imputed based on expected private target discount -0.243; i.e., -0.243 = [1.65/Public target discount] -1.

26

Figure 2. Example of an Escrow Agreement: The merger of Syntax-Brillian Corporation and Vivitar Corporation (10/26/06) AGREEMENT AND PLAN OF REORGANIZATION, AMONG SYNTAX-BRILLIAN CORPORATION, SBV -

AC CORPORATION, VIVITAR CORPORATION, AND GREAT STEP CO., LTD. DATED AS OF OCTOBER 27, 2006

7.3 Escrow Arrangement.

At the Effective Time, Great Step will be deemed to have received and deposited with the Escrow Agent (as defined below) the Escrow Shares (plus any additional shares as may be issued upon any stock split, stock dividend, or recapitalization effected by Syntax-Brillian after the Effective Time), without any act of Great Step. As soon as practicable after the Effective Time, the Escrow Shares will be deposited with Arizona Escrow Financial Corporation (or other institution reasonably acceptable to Syntax-Brillian and Great Step), as Escrow Agent (the “Escrow Agent”), such deposit to constitute an escrow fund (the “Escrow Fund”) to be governed by the terms set forth herein and in the Escrow Agreement. Syntax-Brillian will pay the administrative costs relating to the Escrow Fund, including the charges of the Escrow Agent. The Escrow Fund shall be available to compensate Syntax-Brillian for any Syntax-Brillian Losses. The Escrow Fund shall be held as a trust fund and shall not be subject to any lien, attachment, trustee process, or any other judicial process of any creditor of any party, and shall be held and disbursed solely for the purposes and in accordance with the terms of this Section and the Escrow Agreement. Except in the case of (i) fraud or (ii) a breach of any of the representations and warranties of Great Step in Section 3.3(a), Section 3.3(b), or Section 3.3(c) of this Agreement, the right of Syntax-Brillian after the Effective Time to assert indemnification claims and receive indemnification payments from the Escrow Fund pursuant to this Section shall be the sole and exclusive right and remedy exercisable by Syntax-Brillian with respect to any inaccuracy or breach in any representation, warranty, or covenant made by Vivitar or Great Step contained in this Agreement or in any instrument delivered pursuant to this Agreement or in connection with the transactions contemplated hereby. Syntax-Brillian may not receive any shares from the Escrow Fund unless and until Officer’s Certificates (as defined in Section 7.3(c) below) identifying Syntax-Brillian Losses, the aggregate cumulative amount of which exceed $100,000, have been delivered to the Escrow Agent as provided in Section 7.3(c); in such case, Syntax-Brillian may recover from the Escrow Fund the entire amount of the cumulative Syntax-Brillian Losses.

(a) Escrow Period; Distribution upon Termination of Escrow Periods. Subject to the following requirements, the Escrow Fund shall be in existence immediately following the Effective Time and shall terminate at 5:00 p.m., California time, on the Expiration Date (the “Escrow Period”); provided that the Escrow Period shall not terminate with respect to such amount (or some portion thereof), that is necessary in the reasonable judgment of Syntax-Brillian, subject to the objection of Great Step and the subsequent arbitration of the matter in the manner provided in this Section, to satisfy any unsatisfied Syntax-Brillian Losses concerning facts and circumstances existing prior to the termination of the Escrow Period specified in any Officer’s Certificate delivered to the Escrow Agent prior to termination of the Escrow Period. As soon as any such Syntax-Brillian Loss has been resolved, the Escrow Agent shall deliver to Great Step the remaining portion of the Escrow Fund not required to satisfy any other such unresolved Syntax-Brillian Loss.

(b) Protection of Escrow Fund. Escrow Agent shall hold and safeguard the Escrow Fund during the Escrow Period, shall treat such fund as a trust fund in accordance with the terms of this Agreement and not as the property of Syntax-Brillian and shall hold and dispose of the Escrow Fund only in accordance with the terms of this Section. Any shares of Syntax-Brillian Common Stock or other equity securities issued or distributed by Syntax-Brillian (including shares issued upon a stock split) in respect of shares of Syntax-Brillian Common Stock in the Escrow Fund at the time of issuance or distribution shall be added to the Escrow Fund and become a part thereof. Cash dividends on shares of Syntax-Brillian Common Stock in the Escrow Fund shall not be added to the Escrow Fund but shall be distributed to Great Step. Great Step shall have voting rights and cash dividend distribution rights with respect to the shares of Syntax-Brillian Common Stock in the Escrow Fund (and on any voting securities added to the Escrow Fund in respect of such shares of Syntax-Brillian Common Stock).

(c) Claims Upon Escrow Fund Upon receipt by the Escrow Agent at any time on or before 5:00 p.m. California time on the Expiration Date of a certificate signed by any officer of Syntax-Brillian (an “Officer’s Certificate”): (A) stating that Syntax-Brillian has paid or properly accrued or reasonably anticipates that it will have to pay or accrue Syntax-Brillian Losses and specifying an aggregate amount thereof, and (B) specifying in reasonable detail the individual items of Syntax-Brillian Losses included in the amount so stated, the date each such item was paid or properly accrued, or the basis for such anticipated liability, and the nature of the misrepresentation, breach of warranty or covenant to which such item is related and to the extent known a reasonable summary of the facts underlying the claim,

27

and if no objection is received from Great Step in accordance with this Section, the Escrow Agent shall, subject to the provisions of this Section, deliver to Syntax-Brillian out of the Escrow Fund, as promptly as practicable, shares of Syntax-Brillian Common Stock held in the Escrow Fund in an amount equal to such Syntax-Brillian Losses. For the purposes of determining the number of shares of Syntax-Brillian Common Stock to be delivered to Syntax-Brillian pursuant to this Section, the shares of Syntax-Brillian Common Stock shall be valued at the Syntax-Brillian Common Stock Average Price.

(d) Objections to Claims. At the time of delivery of any Officer’s Certificate to the Escrow Agent, a duplicate copy of such certificate shall be delivered to Great Step in the manner contemplated by Section 7.3(d) and for a period of 30 days after such delivery, the Escrow Agent shall make no delivery to Syntax-Brillian of any Escrow Shares pursuant to this Section unless the Escrow Agent shall have received written authorization from Great Step to make such delivery. After the expiration of such 30-day period, the Escrow Agent shall make delivery of shares of Syntax-Brillian Common from the Escrow Fund in accordance with this Section, provided that no such payment or delivery may be made if Great Step shall object in a written statement to the claim made in the Officer’s Certificate, and such statement shall have been delivered to the Escrow Agent prior to the expiration of such 30-day period.

28

Table 1. Variable Definitions. Brief definitions of the main variables that appear in this study. Variables DefinitionMain Dependent Variables CAR -1 to +1

Cumulative abnormal return (CAR) for the acquirer from trading day t-1 before announcement of the acquisition (t) to trading day t+1 after the announcement of the acquisition. We use a market model to estimate the acquirer’s equity beta over 365 calendar days, ending 46 days before the event. We use equally-weighted market returns in the market model. The variable (CAR) is further winsorized at 1% in each tail of its sample distribution.

Acquisition Discount

We calculate the acquisition discount following Officer (2007). The acquisition discount is defined as the percent difference between deal value to sales multiple for a unlisted firm and the average such multiple for industry- and size-matched comparable acquisitions of publicly traded firms. The portfolio of comparable acquisitions for each unlisted target is all acquisitions of publicly traded targets in the same Fama-French 49 industry as the unlisted target with deal value within 30% of deal value for the unlisted target and occurring with four years window centered on the acquisitions announcement of the unlisted target. We truncate outliers in acquisition multiples data – estimates larger than one are discarded from the sample.

Escrow Indicator Variable An indicator variable if the deal has an escrow agreement as part of the payment terms. Escrow agreements require fraction of the sales price to be deposited with a custodian bank for a pre-determined period of time, following the acquisition completion. Data on escrow agreements are hand collected from the DEF14, DEF14A or 8K of the acquirer.

Escrow Size The natural logarithm of the size of the escrow relative to deal value. The ratio is winsorized at 1% in each tail of its sample distribution.

Time-to-completion The calendar days between the date of announcement of the transaction and the date of closing the transaction.

Litigation An indicator variable equal to one if there is transaction-related litigation I which the acquirer is the defendant, subsequent to the closing of the transaction.

Main Explanatory Variables Indicator Variable for Use of Caps A variable equal to one if the acquisition agreement indicates the use of a cap on

the seller liability in the merger agreements. Caps are limitations onto the size of the liability of the seller, after the closing of the acquisition. Data on caps are hand collected from the DEF14, DEF14A or 8K of the acquirer.

Indicator Variable for Dominant Shareholder

Indicator variable equal to one if the unlisted target has a dominant shareholder. Data to code this variable are hand collected from the DEF14, DEF14A or 8K of the acquirer. A dominant shareholder is defined as a shareholder that owns at least 20 percent of the target’s equity, but is not the sole target firm shareholder.

Indicator Variable for Asset Sale Indicator variable equal to one if the transaction is an asset sale (that is, a cash purchase of assets that are separate from any attached liabilities) or stock sale (that is cash purchase of common stock). Source of data is Pratt’s Statistics.

Target is Subsidiary Indicator variable equal to one if the target is a subsidiary of another company, and zero if it is a private stand-alone target. Source of data is SDC.

Target & Acquirer are in the Same Industry (4-digit SIC Code)

Indicator variable equal to one if both target and acquirer are in the same industry, defined as a 4-digit SIC code. Source of data is SDC.

29

Target Interest Coverage Interest coverage for the target, defined as EBITDA-to-interest expense ratio, as presented in Pratt’s Statistics. The ratio is winsorized at 1% in each tail of its sample distribution.

Target Accruals Target’s accruals calculated as the ratio of (gross profits – operating profits) divided by total assets. Data are from Pratt’s Statistics. The ratio is winsorized at 1% in each tail of its sample distribution.

Ln(Target Value) Natural logarithm of the deal value. Source of data is Pratt’s Statistics. The variable is winsorized at 1% in each tail of its sample distribution. The deal value is the total consideration offered to the seller and includes any cash, notes and/or securities that were used as a form of payment plus any interest-bearing liabilities assumed by the buyer.

Target Relative Value Value of the deal to the market capitalization of the acquirer, calculated 50 calendar days prior to the announcement of the acquisition. The variable is winsorized at 1% in each tail of its sample distribution.

Ln (Acquirer Assets) Natural logarithm of the book assets of the acquirer as of the fiscal year end preceding the year of the acquisition announcement. The variable is winsorized at 1% in each tail of its sample distribution.

Indicator for Earnout Use Indicator variable if an earnout is used in the transaction. Earnout is the use of a basket of options, as means of payment offered to the seller by bidder. Source of data is SDC and Pratt’s Statistics.

Indicator for Installment Note Sale Use

Indicator variable for the use of installment note sale (that is sale through a promissory note from the buyer to the seller). Data is hand collected from Pratt’s Statistics.

C&I Spread Spread of the Commercial & Industrial (C&I) loans yield over the T-bill rate.

Indicator for Top Quintile of Earnings Volatility of the Target Industry (4-digit SIC)

For each year, for each public firm in Compustat, we calculate the standard deviation of its ROA over the preceding five years. We then take the median such ratio per each industry (defined as a 4-digit SIC code) and year. We then rank these standard deviations, and generate an indicator variable equal to one if the median standard deviation is in the top quintile of the sample distribution, and zero otherwise.

Indicator for Low Analyst Coverage of the Target Industry (4-digit SIC)

Each year we sort into quintiles analyst coverage (number of distinct analysts) of all publicly listed companies in IBES database, per each industry (defined as a 4-digit SIC code). We then define an indicator variable for low analyst coverage to be equal to one if the analyst coverage of the target industry is in the bottom four quintiles within a given year, and zero otherwise.

Excluded Instruments Percent of Deals in Target Industry that Use Escrow Agreement, in the Previous Year

Percent of deals in the previous year in the target industry that use escrow agreement. Data are hand collected from the DEF14, DEF14A or 8K of the acquirers in our sample.

Indicator for Previous Use of Hybrid Securities by the Acquirer

Prior use of hybrid payments by the same acquirer. Source of data is SDC.

30

Table 2. Univariate tabulations for the sample of transactions in this study. The sample includes sales of U.S. private companies or subsidiaries completed in 1994-2009, with target size of at least $25 million, whereas the acquirer did not have a controlling stake in the firm prior to the acquisition but achieved 100% stake after the acquisition. Panel A. Sample Characteristics All Deals Sample

Variable All-Sample (943 obs.)

Percent of Deals with an Escrow Agreement 52.1% Average time to completion 57.5 days Deals with Escrow Contract

Variable Escrow Contract

(491 obs.) Percent Deposited Through an Escrow Agreement 12.2% Average Escrow Agreement Size (US$ m) $11.69 Average Escrow Agreement Duration (Months) 17.4 Average time to completion 35 days

Panel B. Deal Characteristics. Reported statistics are averages for the variables of interest. Column (4) presents a Chi-squared test of differences between columns (1) and (2). In this test *** , **, and * indicate significant differences at the 1%, 5%, and 10% levels, respectively.

Percent of deals with:

Escrow Contract (491 obs.)

No Escrow Contract (452 obs.)

All-Sample (943 obs.)

Test of equality of (1) & (2)

(1) (2) (3) (4)

Earnout Payment Sale (%) 13.8% 10.4% 12.2% -

Method of payment is stock (%) 24.2% 20.6% 22.5% -

Percent of Deals with Liability Caps (%) 85.3% 61.1% 73.7% ***

Asset Purchase Transaction (%) 20.0% 33.2% 26.3% ***

Stock Purchase Transaction (%) 80.0% 66.8% 73.7% ***

Percent stand-alone targets 75.60% 43.80% 60.30% ***

Percent subsidiaries 24.40% 56.20% 39.70% ***

Percent with dominant shareholder 48.30% 24.10% 36.70% ***

31

Table 2. Univariate Tabulations (continued). The sample includes sales of U.S. private companies or subsidiaries completed in 1994-2009, with target size of at least $25 million, whereas the acquirer did not have a controlling stake in the firm prior to the acquisition but achieved 100% stake after the acquisition. Panel C. Target Characteristics. Reported statistics are medians for the variables of interest. Column (4) presents a Chi-squared test of differences between columns (1) and (2). In this test *** , **, and * indicate significant differences at the 1%, 5%, and 10% levels, respectively.

Average Target Characteristics

Escrow Contract (491 obs.)

No Escrow Contract (452 obs.)

Whole Sample

(943 obs.)

Test of equality of (1) & (2)

(1) (2) (3) (4)

Dollar Target Net Sales (in U.S.$ million) 38.4 63.7 48.7 ***

Dollar Target Total Assets (in U.S.$ million) 24.6 43.9 32.2 ***

Actual Target Price (in U.S.$ million) 68.1 80.0 73.0 ***

Relative Target Size (to Acquirer) 17.8% 18.9% 18.4% *

Target Interest Coverage 1.93 3.89 2.90 ***

Target ROE 0.16 0.12 0.14 ***

Target ROA 0.035 0.04 0.04 * Panel D. Comparisons across sub-samples of transactions with escrow agreement This table shows within the set of firms that have the characteristics presented in the row, how many have escrow agreement and how many do not. Reported statistics are averages for the variables of interest. Column (3) presents a Chi-squared test of differences between columns (1) and (2). In this test *** , **, and * indicate significant differences at the 1%, 5%, and 10% levels, respectively.

Deals with characteristics in

row & with escrow contract

Deals withoutcharacteristics in

row & with escrow contract

Test of equality of (1) & (2)

(1) (2) (3)

Use of Earnout 59.1% 52.1% -

Use of Cap 60.3% 29.1% ***

Asset Sales 39.5% 56.5% ***

Private Target Sales 65.2% 32.1% ***

Dominant Owner 68.5% 42.5% *** Panel E. Median Price to Sales Multiple, Average Relative Escrow Contract Size and Average Private Target Acquisition Discount. We define these variables in Table 1.

Private-Stand-Alone Target

(569 obs.)

Subsidiary Target

(374 obs.)

All Targets

(943 obs.)

Median Price-to-sales Multiple 2.02 1.35 1.65

Average Relative Escrow Size 0.155 0.089 0.122

Average Unlisted Target Discount -0.171 -0.333 -0.243

32

Table 3. Industry Tabulations. In this tabulation we show the percent of deals in our sample that have escrow and a target in the corresponding industry. We also show the percent of deals in our sample with target in the corresponding industry. We use the Fama-French 49 industry portfolios as the baseline industries in this table. The sample includes sales of U.S. private companies or subsidiaries completed in 1994-2009, with target size of at least $25 million, whereas the acquirer did not have a controlling stake in the firm prior to the acquisition but achieved 100% stake after the acquisition.

FF Ind. Code Fama-French Industry Definition Name

Percent Deals with Escrow Agreement and

Target in Industry Percent Deals with Target in Industry

1 Agriculture 0.4 0.4 2 Food Products 0.8 1.1 3 Candy & Soda 0.6 0.3 4 Beer & Liquor 0.2 0.3 5 Tobacco Products 0.4 0.5 6 Toys & Recreation 1.4 1.2 7 Entertainment 1.0 2.0 8 Printing and Publishing 0.4 1.5 9 Consumer Goods 0.6 0.6 10 Clothing & Apparel 2.9 2.5 11 Healthcare 3.5 2.8 12 Medical Equipment 3.3 4.3 13 Pharmaceutical Products 0.6 1.1 14 Chemicals 1.2 1.4 15 Rubber and Plastic Products 0.2 0.2 16 Textiles 1.9 1.9 17 Construction Materials 1.6 2.2 18 Construction 2.7 1.9 19 Steel Works Etc 1.0 0.9 20 Fabricated Products 1.6 1.7 21 Machinery 1.6 1.8 22 Electrical Equipment 0.6 1.2 23 Automobiles and Trucks 0.4 0.5 24 Aircraft 0.8 0.4 25 Shipbuilding, Railroad Equipment 0.4 0.3 26 Defense 0.0 0.2 27 Precious Metals 1.9 2.3 28 Non-Metallic and Industrial Metal Mining 0.2 0.6 29 Coal 4.7 4.4 30 Petroleum and Natural Gas 2.5 1.7 31 Utilities 14.4 12.9 32 Telecommunication 2.5 1.9 33 Personal Services 21.6 15.3 34 Business Services 6.0 6.6 35 Computers 2.3 2.3 36 Computer Software 0.4 0.6 37 Electronic Equipment 0.0 0.1

(continued on next page)

33

(continued from previous page)

FF Ind. Code Fama-French Industry Definition Name

Percent Deals with Escrow Agreement and

Target in Industry Percent Deals with Target in Industry

38 Measuring and Control Equipment 1.9 2.2 39 Business Supplies 4.1 4.5 40 Shipping Containers 2.7 4.3 41 Transportation 1.2 1.4 42 Wholesale 1.0 1.6 43 Retail 0.2 1.2 44 Restaurants, Hotels, Motels 0.2 0.2 45 Banking 1.4 1.6 46 Insurance 0.6 1.0 47 Real Estate 0.4 0.4 48 Financial Trading 0.8 1.1 49 Other 0.6 0.3

34

Table 4. Determinants of the Escrow Agreement Choice in Private Target Acquisitions. This table documents the determinants of the probability of including an escrow agreement as part of the unlisted target acquisition. Included but not shown are fixed effects for the year of acquisition’s completion and acquirer’s industry (the industry is defined as a portfolio as in the Fama and French (1992) 49 industry portfolios.) Model (1) is estimated by the Probit method and presents marginal effects. Model (2) presents estimates of a linear probability model. All variables are defined in Table 1. We use robust standard errors. The *** , **, and * indicate significance at the 1%, 5%, and 10% levels, respectively. The sample includes sales of U.S. private companies or subsidiaries completed in 1994-2009, with target size of at least $25 million, whereas the acquirer did not have a controlling stake in the firm prior to the acquisition but achieved 100% stake after the acquisition.

Dependent Variable Use of Escrow Agreement

Variable Probit OLS

(1) (2)

Indicator for Use of Caps 0.323*** 0.267*** t-stat (7.35) (6.95) Indicator for Presence of Dominant Shareholder 0.20*** 0.161*** t-stat (5.02) (4.51) Indicator for Asset Sale -0.012 -0.018 t-stat (1.24) (1.43) Target is Stand-alone Private Firm 0.27*** 0.22*** t-stat (5.97) (5.61) Target & Acquirer are in the Same Industry -0.02*** -0.005** t-stat (3.15) (2.16) Target Interest Coverage (scaled by 1,000) -0.121** -0.079* t-stat (1.99) (1.90) Target Accruals 0.64** 0.54** t-stat (2.11) (2.14) Ln (Target Value) -0.065*** -0.045*** t-stat (3.0) (2.74) Target Relative Value 0.025* 0.19* t-stat (1.80) (1.96) Indicator for Earn-out Use 0.020 0.011 t-stat (0.31) (0.22) C&I Spread 0.199*** 0.073** t-stat (3.04) (2.46)

Indicator Top Quintile Earnings Volatility Target Industry 0.009** 0.01** t-stat (2.09) (2.03) Indicator Low Analyst Coverage Target Industry 0.054* 0.038* t-stat (1.86) (1.79)

Excluded Instruments Percent of Deals in Target Industry that Use Escrow Agreement in the Previous Year 0.297* 0.207* t-stat (1.73) (1.68) Indicator Previous Use of Hybrid Securities by Acquirer 0.013* 0.012* t-stat (1.88) (1.91)

Observations 827 837

Pseudo R-squared 0.247

R-squared 0.305

35

Table 5. Multivariate Analysis of Time to Deal Completion. This table presents multivariate analysis of the time to deal completion. Models (1) and (3) offer OLS estimates, while Model (2) documents 2SLS estimates, where we instrument escrow agreement dummy using Model (2) in Table 4. Included but not shown are fixed effects for the year of acquisition’s completion and acquirer’s industry (the industry is defined as a portfolio as in the Fama and French (1992) 49 industry portfolios.) All variables are defined in Table 1. We use robust standard errors. The *** , **, and * indicate significance at the 1%, 5%, and 10% levels, respectively. The sample includes sales of U.S. private companies or subsidiaries completed in 1994-2009, with target size of at least $25 million, whereas the acquirer did not have a controlling stake in the firm prior to the acquisition but achieved 100% stake after the acquisition.

Dependent Variable Time-to-

Completion Time-to-

Completion

Time-to-Completion

(Escrow Contracts)

Variable

(1) (2) (3)

Escrow Agreement Dummy -20.498*** t-stat (2.68) Instrumented Escrow Agreement Dummy -52.925** t-stat (2.55) Escrow Size -17.746** t-stat (2.51) Indicator for Use of Caps 9.008 18.378 -5.493 t-stat (1.16) (0.74) (0.70) Indicator for Presence of Dominant Shareholder -3.33 -2.85 4.12 t-stat (0.50) (0.17) (0.52) Indicator for Asset Sale 0.816 0.998 -0.41 t-stat (0.09) (0.09) (0.04) Target is Stand-alone Private Firm 0.656 15.815 -1.911 t-stat (0.07) (0.74) (0.15) Target & Acquirer are in the Same Industry -3.438** -0.406 6.240 t-stat (2.60) (1.06) (0.98) Target Interest Coverage (scaled by 1,000) 36.47 40.83 -8.31 t-stat (0.92) (0.9) (1.05) Target Accruals 12.785 25.358 -31.339 t-stat (0.41) (0.40) (0.86) Ln (Target Value) 11.3** 8.581 5.164 t-stat (2.22) (1.23) (1.31) Target Relative Value 3.133 5.414 -5.364 t-stat (0.52) (0.87) (0.67) Indicator for Earn-out Use 2.036 1.049 22.2** t-stat (0.19) (0.10) (2.0) C&I Spread -1.049 -3.004 -4.252 t-stat (0.30) (0.41) (1.08)

Indicator Top Quintile Earnings Volatility Target Industry 7.024** 9.258** -2.241 t-stat (2.46) (2.59) (0.16) Indicator Low Analyst Coverage Target Industry 23.16** 28.464*** 20.93** t-stat (2.32) (2.76) (2.47)

Observations 884 837 469

R-squared 0.16 0.17 0.25

36

Table 6. Panel A. Multivariate Analysis of Acquisition Discount. This table presents multivariate analysis of the acquisition discount. Model (1) offers OLS estimates, while Model (2) documents 2SLS estimates, where we instrument escrow agreement dummy using Model (2) in Table 4. Included but not shown are fixed effects for the year of acquisition’s completion and acquirer’s industry (the industry is defined as a portfolio as in the Fama and French (1992) 49 industry portfolios.) All variables are defined in Table 1. We use robust standard errors. The *** , **, and * indicate significance at the 1%, 5%, and 10% levels, respectively. The sample includes sales of U.S. private companies or subsidiaries completed in 1994-2009, with target size of at least $25 million, whereas the acquirer did not have a controlling stake in the firm prior to the acquisition but achieved 100% stake after the acquisition. The Sargan test (of over-identifying restrictions) tests the joint null hypothesis that the excluded instruments are uncorrelated with the error term in the second stage equation and are hence correctly excluded from the second-stage equation.

Dependent Variable Acquisition Discount

OLS 2SLS

Variables: (1) (2)

 Escrow Agreement Dummy 0.082***

t-stat (2.91)

Instrumented Escrow Agreement Dummy 0.166**

t-stat (2.60)

Indicator for Asset Sale -0.001 0.013

t-stat (0.03) (0.31)

Target is Stand-alone Private Firm 0.084** 0.084*

t-stat (2.12) (1.84)

Target & Acquirer are in the Same Industry -0.061 -0.052

t-stat (1.66) (1.36)

Target Relative Value -0.048** -0.026*

t-stat (2.57) (1.81)

Log(Acquirer Assets) 0.004 0.013

t-stat (0.22) (0.66)

C&I Spread 0.009 0.015

t-stat (0.70) (1.08)

IPO Volume -0.03*** -0.032***

t-stat (4.2) (4.0)

Indicator Top Quintile Earnings Volatility Target Industry -0.108* -0.121*

t-stat (1.73) (1.91) Indicator Low Analyst Coverage Target Industry -0.129* -0.129*

t-stat (1.83) (1.75)

Observations 889 825

R-squared 0.282 0.295

Adj. R-squared 0.20 0.21

Sargan Test (p-value) - 0.23

37

Table 6. Panel B. Multivariate Analysis of Acquisition Discount: Interactions. This table presents multivariate analysis of the acquisition discount, allowing for interactions of the escrow agreement dummy with indicators for top quintile of earnings volatility in the target industry and with indicator for top quintile of analyst coverage in the target industry. Models (1) and (3) present OLS results, while models (2) and (4) offer 2SLS analysis where we instrument escrow agreement dummy using Model (2) in Table 4. Included but not shown are fixed effects for the year of acquisition’s completion and acquirer’s industry (the industry is defined as a portfolio as in the Fama and French (1992) 49 industry portfolios.) All variables are defined in Table 1. We use robust standard errors. The *** , **, and * indicate significance at the 1%, 5%, and 10% levels, respectively. The sample includes sales of U.S. private companies or subsidiaries completed in 1994-2009, with target size of at least $25 million, whereas the acquirer did not have a controlling stake in the firm prior to the acquisition but achieved 100% stake after the acquisition. The Sargan test (of over-identifying restrictions) tests the joint null hypothesis that the excluded instruments are uncorrelated with the error term in the second stage equation and are hence correctly excluded from the second-stage equation. Dependent Variable: Acquisition Discount

OLS 2SLS OLS 2SLS

Variables: (1) (2) (3) (4) Escrow Agreement Dummy 0.074** 0.07** t-stat (2.15) (2.04) Instrumented Escrow Agreement Dummy 0.225** 0.369*** t-stat (2.84) (3.04) Indicator for Top Quintile of Earnings Volatility Target Industry * Escrow Agr. Dummy 0.004 t-stat (1.02) Indicator for Top Quintile of Earnings Volatility Target Industry * Instrumented Escrow Agr. 0.235** t-stat (2.22)

Indicator Low Analyst Coverage Target Industry * Escrow Agr. Dummy 0.020** t-stat (2.20) Indicator Low Analyst Coverage Target Industry * Instrumented Escrow Agr. 0.461** t-stat (2.37) Indicator for Asset Sale -0.069 -0.052 -0.014 0.006 t-stat (1.43) (1.04) (0.36) (0.15) Target is Stand-alone Private Firm 0.16 0.11 0.16 0.11 t-stat (3.39) (2.01) (3.37) (2.08) Target & Acquirer are in the Same Industry -0.067 -0.072 -0.068 -0.075 t-stat (1.62) (1.71) (1.63) (1.77) Target Relative Value -0.039** -0.021 -0.039* -0.020 t-stat (1.93) (1.62) (1.82) (1.43) Log(Acquirer Assets) -0.023 0.001 -0.023 0.002 t-stat (1.16) (0.07) (1.16) (0.09) C&I Spread 0.043 0.051 0.043 0.049 t-stat (0.87) (1.36) (0.85) (1.27) (continued on next page)

38

(continued from previous page) Dependent Variable: Acquisition Discount

OLS 2SLS OLS 2SLS

Variables: (1) (2) (3) (4) IPO Volume -0.024*** -0.028*** -0.024*** -0.033*** t-stat (2.74) (3.02) (2.76) (3.45) Indicator Top Quintile Earnings Volatility Target Industry -0.117* -0.108* -0.11* -0.11* t-stat (1.84) (1.76) (1.70) (1.81)

Indicator Low Analyst Coverage Target Industry -0.182*** -0.206*** -0.195** -0.491*** t-stat (2.70) (2.96) (2.10) (3.66)

Observations 889 825 889 825

R-squared 0.374 0.399 0.374 0.402

Adj. R-squared 0.32 0.344 0.320 0.347

Sargan Test (p-value) - 0.12 - 0.18

39

Table 6. Panel C. Multivariate Analysis of Acquisition Discount: Interactions. This table presents multivariate analysis of the acquisition discount allowing for interactions of escrow agreement dummy with demeaned C&I spread and with demeaned target relative size. Models (1) and (3) present OLS results, while models (2) and (4) offer 2SLS analysis where we instrument escrow agreement dummy using Model (2) in Table 4. Included but not shown are fixed effects for the year of acquisition completion and acquirer’s industry (the industry is defined as a portfolio as in the Fama and French (1992) 49 industry portfolios.) We use robust standard errors. The *** , **, and * indicate significance at the 1%, 5%, and 10% levels, respectively. The sample includes sales of U.S. private companies or subsidiaries completed in 1994-2009, with target size of at least $25 million, whereas the acquirer did not have a controlling stake in the firm prior to the acquisition but achieved 100% stake after the acquisition. The Sargan test (of over-identifying restrictions) tests the joint null hypothesis that the excluded instruments are uncorrelated with the error term in the second stage equation and are hence correctly excluded from the second-stage equation.

Dependent Variable: Acquisition Discount

OLS 2SLS OLS 2SLS

Variables: (1) (2) (3) (4) Escrow Agreement Dummy 0.094** 0.093** t-stat (2.55) (2.53) Instrumented Escrow Agreement Dummy 0.181* 0.171* t-stat (1.91) (1.81) Demeaned C&I Spread*Escrow Agr. Dummy 0.014* t-stat (1.78) Demeaned C&I Spread*Instrumented Escrow Agr. 0.092** t-stat (2.23)

Demeaned Target Relative Value * Escrow Agr. Dummy 0.167** t-stat (2.43) Demeaned Target Relative Value * Instrumented Escrow Agr. Dummy 0.335*** t-stat (2.56) Indicator for Asset Sale -0.001 -0.001 -0.001 0.015 t-stat (0.03) (0.02) (0.01) (0.34) Target is Stand-alone Private Firm 0.083** 0.086* 0.084** 0.083* t-stat (2.08) (1.89) (2.11) (1.79) Target & Acquirer are in the Same Industry -0.062* -0.055 -0.061* -0.051 t-stat (1.69) (1.45) (1.66) (1.38) Demeaned Target Relative Value -0.14** -0.12* -0.235*** -0.284** t-stat (2.45) (1.78) (2.87) (2.43) Log(Acquirer Assets) 0.004 0.014 0.004 0.012 t-stat (0.24) (0.74) (0.22) (0.64) Demeaned C&I Spread 0.003 -0.029 0.009 0.015 t-stat (0.18) (1.09) (0.69) (1.03) (continued on next page)

40

(continued from previous page)

Dependent Variable: Acquisition Discount

OLS 2SLS OLS 2SLS

Variables: (1) (2) (3) (4) IPO Volume -0.029*** -0.029*** -0.029*** -0.031*** t-stat (4.12) (3.56) (4.17) (4.03) Indicator Top Quintile Earnings Volatility Target Industry -0.107* -0.129** -0.109* -0.126** t-stat (1.72) (2.02) (1.76) (1.96)

Indicator Low Analyst Coverage Target Industry -0.129* -0.123* -0.129* -0.126* t-stat (1.83) (1.69) (1.82) (1.72)

Observations 889 825 889 825

R-squared 0.369 0.404 0.369 0.397

Adj. R-squared 0.312 0.349 0.312 0.343

Sargan Test (p-value) - 0.13 - 0.15

41

Table 7. Panel A. Multivariate Analysis of Bidder Announcement Returns. This table presents multivariate analysis of the bidder announcement returns. The dependent variable is the cumulative abnormal announcement return for acquirer starting -1 and ending +1 trading days around the announcement. Models (1) and (3) present OLS results, while models (2) and (4) offer 2SLS analysis where we instrument escrow agreement dummy using Model (2) in Table 4. Included but not shown are fixed effects for the year of acquisition’s completion and acquirer’s industry (the industry is defined as a portfolio as in the Fama and French (1992) 49 industry portfolios.) All variables are defined in Table 1. We use robust standard errors. The *** , **, and * indicate significance at the 1%, 5%, and 10% levels, respectively. The sample includes sales of U.S. private companies or subsidiaries completed in 1994-2009, with target size of at least $25 million, whereas the acquirer did not have a controlling stake in the firm prior to the acquisition but achieved 100% stake after the acquisition. The Sargan test (of over-identifying restrictions) tests the joint null hypothesis that the excluded instruments are uncorrelated with the error term in the second stage equation and are hence correctly excluded from the second-stage equation.

Dependent Variable: CAR -1 to +1

OLS 2SLS

Variables: (1) (2)

Escrow Agreement Dummy 0.013*

t-stat (1.91)

Instrumented Escrow Agreement Dummy 0.035*

t-stat (1.79)

Target is a Stand-alone Private Company 0.002 -0.002

t-stat (0.28) (0.18)

Payment is with Cash Only 0.006 0.006

t-stat (0.84) (0.78)

Payment is with Shares of Acquirer Only 0.038** 0.04**

t-stat (2.33) (2.28)

Indicator for Asset Sale 0.006 0.009

t-stat (0.82) (1.22)

Target & Acquirer are in the Same Industry 0.006* 0.009**

t-stat (1.83) (2.26)

Target Relative Value 0.012 0.016*

t-stat (1.51) (1.75)

Log(Acquirer Assets) -0.004 -0.003

t-stat (1.21) (0.87)

C&I Spread 0.001 0.001

t-stat (0.06) (0.43)

IPO Volume 0.004* 0.003

t-stat (1.77) (1.54)

Indicator Top Quintile Earnings Volatility Target Industry -0.015 -0.016

t-stat (1.28) (1.30)

Indicator Low Analyst Coverage Target Industry -0.006 -0.008*

t-stat (1.51) (1.70)

Observations 844 783

R-squared 0.105 0.113

Adj. R-squared 0.019 0.022

Sargan Test (p-value) - 0.21

42

Table 7. Panel B. Multivariate Analysis of Bidder Announcement Returns: Interactions. This table presents multivariate analysis of the bidder announcement returns allowing for interactions of the escrow agreement dummy with indicators for top quintile of earnings volatility in the target industry and with indicator for top quintile of analyst coverage in the target industry. The dependent variable is the cumulative abnormal announcement return for acquirer starting -1 and ending +1 trading days around the announcement Models (1) and (3) present OLS results, while models (2) and (4) offer 2SLS analysis where we instrument escrow agreement dummy using Model (2) in Table 4. Included but not shown are fixed effects for the year of acquisition completion and acquirer’s industry (the industry is defined as a portfolio as in the Fama and French (1992) 49 industry portfolios.) All variables are defined in Table 1. We use robust standard errors. The *** , **, and * indicate significance at the 1%, 5%, and 10% levels, respectively. The sample includes sales of U.S. private companies or subsidiaries completed in 1994-2009, with target size of at least $25 million, whereas the acquirer did not have a controlling stake in the firm prior to the acquisition but achieved 100% stake after the acquisition. The Sargan test (of over-identifying restrictions) tests the joint null hypothesis that the excluded instruments are uncorrelated with the error term in the second stage equation and are hence correctly excluded from the second-stage equation.

Dependent Variable CAR -1 to +1

OLS 2SLS OLS 2SLS

Variables: (1) (2) (3) (4)

Escrow Agreement Dummy 0.013* 0.016

t-stat (1.75) (1.59)

Instrumented Escrow Agreement Dummy 0.025** 0.039*

t-stat (2.01) (1.81) Indicator Top Quintile Earnings Volatility Target Industry * Escrow Agreement Dummy 0.002**

t-stat (2.12)

Indicator Top Quintile Earnings Volatility Target Industry *Instrumented Escrow Agreement Dummy 0.031*

t-stat (1.81)

Indicator for Low Analyst Coverage Target Industry * Escrow Agreement Dummy 0.013*

t-stat (1.78) Indicator for Low Analyst Coverage Target Industry *Instrumented Escrow Agreement Dummy 0.017*

t-stat (1.83)

Target is a Stand-alone Private Company 0.002 -0.001 0.002 -0.002

t-stat (0.27) (0.15) (0.24) (0.19)

Consideration Offered is Cash Only 0.006 0.005 0.005 0.006

t-stat (0.83) (0.76) (0.80) (0.80)

Consideration Offered is Acquirer Shares Only 0.038** 0.039** 0.038** 0.04**

t-stat (2.32) (2.26) (2.30) (2.27)

Indicator for Asset Sale 0.006 0.008 0.006 0.009

t-stat (0.82) (1.10) (0.82) (1.21)

Target & Acquirer are in the Same Industry 0.006* 0.009** 0.006* 0.009***

t-stat (1.83) (2.63) (1.83) (2.66)

Target Relative Value 0.012 0.016* 0.011 0.016*

t-stat (1.51) (1.79) (1.47) (1.78)

(continued on next page)

43

(continued from previous page)

Dependent Variable CAR -1 to +1

OLS 2SLS OLS 2SLS

Variables: (1) (2) (3) (4)

Log(Acquirer Assets) -0.004 -0.003 -0.004 -0.003

t-stat (1.21) (0.89) (1.22) (0.86)

C&I Spread 0.001 0.001 0.001 0.001

t-stat (1.06) (1.39) (1.09) (1.41)

IPO Volume 0.004* 0.003** 0.004* 0.003**

t-stat (1.77) (2.25) (1.80) (2.27) Indicator Top Quintile Earnings Volatility Target Industry -0.016 -0.012 -0.015 -0.016

t-stat (1.03) (1.48) (1.24) (1.30)

Indicator Low Analyst Coverage Target Industry -0.006 -0.008* -0.002 -0.017*

t-stat (1.52) (1.68) (1.15) (1.68)

Observations 844 783 844 783

R-squared 0.105 0.115 0.105 0.113

Adj. R-squared 0.018 0.024 0.018 0.021

Sargan Test (p-value) - 0.30 - 0.28

44

Table 7. Panel C. Multivariate Analysis of Bidder Announcement Returns: Interactions. This table presents multivariate analysis of the bidder announcement returns allowing for interactions of escrow agreement dummy with demeaned C&I spread and with demeaned target relative size. The dependent variable is the cumulative abnormal announcement return for acquirer starting -1 and ending +1 trading days around the announcement. Models (1) and (3) present OLS results, while models (2) and (4) offer 2SLS analysis where we instrument escrow agreement dummy using Model (2) in Table 4. Included but not shown are fixed effects for the year of acquisition completion and acquirer’s industry (the industry is defined as a portfolio as in the Fama and French (1992) 49 industry portfolios.) All variables are defined in Table 1. We use robust standard errors. The *** , **, and * indicate significance at the 1%, 5%, and 10% levels, respectively. The sample includes sales of U.S. private companies or subsidiaries completed in 1994-2009, with target size of at least $25 million, whereas the acquirer did not have a controlling stake in the firm prior to the acquisition but achieved 100% stake after the acquisition. The Sargan test (of over-identifying restrictions) tests the joint null hypothesis that the excluded instruments are uncorrelated with the error term in the second stage equation and are hence correctly excluded from the second-stage equation.

Dependent Variable: CAR -1 to +1 OLS 2SLS OLS 2SLS

Variables: (1) (2) (3) (4) Escrow Agreement Dummy 0.013* 0.014* t-stat (1.88) (1.91) Instrumented Escrow Agreement Dummy 0.037* 0.038* t-stat (1.79) (1.84) Demeaned C&I Spread * Escrow Agr. Dummy 0.003** t-stat (1.96) Demeaned C&I Spread * Instrumented Escrow Agr. 0.005* t-stat (1.77) Demeaned Relative Size * Escrow Agr. Dummy 0.009** t-stat (2.61) Demeaned Relative Size * Instrumented Escrow Agr. 0.005** t-stat (2.36) Target is a Stand-alone Private Company (not subsidiary) 0.002 -0.002 0.002 -0.002 t-stat (0.34) (0.17) (0.30) (0.18) Consideration Offered is Cash Only 0.005 0.005 0.006 0.006 t-stat (0.78) (0.76) (0.91) (0.86) Consideration Offered is Shares Only 0.038** 0.04** 0.039** 0.039** t-stat (2.30) (2.28) (2.35) (2.25) Indicator for Asset Sale 0.006 0.009 0.006 0.009 t-stat (0.82) (1.23) (0.84) (1.19) Target & Acquirer are in the Same Industry 0.006* 0.009** 0.006* 0.009** t-stat (1.82) (2.28) (1.84) (2.30) Demeaned Target Relative Size 0.012 0.016* 0.007* 0.004 t-stat (1.49) (1.76) (1.81) (1.23) (continued on next page)

45

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Dependent Variable: CAR -1 to +1 OLS 2SLS OLS 2SLS

Variables: (1) (2) (3) (4) Log(Acquirer Assets) -0.004 -0.003 -0.004 -0.003 t-stat (1.25) (0.90) (1.21) (0.82) Demeaned C&I Spread 0.002 0.003 0.001 0.001 t-stat (0.62) (0.87) (1.09) (1.39) IPO Volume 0.004* 0.003 0.004* 0.003 t-stat (1.71) (1.28) (1.81) (1.41)

Indicator Top Quintile Earnings Volatility Target Industry -0.015 -0.016 -0.015 -0.016 t-stat (1.28) (1.31) (1.30) (1.31)

Indicator Low Analyst Coverage Target Industry -0.006 -0.008* -0.006 -0.009* t-stat (1.50) (1.70) (1.52) (1.72)

Observations 844 783 844 783

R-squared 0.105 0.113 0.105 0.116

Adj. R-squared 0.019 0.021 0.018 0.025

Sargan Test (p-value) - 0.29 - 0.27