leonidas barbopoulos and dimitris alexakis...mergers and acquisitions (m&as) financed with...
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Agreeing to participate or disagreeing to implement it?
Leonidas Barbopoulos and Dimitris Alexakis
Abstract: We present new evidence on the announcement period returns of a sample of UK
mergers and acquisitions (M&As) financed with earnout (contingent) versus non-earnout (non-
contingent) payments and advised by financial advisors. We show that deals financed with
earnouts in the presence of a financial advisor consulting the acquiror yield the highest
announcement period returns to bidders’ shareholders. Such deals consistently outperform other
earnout financed cases without the involvement of financial advisors, as well as non-earnout deals
regardless of the presence of financial advisors. We argue that this result is mainly due to the
ability of financial advisors to extract profitable opportunities, and where necessary structure the
earnout contract’s terms efficiently, leading to a very optimistic market reaction. Overall, earnout
financing provides a more effective payment method in M&As, particularly when interacting with
the presence of financial advisors, than that of other forms of payment methods.
Keywords: Methods of Payment; Earnout; Mergers and Acquisitions; Financial Advisor;
Announcement Period Returns.
JEL Classification: G34
Preliminary Version
Please Do Not Quote
Please address correspondence to Leonidas Barbopoulos, School of Economics and Finance, University of St
Andrews, The Scores, St Andrews, Fife KY16 9AL, UK. Tel: +44133461955. Email: leonidas.barbopoulos@st-
andrews.ac.uk. Dimitris Alexakis, School of Economics and Finance, University of St Andrews, The Scores, St
Andrews, Fife KY16 9AL, UK. Tel: +44133461955. Email: [email protected].
1. Introduction
There is, by now, an established literature that studies mergers and acquisitions’ (M&As) success
conditional on the choice of method of payment used to finance the deal as well as the
involvement of financial advisors along with its reflection on the excess returns accrued to
merging firms’ shareholders. See for example Myers and Majluf (1984), Travlos (1987), Eckbo,
Giammarino and Henkel (1990), Fuller, Netter and Stegemoller (2002), Kale, Kini and Ryan
(2003), Faccio and Masulis (2005), Eckbo (2009), Bao and Edmans (2011), Golubov, Petmezas
and Travlos (2012). This literature provides convincing evidence that the involvement of skilled
financial advisors and, more specifically, the involvement of top-tier advisors, known for their
ability to identify profitable opportunities and create substantial synergies, interacts with the
payment method in shaping the likelihood of success of the deal and thus the distribution of the
bidding firm’s abnormal returns (Golubov, Petmezas and Travlos, 2012). Extant literature appears
also convincing that earnout financing provides a solution to valuation risk arising in smaller
deals involving mainly unlisted targets and operating in intangible rich sectors (Kohers and Ang,
2000; Barbopoulos and Sudarsanam, 2012). Under the terms of an earnout contract the selling
firm receives additional future payments provided it achieves certain pre-specified performance-
related goals. The earnout payment mechanism often involves two stages. In the first stage, the
payment is delivered to the seller at the time of the deal announcement (in the form of cash, stock,
or mixed payments), while the second (usually in cash) is delivered after a pre-determined period
has elapsed following the deal announcement. Earnout contracts share the risk of possible mis-
valuation between the bidder and the target during the announcement period while they eliminate
moral hazard problems in the post-merger or integration period. Provided that earnouts are
complicated contracts and difficult to be structured, while they also give rise to substantial
monitoring costs in the post-merger period, which can offset the majority of the aforementioned
benefits, the involvement of financial advisor(s) is likely to affect their implementation, improve
the efficiency of their design and estimate its terms more accurately.1 However, we are not
exposed into evidence on whether in deals financed with earnouts, versus non-earnout, the
involvement of financial advisors enhances the likelihood of their success, which ultimately leads
to higher announcement period returns to bidders’ shareholders. In this paper we aim to fill this
void in the literature.
1 Cain, Denis and Denis (2011) provide a thorough discussion on the costs and benefits involved in M&As financed
with earnouts.
Information asymmetry in M&As involving unlisted target firms2 stands as one of the major
sources of valuation risk.3 One way of managing, and in most of the times mitigating this risk is
to make part of the payment contingent upon the future performance of the target firm under
existing management via the utilization of an earnout payment mechanism. Evidence presented in
previous studies shows that earnouts have been used to manage valuation risk in acquisitions of
private targets operating in the hi-tech and service industries (Kohers and Ang, 2000). In such
industries, information asymmetry is high and the value of the firm is often dependent on the
knowledge, skill, creativity, and flair of key personnel. However, the level of complexity
involved when agreeing upon the (threshold) performance goals as well as the size of the deferred
payment and the length of the earnout contract, which are balanced against the current and future
risk exposure of the merging firms, stand as major challenges in earnout financed deals (Cain,
Denis and Denis, 2011).4 Along these lines, skilled financial advisors have been proven to be able
to extract higher synergy gains while negotiating better terms in M&As (Bao and Edmans,
2011).5 Servaes and Zenner (1996) demonstrate that the choice to use a financial advisor is
strongly affected by the complexity of the deal, the type of transaction (takeovers versus
acquisitions of assets), the acquiror acquisition experience and the degree of diversification of the
target firm. As a result, the presence of financial advisors in M&As financed with earnouts is
vital.6
The earnout usage in cases characterized by high valuation risk leads to positive returns
outperforming traditional means of financing, such as cash, stock and mixed ones that are fully
delivered at the announcement time, and mirrors the market’s optimistic perception of such
concentrations. More recent literature confirms that the presence of financial advisors in M&As is
associated with higher short-run gains to bidders while this effect is stronger under top-tier
advisor involvement (Golubov, Petmezas and Travlos, 2012). Therefore, it should be value
2 Faccio and Masulis (2005) show that approximately 90% of UK (and Irish) acquisitions involve unlisted target firms
while Draper and Paudyal (2006) report approximately 87% of the UK acquisitions involved privately held targets.
However, Moeller et al. (2007) show that approximately only 53% of US acquisitions involve unlisted targets. 3 Discussions on the valuation risk of private target M&A can be found in Chang (1998), Fuller et al. (2002), Faccio et
al. (2006) and Officer et al. (2009). 4 Cain, Denis, and Denis (2011) have adderees, via simulations, the complexity involved in ea financed deals while
they provide convincing arguments regarding the size and length of the contracts. 5 Previous literature shows that M&As advisors stand as a very influencing factor affecting the outcome of M&As.
Many aspects of their involvement along with their incentives have been examined in terms of their reputation and top-
tier classification (Bowers and Miller, 1990; Servaes and Zenner, 1996; Kale, Kini and Ryan, 2003; Golubov, Petmezas
and Travlos, 2012) as well as the possible existence of a conflict of interest (Allen, Jagtiani and Peristiani, 2004;
Kolasinski and Kothari, 2008; Bodnaruk, Massa and Simonov, 2009). In a more recent study, Bao and Edmans (2011)
discussed the ‘skilled advice’ hypothesis highlighting that investment banks, acting as advisors, are more capable
of identifying higher synergy gains in target firms and can negotiate better terms. This leads to the
‘investment bank fixed effect’ in bidder announcement returns. 6 Servaes and Zenner (1996) illustrate that the choice to use a financial advisor is positively related to the complexity of
the transaction as is the choice to implement an earnout contract (Kohers and Ang, 2000).
adding in the existing literature to investigate whether the relative outperformance of earnout
financed deals, when compared to non-earnout ones, is due to the ability of the earnout itself to
reduce valuation problems and enhance future synergies or due to the presence of an investment
bank consulting the acquiring firm and influencing the implementation (and structure) of this
payment method, or the association of both. We argue that in complex cases, where synergy gains
are not easily extracted due to information asymmetry problems or difficult to value assets,
financial advisors are likely to propose such instruments in order to combat moral hazard,
enhance the realization of the above-mentioned synergies and hence benefit both parties involved
in the concentration. We test for these effects and provide new evidence in the existing literature.
This paper presents new evidence on announcement period returns using a larger sample,
near exhaustive, of UK M&As financed with various methods of payments (fully delivered at the
announcement period, such as cash, stock, mixed, and contingent such as earnouts) and advised
by M&As financial advisors. We test whether the use of earnouts as a structural payment
mechanism, versus other payments that are delivered fully at the announcement period, increases
the announcement period returns to bidders’ shareholders. As such this paper is the first to
explore the effects of earnout financing on bidders’ short-run returns when M&As financial
advisors are involved.
Using a UK sample of M&As covering the period from 1986 to 2010 we present new
evidence on the determinants of value creation from earnout financed deals. In the presence of
financial advisors, M&As financed with earnouts yield the highest returns to bidders’
shareholders further indicating that the well documented evidence on value creation from deals
financed with earnouts is mainly driven by the presence of financial advisors on the acquiring
side of the deal. We argue that this is the outcome of the interaction between contingent payments
and the involvement of specialised financial advisors, but mainly due to latter’s ability to extract
synergies and thus design such complicated contracts more effectively.
We employ a two stage approach. The first stage comprises a standard univariate analysis of
bidders’ announcement period returns. This involves comparing the risk-adjusted returns of
bidders financing deals using earnouts relative to counterparts using traditional methods of
payment only, such as full-cash (cash), full-stock (stock), and mixed payments (involving only
cash and stock). The second stage of our analysis comprises a multiple regression analysis of the
impact of earnouts on bidders’ announcement period returns, while controlling for the impact of
several transaction- and merging institution-specific features.
The main findings of our analysis indicate that the use of earnouts in M&As involving
financial advisors leads to significantly higher announcement period returns to bidders’
shareholders when compared to earnout deals not involving financial advisors as well as deals
financed with cash, stock or a mixture of cash and stock payments. Earnout interacts with several
transaction- and merging institution-specific characteristics (such as the target firm’s listing
status, the relative size of the transaction), in determining the announcement period returns of
bidders. We show that the higher the size of the earnout contract, as a fraction of the total
transaction value, the lower the announcement period returns accrued to bidders. Overall, the
results presented in this paper suggest that the market reacts favorably to the use of earnout
contracts in M&As involving financial advisors depicting a potential complementarity between
the two.
Our paper contributes to the literature in the following ways. First, this paper is the first to
explore the effects of earnout financing on bidders’ short-run returns when financial advisors are
involved in the valuation process of the deal. This provides the opportunity to incorporate factors
specific to the financial advisor when assessing how the market reacts to M&A announcements.
Second, provided that M&As financed with earnouts and involving financial advisors constitute
cases with additional complexities to the bidding firm regarding the valuation of the target firm
and the planning of the design of the contract, we investigate the announcement period returns to
bidders’ shareholders.
The remainder of the paper is organised as follows. Section 2 examines the incentives
relating to the choice of payment method in M&A transactions, and how such a choice affects
returns to bidding institutions. Section 2 also formulates reviews salient literature and presents
testable hypotheses. Section 3 outlines the methods used to conduct the empirical analysis. This
section also discusses the determinants of bidders’ announcement period returns. Section 4
provides a description of the data employed and discusses the main findings. Finally, Section 5
provides a conclusion.
2. Financial advisor involvement, earnout financing and testable hypotheses
Two streams of M&A literature are combined in this paper. The first deals with the use of
earnouts as a means of financing an acquisition while the second one deals with the role of
financial advisors involved in the acquiring side of the deal.
2.1. Financial advisor involvement
The role of financial advisors and their involvement in corporate takeovers has been
thoroughly examined in the current M&A literature. Bowers and Miller (1990) demonstrate that
the choice of investment banker has wealth implications for the bidding firm’s shareholders by
establishing the “Better Merger” and “Bargaining Power” hypotheses. More specifically, it is
concluded that an investment bank, and especially a top-tier one due to its better expertise, is
able to identify firms with whom an acquisition would result in greater economic benefits.
Nevertheless, it is implied that the market for takeover targets is sufficiently competitive so that
no differential bargaining power between investment banks is observed. Michel, Shaked and
Lee (1991), however, cast doubt upon whether the prestige of a financial advisor affects
acquisition performance by depicting the relative outperformance of deals advised by Drexel
Burnham Lambert, an investment bank from the second most prestigious group.
Within the same context, Servaes and Zenner (1996) investigated the largest takeovers per
year and compared acquisitions completed with and without investment bank advice. They
conclude that transaction costs and, in part, contracting costs and information asymmetries are
related to the choice to hire a financial advisor. More specifically, an investment bank is more
likely to be consulted when the acquisition is more complex, when bidders have less previous
takeover experience as well as when targets operate in an unrelated industry. Considering the
investment bank’s top-tier classification and the announcement period bidder returns, no
significant relationship is identified. On the contrary Kale, Kini and Ryan (2003) report that the
absolute wealth gain as well as the share of the total takeover wealth gain accruing to the bidder
increases as the reputation of the bidder's advisor increases relative to that of the target.
Similarly, Hunter and Jagtiani (2003) indicate that advisor quality and the number of advisors
employed in a given transaction are important in determining the probability of completing a deal
as well as the time required for its completion with top-tier advisors being more efficient.
Recently published studies have shed more light on the influence of financial advisors on
takeover outcomes. In their paper, Bao and Edmans (2011), show that investment banks matter
for takeover outcomes. They establish the “skilled-advice” hypothesis indicating that
investment banks, acting as advisors, are capable of identifying higher synergy gains in
target firms. This consulting superiority of financial advisors results in a significant
investment bank fixed effect in the announcement returns of M&A deals. Within the same
context and contrary to prior studies, Golubov, Petmezas and Travlos (2012), report that top-tier
advisors deliver higher bidder returns than their non top-tier counterparts, but in public
acquisitions only. Their ability to deliver greater announcement period returns is proven to be
sourcing from their reputational exposure in public concentrations along with their larger set of
advisor expertise and capabilities.
Another issue that has been addressed by financial advisor M&A literature relates to the
conflict of interests that may exist between the investment bank and the bidder being consulted by
it. Allen, Jagtiani and Peristiani (2004) address this issue when financial institutions act both
as lenders and advisors of a merging firm. In particular, target firms earn higher abnormal returns
when the target's own bank is hired as merger advisor, consistent with the bank's role as certifier
of the target's value to the acquirer. Within the same context, Kolasinski and Kothari (2008) find
evidence that conflicts of interest arising from mergers and acquisitions relations influence
analysts’ recommendations, corroborating regulators’ and practitioners’ suspicions. Furthermore,
Bodnaruk, Massa and Simonov (2009) study holdings in M&A targets by financial
conglomerates, in which affiliated investment banks advise the bidders, and show that
advisors take positions in the targets before M&A announcements. These stakes are negatively
related to the viability of the deal. Within the same context, Ismail (2009) indicates that
investment banks might have different incentives when they advise on large deals as opposed to
small ones.
Finally, another aspect of the involvement of financial advisors in company takeovers relates
to the fees charged by investment banks when advising merging parties. McLaughlin (1990)
reports an average total fee of 1.29% of transaction value with a remarkable variation,
nevertheless, between comparable deals. Furthermore, it is depicted that in almost 80% of
contracts, the advisory fee is contingent upon the completion of the deal, thus incentivizing the
investment bank to work towards the completion of the deal regardless of potential losses in
synergy gains for the advised merging party. McLaughlin (1992) also demonstrates that bidding
firms using less prestigious financial advisors offer significantly smaller premiums for takeover
targets and enjoy higher announcement period abnormal returns.
Overall, empirical evidence suggests that the presence of financial advisors influences the
outcome of an M&A deal and affects the wealth gains accrued to the bidding firms’ shareholders.
Despite the ambiguity concerning the impact of their reputation as well as the proper alignment of
incentives, investment banks are depicted as skillful experts able to identify synergy gains in
complex deals thus influencing announcement period returns.
2.2. Earnout financing
Information Asymmetry constitutes one of the major issues in Mergers and Acquisitions as it
may lead to an adverse selection effect. In his study, Hansen (1987), demonstrated that
valuation risk, sourced from information asymmetry, can be controlled through the method of
payment used to finance an acquisition. However, none of the payment methods mentioned
above makes the financing of the acquisition conditional upon post-merger performance of
the target firm. In an earnout contract, an acquirer buys the target in two stages. An
upfront payment of a large proportion of the agreed transaction value (in cash, stock or a
mixture of the two) and a relatively smaller performance contingent earnout (usually cash). The
second stage payment is made over a time period varying between three and five years
contingent on the target reaching agreed milestones. Cain et al. (2011) report that the earnout
component can be as high as 33% of the total purchase consideration.
Kohers and Ang (2000) and Cain et al. (2011) for the US as well as Barbopoulos and
Sudarsanam (2011) for the UK, report that earnout deals generate higher returns to acquiring
firms than cash or stock acquisitions. Within the same studies it is pointed out that earnouts are
more likely to be used in acquisitions where targets are more difficult to value (private
companies), there is higher information asymmetry, the target belongs to an unrelated
industry and the target has many intangible assets which are complex to value.
More specifically, Kohers and Ang (2000) illustrate that targets with higher information
asymmetry are suitable for the use of earnout and that this payment method results in
positive event period abnormal returns for the acquiring firm. In their study, Cain et al. (2011)
find that the earnout size is positively related to the uncertainty of target value, the choice of
performance measure and the importance of target manager effort while the earnout length is
negatively related to proxies for the noise in the performance signal. Reuer et al. (2004)
indicate that the likelihood of the use of an earnout contract increases with the uncertainty
faced by the bidding firm concerning the target value. When looking at the effect of earnouts
in cross-border acquisitions, Datar et al. (2001) find that foreign bidders of US targets are less
likely to use earnout than US domestic acquirers. This result is due to differences in
accounting practices and corporate governance techniques between countries. Within the same
context, Mantecon (2009) indicates that the use of earnouts yields positive announcement
returns to domestic bidders while cross-border acquirers do not benefit from the earnout use as
a means of financing a takeover.
Furthermore, Barbopoulos and Sudarsanam (2011) indicate that US bidders enjoy
significant gains from corporate takeovers when they utilize earnouts as an acquisition payment
currency. US bidder gains from cross-border acquisitions appear significantly higher
than gains from domestic acquisitions when bidders employ earnout correctly to finance their
acquisitions. The correct use of earnout in international acquisitions provides a well
calibrated payment technique that deals effectively with the higher level of adverse selection
and moral hazard associated with cross-border acquisitions than with domestic targets. Finally
when examining the valuation effects of mergers of US financial institutions, Barbopoulos and
Wilson (2011) find that bidders enjoy higher announcement period returns when using
earnouts compared to other forms of payment. More specifically, earnout-financed bids
outperform their non-earnout matching counterparts and the higher the size of the earnout
contract, as a fraction of the total transaction value, the higher the announcement period
returns of bidders.
Overall, earnout financing constitutes a payment mechanism that reduces the probability of
overpayment and increases the probability of success during the integration period as part of the
transaction value is dependent on the future performance of the target firm. Despite their
complexity, when properly implemented earnouts are proven to be able to generate greater
announcement period returns outperforming alternative means of payment and offer an intuitive
solution in cases with substantial overpayment risk.
2.3. Testable hypotheses
As mentioned above, earnout contracts do not constitute a simple and easy-to-use method of
payment. They require intense negotiations between bidders and targets in order to agree upon
the performance-related thresholds regarding the second payment. The complexities
regarding the valuation of the target, the uncertainty related to its post-acquisition operating
performance, caused by moral hazard issues, and the avoidance of an adverse selection effect,
related to information asymmetry, render this method of payment appropriate for acquisitions
of targets exposed to the above risks.
Given the high percentage of the earnout component (up to 33% of the total purchase
consideration according to Cain et al. (2011) along with the willingness of target shareholders to
bind themselves to the post-acquisition performance of the merged entity, it becomes
evident through numerous studies that this financing decision is optimal for acquisitions of
difficult to value targets such as unlisted firms, or firms belonging to industries characterized
by high intangible assets (Kohers and Ang, 2000). Therefore, the implementation of an earnout
provision, especially in cases similar to the above that have been proven to be optimal for its use,
results in acquirors experiencing greater gains than their non-earnout counterparts. Consequently,
our first hypothesis is as follows:
H1: Bidders financing M&A bids with an earnout provision yield higher announcement period
returns to their shareholders, compared to returns generated from M&A bids financed with non-
earnout payment methods.
On the other hand, the role of financial advisors involved in the deal has been thoroughly
examined. Nevertheless, certain conflict of interest issues arise, mostly dealing with whether
these consulting firms have the right incentives when advising a concentration (Allen et al. 2004,
Kolasinski et al. 2008, Bodnaruk et al. 2009). Despite the above, investment banks, acting as
financial advisors have been proven to be better able to distinguish synergy gains in potential
targets and have also been shown to be able to generate greater announcement period returns( Bao
and Edmans, 2011).
More specifically, financial advisors have been established to be playing a significant role in
takeover outcomes. The “skilled advice hypothesis” indicates that investment banks consulting
the acquiring firm are better able to identify synergy gains in targets. Subsequently, this
consulting superiority is reflected through the “investment bank fixed effect” in the
announcement period abnormal returns.
Earnouts, as a means of financing an acquisition, have also been proven to be able to extract
synergy gains from difficult to value targets due to the ability of their design to maintain the
target firm’s management. The performance-related thresholds that have been agreed upon in the
contract incentivize the target’s administration towards the realization of those goals which,
ultimately, benefit both parties. It can therefore be the case that financial advisors, due to their
skillful expertise in identifying synergy gains in target firms and implementing the appropriate
instruments to extract them, are better able to notice such opportunities in high valuation risk
firms. Due to the complexities surrounding such deals, sourced from information asymmetry and
moral hazard, an earnout provision is subsequently implemented, as the investment bank realizes
its appropriation for such cases and is skillful enough to design the contract efficiently. Therefore,
our second hypothesis consists of two parts and is as follows:
H2a: Deals involving an earnout provision and a financial advisor consulting the acquiror yield
greater announcement period returns to the bidding firms’ shareholders than deals involving a
financial advisor consulting the acquiror and not involving an earnout payment.
H2b: Deals involving an earnout provision and a financial advisor consulting the acquiror yield
greater announcement period returns to the bidding firms’ shareholders than deals not involving
a financial advisor and also not involving an earnout payment.
Taking into consideration the above, it can be the case that the announcement period
abnormal returns accrued to the bidding firms’ shareholders in earnout-financed concentrations
are influenced by the presence of financial advisors. Therefore, it needs to be addressed whether
the significant outperformance of deals involving this contingent payment method sources from
the earnout itself, or whether it is also related to the presence of an investment bank consulting
the bidder. Earnouts constitute a complex transaction method that requires intense negotiations
and can easily result in a failure or a legal dispute. Therefore, the acquiring firm alone may not
possess the necessary expertise to properly design and implement this payment method in contrast
to the financial advisor. As a result, the market’s reaction reflects both the investment bank fixed
effect and the risk-mitigating properties of an earnout provision. The latter indicate a potential
complementarity between earnouts and financial advisors which leads to greater announcement
period returns. The market acknowledges the investment bank’s expertise and in addition to the
risk hedging properties of earnouts reacts positively as depicted in the acquiring firms’ wealth
gains.
3. Methods
In this sub-section discussed the methodology used to test the aforementioned hypotheses and
derive the main results of the paper. Methods for calculating abnormal returns around M&As
announcements are therefore presented. Subsequently, the univariate and multivariate methods of
analysis are outlined.
3.1. Measurement of abnormal returns
The commonly used method in estimating abnormal returns in response to an event requires long
estimation period returns series that is free from the effect of the event under analysis.
Nevertheless, the current sample is composed of many bids announced by the same acquiring
firm within a small period of time. Therefore, such method cannot be applied. Alternatively, in
line with numerous studies with similar sample characteristics (Fuller et al. 2002, Faccio et al.
2006) the announcement period abnormal returns are estimated using the market-adjusted model
(equation 1):
(1)
Where: ARi,t, is the abnormal return to bidder I on day t, Ri,t is the return on firm/bidder I at day t,
Rm,t is the value-weighted market return index at day t. The announcement period cumulative
excess return is the sum of the abnormal returns in the 5-day window (t-2 to t+2) surrounding the
bid announcement, day t=0, as outlined in equation 2:
∑ (2)
3.2. Univariate and multiple regression analysis
At first, the announcement period abnormal returns of UK acquirers are analyzed by method of
payment used (cash, stock, mixed, and earnout) and target listing status (private, public, and
subsidiary). The analysis is also divided into sub-categories related to the presence of a financial
advisor for the acquiring firm. Subsequently, differentials between the gains to bidders using
cash, stock or mixed payments for different target listing statuses and the gains to bidders using
earnouts are calculated. To assess the comparative performance of different groups of acquirers,
the difference in means is tested using the t-test along with the difference in medians using the
Wilcoxon test.
Subsequently, we further examine the impact of financial advisors in earnout financed
deals on a multivariate framework where the effects of several other factors in shaping the
announcement period bidders’ returns are simultaneously controlled. Extant literature
demonstrates that a number of control variables influence acquirer’s value gains. Such factors
include the method of payment, bidding firm’s age, the relative size of the deal, the target firm’s
listing status, the industry affiliation of the merging firms and the target’s domicile and operating
legal system. Furthermore, this empirical paper includes certain new factors that aim to explain
the bidding firm’s returns. They consist of the existence of a financial advisor, a further
exploration of the listing status of the immediate parent of subsidiary targets, the legal system in
which the target firm operates, and certain key financial ratios of the bidder such as the cash ratio
(total cash and cash equivalent over total assets) and debt ratio (total debt to common equity). In
particular, the following equation is estimated in a nested form:
∑ (3)
Where: the intercept, α, accounts for the abnormal returns accrued to bidders after accounting for
the effects of all the explanatory variables Xi. The dependent variable, CAR, is the five-day
announcement period cumulative abnormal return of acquirers. The vector of explanatory
variables, X, includes a number of factors that are known to affect bidders’ gains. Such factors
consist of:
Earnout as a method of payment (EA): Previous research indicates that acquisitions of
difficult to value targets, such as private targets operate in the high-tech industry generate greater
bidder announcement period returns when financed with an earnout component (Kohers and Ang,
2000). Therefore to account for the potential implications of the occurrence of an earnout on
bidder gains, a variable taking the value of one when there exists an earnout and zero otherwise is
included in equation (3).
Bidder’s age (BAGE): Information asymmetry between the merging firms influences
heavily the announcement period returns accrued to bidders’ shareholders. Draper and Paudyal
(2008) and Zhang (2006) suggest that investors tend to have more information on firms with
longer trading history which results in lower information asymmetry. Therefore the age of the
acquirer (measured by the log of number of days between the announcement day and the first
record of the company in Datastream) is included in equation (3).
Relative size of the deal (LRS): Current literature (Fuller et al. 2002) depicts that the
bidders’ gains are positively related to the relative size of the bid (measured as the log of the deal
value over the market value of the acquirer). Hence this variable is included in equation (3).
Diversification (CROSSIND): Extant literature (Barbopoulos et al. 2012) shows that if
target and bidder belong to the same industrial sector, the integration of the two firms should be
easier and the synergy gains higher. On the other hand, firms acquiring targets operating in
unrelated sectors may also gain from diversification. Therefore to control for the potential effect
of corporate diversification a dummy variable taking the value of one for cross-industry bids (i.e.
target and acquirer do not have the same 2-digit SIC code) and zero otherwise is included in
equation (3).
Target’s domicile (CROSSB): Domestic and international deals have been proven to be
affecting the bidding firm’s value gains (Conn et al. 2005). Domestic acquisitions can be
perceived as less risky than crossborder acquisitions as there is less information asymmetry about
the target firm, especially in those cases where it is a listed firm. Therefore, in order to control for
the effect of international deals and how they affect bidder returns a dummy variable that equals
one when bidder and target reside in different countries and zero otherwise is included in equation
(3).
Target’s operating legal system: Current literature (Barbopoulos and Paudyal, 2012)
depicts that the target firm’s operating legal system interacts with the bidding firm’s
announcement period returns as the legal tradition of the target's domicile interacts with target's
status and method of payment in shaping the net gains of acquirers. Therefore dummy variables
that equal one when the acquired company’s legal system is the Common Law or the Civil Law
and zero otherwise are introduced in equation (3).
Additional indicator variables: Certain new factors are introduced in this paper that aim
to explain the wealth effects arising to bidding firms’ shareholders. The main variable under
examination consists of the advisors involved in the deal and, more specifically, financial
advisors. Therefore a dummy variable for the existence of financial (AFAE) advisors is included.
Furthermore, the target’s listing status has been proven by empirical studies to be influencing the
announcement period acquirer returns. Dummy variables are hence, created for those cases where
the acquired firm is private (PRIVATE) or subsidiary. Finally, key financial ratios of the
acquiring firm (such as the ratio of total cash and cash equivalents to its total assets,
CASH_RATIO, and the ratio of total debt to its common equity, DEBT) signal information
about the bidder’s financial status and probability of default. Therefore, they are included in
equation (3). A more detailed presentation of all parameters used in this paper is given in the
Table 1.
4. Data and Results
This section presents the data and offers a discussion of the main findings of our empirical
investigation. Section 4.1 outlines the sample of M&As transactions and presents descriptive
statistics. Section 4.2 discusses the results from the univariate analysis. Finally in section 4.3 we
present and discuss the results from the multivariate cross-sectional analysis.
4.1. The sample
The sample consists of takeover bids announced by UK public firms between 01/01/1986
and 31/12/2010 and recorded by the Security Data Corporation (SDC). SDC records 31,658 cases
of M&As bids involving UK acquirers within the sample period. In order for a bid to remain in
the sample, it must meet the following criteria: first, the acquirer is a UK public company listed
in the FTSE and has a market value of at least $1 million, measured four weeks prior to the
announcement of the bid. To avoid the insignificant effects of very small deals, the transaction
value needs to be at least $1 million. To ensure that the acquirer enjoys control of the target, only
acquisitions of at least 50 percent of target equity are included in the sample. Targets of all
listings (listed, private and subsidiary) and domicile (UK or non-UK) are included in the
sample. To avoid the confounding effects of multiple bids, bids announced within 5-days
surrounding another bid by the same bidder are excluded. Furthermore, the daily stock price
and market value of the acquirer need to be available from Datastream. Buybacks and
repurchases are excluded from the sample. Cases where either bidder or target firms belong to
regulated industries (Healthcare, Financials, Energy and Power) or to the government are
excluded from the sample. Finally, considering the method of financing the acquisition, the
percentage of unknown, provided by SDC, must be less than 100% so that the sum of cash, stock
and other payments equals 100%. The above criteria are satisfied by 6,432 bids and remain in the
sample. 1,505 bids comprise earnout contracts. 2.053 of these deals involve financial advisors
while only 331 of those belong in the earnout financed deals.
4.2. Sample Characteristics
4.2.1. All Acquisitions
Table 2 depicts the frequency of acquisitions in the UK takeover market according to the acquired
firm’s location and industry as well as the method of payment used, the presence of a financial
advisor for either bidder or target and the acquired firm’s listing status. Earnout financed
acquisitions constitute 23.4% of the sample. The remaining 76.6% involves cash, stock or mixed
payments. Nevertheless, the use of earnouts has increased dramatically since the mid 80’s
reaching 31.73% and 33.72% of total M&As activities in the years 2006 and 2007 respectively
as compared to just 14.05% in 1987. Cash along with mixed payments constitute the two
dominating methods of payment (accounting for 44.37% and 48.94% respectively) followed by
stock which accounts for just 6.69%. A reason for the relatively low percentage of
acquisitions fully financed with stock is the severe regulatory regime in the UK which
generally prohibits acquisitions fully financed with equity.
Almost 32% of the sample deals include a financial advisor for the acquiring firm and
27.16% a financial advisor for the target firm. The above indicate that one third of all acquisitions
is accompanied by a financial advisor rendering its influence substantial in takeover outcomes.
Furthermore 331 deals are characterized by the simultaneous presence of both an earnout and a
financial advisor.
Cross-border acquisitions, i.e. UK bidders acquiring non-UK targets appear
relatively frequently (28.81% of sample) while acquisitions of non-listed targets, i.e. acquisitions
of private and subsidiary targets, seem to be dominating the sample accounting for
90.58% (59.56% and 31.02% respectively). More specifically, 9.2% of all acquisitions
consist of subsidiary targets with a private immediate parent, 13.85% consist of subsidiary
targets with a public immediate parent and 7.85% consist of subsidiary targets with a
subsidiary immediate parent. The remaining 9.42% consists of acquisitions of public firms.
Cross-industry concentrations represent 49.32% of the sample while 49.32% of the deals
involve acquisitions of targets belonging to industries characterized by high intangible assets (i.e.
High-Tec, Consumer Products and Services and Media and Entertainment).
4.2.2. Acquisitions involving earnouts
In this section the sample is restricted to only those deals involving an earnout payment. In
Table 3, deals financed with earnouts are dominated by acquisitions of private targets
accounting for 85.12% and followed by acquisitions of subsidiary targets representing
13.75%. Furthermore, subsidiary targets whose immediate parent is a private firm account
for 5.78%, subsidiary targets whose immediate parent is a subsidiary firm account for 2.26%
and subsidiary targets whose immediate parent is a public firm account for 5.71%.
Acquisitions of public targets, very rarely involve an earnout payment as they account for
merely 1.13%. Cross-border acquisitions represent 20.93% of earnouts indicating their
appropriation for domestic cases (Datar et al. 2001). Considering the target’s industry
classification, almost 50% of earnout financed deals involve targets belonging to a different
industry than the acquiring firm while almost 60% of acquired companies belong to industries
characterized by high intangible assets.
Considering the advisors involved in the deals, almost 22% of acquirers are being
advised by a financial advisor while 25.65% are being advised by a legal advisor Finally,
considering target advisors, almost 17% of targets are being consulted by investment banks. The
use of financial advisors seems to be following the general trend of earnout use. As in the case of
earnout occurrences, the presence of a financial advisor for the acquiring firm increases
dramatically during the ten years between 1991 and 2001 and subsequently drops, in the
aftermath of the dot-com bubble. Subsequently, it once again increases during the years 2004-
2007 only to start dropping again during the credit crunch crisis of 2008.
4.2.3. Deal Characteristics
Table 3 presents mean and median deal values according to target listing status, method of
payment, industry, target firm’s domicile and financial advisor presence. The average deal value
of all deals is around $134 million with a median value of almost $11 million. Deals involving
public targets exhibit the highest average and median deal values ($920 million and $83.45
million respectively) followed by deals involving subsidiary and private targets ($102.4 million
and $13.8 million and $26.4 million and $7.95 million respectively). Earnout financed
acquisitions exhibit average and median deal values of $22.5 million and $8.85 million
respectively which are the lowest when compared to the alternative means of payment (cash,
stock or mixed). Nevertheless, this is somewhat expected as acquisitions financed with an earnout
provision mostly involve small unlisted targets which render the transaction value relatively
small.
Considering the financial advisors involved in the deal process, it is shown that deals
including a financial advisor are much larger in size than those which do not. More specifically,
the presence of a financial advisor for the acquiring firm increases the average deal value from
$21.22 million to $375 million while the median transaction value also increases from $7 million
to $36.17 million. When there exists a financial advisor for the acquiring firm along with an
earnout provision the average and median deal value is greater than when there exists an earnout
provision without an advisor reaching $51.19 million and $17.13 million respectively. The same
observation persists across all different target listing statuses indicating that earnout deals which
include a financial advisor for the bidder are much larger in size than earnout deals without one.
Nevertheless these values are significantly smaller than when there exists a financial advisor for
the bidder without the presence of an earnout. In those cases the average and median deal values
climb to $437.32 million and $43.65 million respectively.
Considering the target firm’s domicile, cross-border acquisitions exhibit much larger
average and median deal values ($301.63 million and $18.88 million) than domestic ones ($66.39
million and $9 million). More specifically, cross-border acquisitions of public targets exhibit an
average deal value of $2.1 billion and median value of $190.16 million. Acquisitions involving
targets in the same industry exhibit a higher average deal value than when the target firm belongs
to a different industry ($187.57 million and $79.27 million respectively). Nevertheless this
difference is not as substantial when looking at the median values ($11.68 million and $10.43
million respectively). Finally acquisitions of firms that belong to a high intangible assets industry
are characterized by lower average and median deal values than crossindustry or same industry
acquisitions ($67.1 million and $10.2 million respectively).
The above simplistic analysis demonstrates that the vast majority of earnout financed
M&As deals is composed of domestic acquisitions of unlisted targets belonging to an industry
characterized by high intangible assets, and hence valuation risk, while almost 22% of them are
accompanied by an investment bank consulting the acquirer. Furthermore, earnout deals are much
smaller in size than non-earnout ones. Nevertheless, when there exists an investment bank
consulting the acquirer, earnout financed acquisitions increase significantly in size across all
different target listed statuses. The above effect of the presence of a financial advisor on the
bidding side of the deal is also present in non-earnout acquisitions verifying the conclusion that
deals including financial advisors are generally larger in size.
4.3. Univariate analysis of announcement period returns
Table 5 reports the findings of our univariate analysis of announcement period returns. Results
are presented according to method of payment used and target listing status. The analysis is also
divided into sub-categories related to the presence of a financial advisor for the acquiring firm.
Subsequently, differentials between the gains to bidders using cash, stock or mixed payments for
different target listed statuses and the gains to bidders using earnouts are calculated as well as the
gains to bidders using a financial advisor and the gains to acquirors not using one.
Panel A reports the mean and median 5-day announcement period returns for all
acquisitions. Earnout financed deals are depicted to be outperforming alternative means of
payment averaging 1.70% with a median return of 0.64% which is also the highest among other
financing methods (consistent with earlier studies such as Kohers and Ang, 2000; Barbopoulos
and Sudarsanam, 2012). Earnout deals involving unlisted targets, which are depicted by literature
to be optimal for their use, illustrate an average and median return of 1.70% and 0.63%
respectively. When compared to alternative means of payment earnout financed deals involving
such targets only outperform cash deals with just the average difference being significant at
1.00%. Among acquisitions involving earnouts, deals involving a subsidiary target with a private
immediate parent demonstrate the greatest average and median abnormal returns (2.83% and
1.22% respectively both significant at 1%). This is somewhat expected as bidders acquiring such
firms are exposed to greater valuation risk due to the complicated status of the target. Therefore
the implementation of an earnout contract should be regarded as more appropriate thus resulting
in a positive market reaction.
In order to assess the impact of financial advisors specifically, Panel B restricts the
sample to only those cases where there exists a financial advisor for the acquiring firm. Earnout
financed deals still depict the greatest average and median abnormal returns (2.48% and 1.18%
respectively, both significant at 1%) which are also much larger than those presented in panel A.
Furthermore, under the presence of a financial advisor bids including this contingent payment
method outperform those that do not by 1%, significant at 5%, while the median difference is
0.54% also significant at 5%. Furthermore, deals involving an earnout provision and unlisted
targets now depict much larger average and median returns than before (2.57% and 1.27%
respectively, both significant at 1%). Finally, once again, deals involving subsidiary targets with a
private immediate parent yield the greatest returns among the earnout group (5.63% and 3.98%
respectively, both significant at 1%) and are also much larger than those in panel A. The above
results indicate that the presence of financial advisors significantly increases the wealth gains
accrued to the bidding firms’ shareholders in earnout financed acquisitions. Especially in those
cases where earnout literature depicts their use to be optimal, i.e. unlisted targets, the average and
median returns corresponding to acquiring firms’ equity owners are significantly increased.
In order to better assess the influence of financial advisors, in Panel C, the sample is
restricted to those cases where there does not exist a financial advisor consulting the bidding firm.
This separation should give us a first glimpse of the impact that investment banks have on
bidders’ wealth gains in earnout financed concentrations. Earnout financed acquisitions now
depict the smallest average and median returns between all Panels (1.48% and 0.53%
respectively, both significant at 1%). When compared to non earnout financed acquisitions, deals
involving this contingent payment are depicted to be outperforming only in terms of average
returns by 0.45%, significant at 5%. Interestingly, and in contrast to the case where there exists a
financial advisor in Panel B, earnout financed deals when compared to stock financed deals do
not exhibit a significant outperformance. As shown by Hansen (1987), stock financing offers
some risk-mitigating advantages, especially in cases with asymmetric information that favor the
acquiring firms’ shareholders. Under the presence of a financial advisor, a significant
outperformance of earnout financed bids is observed whereas when there does not exist an
investment bank advising the acquiring firm the aforementioned outperformance becomes
insignificant. Furthermore, acquisitions of subsidiary targets with a private immediate parent
financed with an earnout now exhibit much lower average and median returns (1.94% significant
at 5% and 0.69% significant at 1% respectively).
Finally, Panel D exhibits the differences in portfolio returns between cases that include a
financial advisor and those that do not. In earnout financed deals, the presence of an investment
bank yields greater mean and median announcement returns by 1% significant at 5% and 0.66%
also significant at 5% respectively. In non earnout acquisitions the presence of a financial advisor
only increases the mean return by 0.44%, significant at 5%, while the median increase is rendered
insignificant. Acquisitions, characterized by literature to be optimal for earnout use, such as those
involving unlisted targets, are also benefited by the presence of a financial advisor in terms of the
wealth gains accrued to the bidding firms’ shareholders. More specifically, the existence of an
investment bank translates to a 1.11% increase in average bidder gains, significant at 1%, and a
0.77% increase in median acquiror returns, significant at 5%. Once again subsidiary targets with a
private immediate parent as well as subsidiary targets with unlisted immediate parents which,
intuitively alone, constitute cases with substantial valuation and overpayment risk are presented to
be benefited the most of financial advisor presence. The existence of an investment bank yields
an excess average return of 3.69%, significant at 5%, and an excess median return of 3.29%,
significant at 1% in the case of private immediate parenthood as well as an excess average return
of 4%, significant at 1%, and an excess median return of 3.48% in the case of unlisted immediate
parenthood.
The above indicate that the presence of a financial advisor on the acquiring side of the
deal significantly benefits the wealth gains accrued to the bidding firms’ shareholders in earnout
financed acquisitions. Financial advisor presence translates to an excess return of 1% in deals
involving this contingent payment method. More specifically, in cases characterized by literature
to be optimal for the use of earnouts, such as deals involving unlisted targets (Kohers and Ang,
2000), the existence of an investment bank along with the occurrence of an earnout payment
significantly increase bidders’ abnormal returns. It is of particular importance to explain this
effect.
Recent literature on financial advisor involvement in M&As transactions depicts their
significant influence on deal outcome and bidder value gains. The ‘skilled advice’ hypothesis,
established by Bao and Edmans (2011), indicates that investment banks, acting as financial
advisors, are more capable of identifying synergy gains in targets and that this superiority of
theirs is reflected through the ‘investment bank fixed effect’ in the announcement period returns.
It can be argued, therefore, that in cases where there exists a substantial synergy gain but cannot
be easily extracted, due to high information asymmetry, financial advisors possess the necessary
skills which enable them to realize the appropriation of an earnout contract. Due to their skillful
expertise, the complex process of designing the contract and negotiating its terms is managed
successfully and the earnout is implemented. The market’s perception of the above process is
positive leading to a substantial wealth gain to the bidding firm’s shareholders. The latter can also
be verified by cases involving unlisted targets and, more specifically, subsidiary targets with an
unlisted immediate parent. Such cases depict a substantial valuation risk, due to the complicated
listing status of the target firm. The presence of a financial advisor along with an earnout
provision translated to a 4% increase in bidders’ stock gains and can be perceived as the
“investment bank fixed effect” complementing the already positive effect of earnout choice on
announcement period equity returns.
Another aspect of financial advisor involvement that can explain the positive effect of
their presence in earnout financed acquisitions relates to McLaughlin (1990, 1992) and his
findings regarding the prestige and the incentives of investment banks towards deal completion. It
is illustrated that in almost 80% of advisory contracts, the fee is contingent upon deal completion
incentivizing the investment bank to focus on completing the deal, increasing the risk of
overpayment, at the expense of synergy gains. In light of the above, he also demonstrates that
firms using less prestigious financial advisors offer significantly smaller premiums for takeover
targets and enjoy higher announcement period returns. The choice to use an earnout in a complex
case under the presence of a financial advisor can be perceived as signaling to the market that the
financial advisor is indeed aiming towards the realization of synergy gains between the merging
parties. Furthermore, as mentioned above, deals involving earnouts are smaller in average and
median transaction value than those that do not and, consequently, do not involve many top-tier
financial advisors which focus mainly on large concentrations. Therefore, along with their skillful
expertise discussed earlier, financial advisors, when involved in earnout financed deals are also
likely to signal to the market that their aims consist of the realization of synergy gains and the
reduction of overpayment risk and not deal completion which can potentially damage their
clients. The market’s perception of the above is positive leading to a substantial excess wealth
gain.
4.4. Multiple regression analysis of announcement period returns
Table 6 reports the findings of our multivariate analysis which means to control for several
factors simultaneously shaping bidders’ returns in the announcement period. In order to deal with
heteroscedasticity in the models, the Ordinary Least Squares estimation outputs are
calculated and standard errors are adjusted using the White heteroscedasticity consistent
standard errors. The results obtained from the cross-section analysis support the findings of the
univariate analysis and also further corroborate the significant impact of the presence of financial
advisors in earnout financed deals.
Models 1-4 illustrate the results of the analysis for the whole sample while, in Models 5
and 6 the sample is restricted to only earnout financed acquisitions. Model 1 depicts the effect of
certain established variables in earnout literature on bidders’ announcement period returns
without taking into consideration the effect of financial advisors. The earnout presence has an
insignificant effect. Nevertheless, deals involving targets operating in industries concentrated in
intangible assets positively influence the market’s reaction as do cases involving unlisted targets
that constitute the vast majority of M&As deals in the UK. Cross-border and cross-industry
acquisitions have an insignificant effect as does the legal system in which the target firms operate.
This is somewhat expected as the vast majority of targets operate in a Common Law legal
framework. The bidding firm’s age has an insignificant effect illustrating the uniqueness of
merger announcements regardless of the life cycle of the firm in contrast to its market value
which has a negative and significant effect depicting that the larger the acquiring firm’s equity
value the smaller the impact of the deal on the bidding firm’s stock. The size of the transaction
positively influences announcement period bidder returns, illustrating that larger deals have a
more positive impact on acquirors’ wealth gains, as does the bidding firm’s cash ratio. The latter,
as a substantial indicator of the firm’s liquidity, strongly influences the market’s assessment of an
acquisition depicting that acquiring firms which are highly liquid enjoy greater announcement
period returns.
Considering the effect of financial advisor involvement on bidders’ gains, it can be seen
in Model 2 that the presence of an investment bank on the acquiring side of the deal has a positive
and significant impact on acquirors’ announcement period returns. This finding relates to current
literature pointing out the positive effect of financial advisor involvement on bidders’ wealth
gains. In order to address a potential endogeneity issue regarding the effect of financial advisors,
the variable corresponding to the deal value was not included in Models 2-6 due to evidence in
current literature that relates the size of the transaction to the financial advisors involved in the
deal process. Furthermore, it can be seen in Models 3 and 4 that the simultaneous presence of an
earnout provision along with a financial advisor as well as the simultaneous presence of an
earnout provision, a financial advisor and an unlisted target positively and significantly influence
bidders’ abnormal returns in contrast to just the presence of an earnout which has a positive but
insignificant effect. The latter provide evidence that in cases involving an investment bank
advising the bidder, the implementation of an earnout and more specifically, the implementation
of an earnout provision along with a high information asymmetry target lead to significantly
positive market reaction. This can be perceived as providing evidence on the complementarity of
earnout contracts and financial advisors illustrating the impact of the “skilled advice” hypothesis
on bidders’ wealth gains.
In order to better assess the influence of the presence of financial advisors on bidders’
announcement period returns, in Models 5 and 6 the sample is restricted to only earnout financed
acquisitions. Furthermore, an additional variable introduced consists of the relative earnout size
compared to the transaction value of the deal. As can be seen in both regression outputs, the
relative earnout size imposes a negative and significant effect on bidders’ value gains. This is
somewhat expected as the latter has been proven to be positively linked to the valuation
uncertainty of the deal (Cain et al. 2011). Therefore, as it increases in size it can be perceived as
signaling to the market the complex character of the concentration thus negatively influencing the
market’s reaction. Considering the impact of financial advisors in earnout financed acquisitions,
as can be seen in Model 5, the presence of an investment bank leads to a positive and significant
effect on acquirors’ announcement period returns as does the simultaneous presence of a financial
advisor and an unlisted target firm in Model 6. The above findings illustrate the significantly
positive effect of investment bank presence in earnout financed acquisitions as well as the
market’s positive assessment of their involvement in complex cases with substantial valuation
risk.
Overall, the above analysis verifies the results of the univariate analysis and depicts the
significance of financial advisor presence in earnout financed deals. Financial advisors can be
perceived as being better able to distinguish when the implementation of an earnout contract is
suitable while also being skillful enough to design this complex payment mechanism efficiently.
The market’s perception of the above process is very optimistic yielding greater gains to the
bidding firms’ shareholders as illustrated in both a univariate and a multivariate context.
5. Conclusion
This paper presents new evidence on the announcement period returns of a large sample of UK
M&As involving deals financed with alternative methods of payment (such as cash, stock, mixed
and earnout) and either advised by financial advisors or not. A univariate analysis of bidders’
announcement period returns compared the wealth gains accrued to acquirors financing bids
using earnouts to counterparts using traditional methods of payment. Similarly, a comparison of
announcement period performance of deals advised by investment banks across all payment
methods, but mainly when an earnout is utilized, was also conducted. The results of the above
analysis suggest that bidders enjoy greater announcement period returns when, (a) financing deals
with an earnout provision, (b) there exists a financial advisor consulting them, and (c) when the
latter occur simultaneously.
A multiple regression analysis assesses the interaction effect of earnout involvement,
with or without the involvement of financial advisors on bidders’ announcement period returns,
while controlling for other transaction- and merging institution-specific characteristics. The main
findings of the multiple regression analysis suggest that the interaction of earnout financing with
the presence of financial advisors yields the highest gains to bidders’ shareholders. The results
also suggest that bidders’ returns are sensitive to several other explanatory variables known as
important determinants in shaping bidders’ returns.
Overall, our results suggest that the interaction between earnout financing and financial
advisor presence in M&As involving mainly unlisted target firms provides a more effective
valuation risk treatment. We argue that this interaction leads to a significant reduction of adverse
selection and moral hazard issues arising from asymmetric information problems between the
merging partners and thus increase the odds of M&As success. The above can be perceived as
providing evidence for a potential complementarity between earnouts and financial advisors
which is priced as good news in the marked.
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Table 1: Variable Definitions
The table defines the variables used in the empirical analysis, and indicates the data source used. SDC denotes
Thomson-Reuters SDC M&A database. With a dummy variable, a sample observation without the value of 1 has the
value of 0. Age, MV, DV, EAV, RS and Debt are log transformed in subsequent regressions.
Variable
Type/Name Description
Data
Source
All Refers to the entire sample analysed in this paper. SDC
Age Number of days between day the bidder is first recorded on
Datastream and bid’s announcement day. Datastream
Market Value
(MV)
Bidder’s market value of equity at four weeks prior to bid’s
announcement, in millions dollars. Datastream
Deal Value (DV) Bid’s transaction value, in millions dollars. SDC
Earnout Value
(EAV)
Value of earnout contract, in millions dollars (proxy for size of
earnout). SDC
Relative Size
(RS) Ratio of DV to MV.
SDC &
Datastream
Relative earnout
size (RES) Ratio of EAV to DV SDC
Crossborder
(CROSSB)
Dummy = 1 with a UK bidder and non-UK target, and = 0
when both bidder and target are UK institutions (= Domestic). SDC
Domestic (DOM) Dummy = 1 with a UK bidder and a UK target, and = 0 when
target is not a UK company. SDC
Crossindustry
(CROSSIND)
Dummy = 1 when bidder and target do not share the same two-
digit SIC code and = 0 otherwise. SDC
Same Industry
(SAME)
Dummy = 1 when bidder and target share the same two-digit
SIC code and = 0 otherwise. SDC
Intangible
(INTANG)
Dummy = 1 when target belongs to a high intangible assets
industry (Media and Entertainment, Consumer Products and
Services, High Technology) and = 0 otherwise.
SDC
Cash Dummy = 1 when payment is 100% cash. SDC
Stock Dummy = 1 when payment is 100% stock exchange. SDC
Mixed Dummy = 1 when payment is mixture of cash, stock, and other
methods of payment excluding earnout. SDC
Earnout (EA)
Dummy = 1 when payment includes earnout in addition to
cash, stock, or mixed, and = 0 otherwise (= Non-Earnout)
(NEA).
SDC
Non-Earnout
(NEA)
Dummy = 1 with full-cash, or full-stock, or mixed payment
without EA, and = 0 when EA is included. SDC
Private (PRIV) Dummy = 1 if target is private, and = 0 otherwise. SDC
Public (PBL) Dummy = 1 if target is publicly listed, and = 0 otherwise. SDC
Subsidiary (SUB) Dummy = 1 if target is a subsidiary institution, and = 0
otherwise. SDC
Subsidiary with
private immediate
parent (SUBPRI)
Dummy = 1 if target is a subsidiary institution with a private
immediate parent, and = 0 otherwise. SDC
Subsidiary with
public immediate
parent (SUBPUB)
Dummy = 1 if target is a subsidiary company with a public
immediate parent, and = 0 otherwise. SDC
Subsidiary with
subsidiary
immediate parent
(SUBSUB)
Dummy = 1 if target is a subsidiary company with a subsidiary
immediate parent, and = 0 otherwise. SDC
Subsidiary with
unlisted
immediate parent
(SUBUNLI)
Dummy = 1 if target is a subsidiary company with an unlisted
immediate parent (private or subsidiary), and = 0 otherwise. SDC
Unlisted (UNLI) Dummy = 1 if target is not a listed firm, and = 0 otherwise. SDC
AFAE Dummy = 1 when there exists a financial advisor for the
bidder, and = 0 otherwise. SDC
NAFAE Dummy = 1 when there does not exist a financial advisor for
the bidder, and = 0 otherwise. SDC
TFAE Dummy = 1 when there exists a financial advisor for the target,
and = 0 otherwise. SDC
ALAE Dummy = 1 when there exists a legal advisor for the bidder,
and = 0 otherwise. SDC
TLAE Dummy =1 when there exists a legal advisor for the target, and
= 0 otherwise. SDC
EA_AFAE
Dummy = 1 when there exists a financial advisor for the
bidder and the transaction includes an earnout provision, and =
0 otherwise.
SDC
EA_AFAE_UNLI
Dummy = 1 when there exists a financial advisor for the
bidder, the transaction includes an earnout provision and the
target is unlisted, and = 0 otherwise.
SDC
NEA_AFAE
Dummy = 1 when there exists a financial advisor for the
bidder and the transaction does not include an earnout
provision, and = 0 otherwise.
SDC
Experience Dummy = 1 when the bidder has used and earnout provision at
any time in the past, and =0 otherwise. SDC
Common
Dummy = 1 when the acquisition is crossborder and the
target's nation follows the English Common Law legal system,
and = 0 otherwise.
SDC
Cash_ratio Bidder's total cash and cash equivalents to its total assets Datastream
Debt Bidder's total debt to common equity. Datastream
Table 2: M&A Activity by Location, Industry, Method of Payment and Advisor Presence
The table presents the UK M&A activity according to the target institution’s domicile (Domestic versus Crossborder), industry (Same Industry versus Crossindustry and
Intangible), currency of financing (earnout, and non-earnout which includes cash, stock and mixed payments), advisor presence (afae versus tfae and alae versus tlae as well as
ea_afae versus nea_afae) and target listed status (private, public, subsidiary, subpub, subpri and subsub). Table 1 provides the definitions of variables.
Year ALL DOM CROSSB SAME CROSSIND INTANG EA NEA CASH STOCK MIXED AFAE EA_AFAE NEA_AFAE PRIV PBL DUB SUBPUB SUBPRI SUBSUB
1986 39 25 14 19 20 10 0 39 21 11 7 24 0 24 19 11 9 5 1 3
1987 121 98 23 53 68 33 17 104 50 30 41 47 1 46 60 30 31 16 6 9
1988 286 224 62 108 178 93 81 205 128 23 135 62 13 49 175 43 68 37 14 17 1989 351 262 89 146 205 121 76 275 173 31 147 89 13 76 185 42 123 68 31 24
1990 215 159 56 91 124 70 43 172 110 15 90 76 9 67 97 20 98 53 22 23
1991 138 115 23 56 82 37 28 110 57 16 65 54 6 48 58 20 60 32 16 12 1992 145 113 32 52 93 37 22 123 64 11 70 45 4 41 69 5 71 30 17 24
1993 217 168 49 85 132 62 31 186 97 16 104 81 11 70 101 15 101 45 25 31
1994 272 211 61 130 142 83 42 230 124 24 124 88 12 76 148 20 104 44 29 31 1995 288 209 79 111 177 100 67 221 114 17 157 80 11 69 167 20 101 45 34 22
1996 324 243 81 145 179 114 70 254 142 22 160 91 16 75 206 26 91 40 25 26
1997 398 277 121 173 225 149 88 310 159 23 216 105 22 83 252 31 115 55 29 31 1998 423 293 130 224 199 158 67 356 222 19 182 150 15 135 228 43 152 67 45 40
1999 437 300 137 253 184 188 74 363 200 23 214 192 25 167 233 66 137 55 41 41
2000 418 279 139 236 182 230 95 323 160 37 221 168 23 145 237 42 138 65 45 28 2001 304 208 96 168 136 172 95 209 106 18 180 124 32 92 192 24 88 32 32 24
2002 224 169 55 119 105 121 57 167 115 12 97 74 17 57 145 15 64 32 22 10 2003 191 124 67 123 68 111 47 144 93 7 91 53 13 40 110 17 64 29 21 14
2004 223 157 66 130 93 116 68 155 88 12 123 60 9 51 154 9 60 20 23 17
2005 300 218 82 180 120 173 89 211 131 13 156 89 20 69 213 27 60 24 22 14 2006 312 210 102 187 125 190 99 213 132 9 171 81 12 69 223 18 70 26 27 17
2007 347 232 115 207 140 188 117 230 135 13 199 102 24 78 249 26 71 29 29 13
2008 188 115 73 111 77 109 59 129 90 9 89 41 10 31 143 9 36 17 13 6 2009 100 67 33 60 40 60 26 74 45 12 43 31 6 25 61 16 22 8 4 10
2010 171 103 68 93 78 91 47 124 98 7 66 46 7 39 106 11 54 17 19 18
Total 6432 4579 1853 3260 3172 2816 1505 4927 2854 430 3148 2053 331 1722 3831 606 1988 891 592 505
% 100 71.19 28.81 50.68 49.32 43.78 23.40 76.60 44.37 6.69 48.94 31.92 5.15 26.77 59.56 9.42 30.91 13.85 9.20 7.85
Table 3: Earnout M&A Activity by Location, Industry, Method of Payment and Advisor Presence
The table presents the UK M&A activity involving earnout-financed according to the target institution’s domicile (Domestic versus Crossborder), industry (Same Industry versus
Crossindustry and Intangible), currency of financing (earnout, and non-earnout which includes cash, stock and mixed payments), advisor presence (afae versus tfae and alae versus
tlae) and target listed status (private, public, subsidiary, subpub, subpri, subsub). Table 1 provides the definitions of variables.
Year ALL DOM CROSSB SAME CROSSIND INTANG AFAE PRIV PBL SUB SUBPUB SUBPRI SUBSUB
1986 0 0 0 0 0 0 0 0 0 0 0 0 0
1987 17 16 1 9 8 8 1 14 0 3 3 0 0
1988 81 70 11 32 49 35 13 66 6 9 5 4 0
1989 76 63 13 29 47 37 13 60 3 13 6 4 3
1990 43 36 7 17 26 24 9 32 1 10 5 4 1
1991 28 22 6 5 23 9 6 20 1 7 3 4 0
1992 22 20 2 7 15 3 4 15 0 7 5 2 0
1993 31 27 4 13 18 10 11 19 1 11 4 3 4
1994 42 32 10 16 26 16 12 38 1 3 2 1 0
1995 67 54 13 27 40 34 11 57 1 9 5 3 1
1996 70 57 13 30 40 29 16 63 0 7 5 2 0
1997 88 68 20 39 49 48 22 70 0 18 5 6 7
1998 67 52 15 36 31 32 15 57 0 10 1 6 3
1999 74 57 17 40 34 45 25 61 1 12 3 8 1
2000 95 79 16 45 50 70 23 78 0 17 6 8 3
2001 95 74 21 50 45 71 32 85 0 10 0 6 4
2002 57 44 13 28 29 47 17 46 1 10 4 3 3
2003 47 35 12 26 21 32 13 40 0 7 5 1 1
2004 68 55 13 39 29 39 9 59 0 9 4 5 0
2005 89 69 20 61 28 68 20 85 1 3 1 2 0
2006 99 77 22 56 43 73 12 89 0 10 5 4 1
2007 117 90 27 70 47 76 24 106 0 11 4 6 1
2008 59 42 17 36 23 39 10 56 0 3 2 1 0
2009 26 20 6 15 11 20 6 23 0 3 1 2 0
2010 47 31 16 28 19 27 7 42 0 5 2 2 1
Total 1505 1190 315 754 751 892 331 1281 17 207 86 87 34
% 100 79.07 20.93 50.10 49.90 59.27 21.99 85.12 1.13 13.75 5.71 5.78 2.26
Table 4: Summary Statistics
The table presents mean and median deal values according to target listed status (Private versus Subsidiary and Public), method of payment
(Earnout, Cash, Stock and Mixed), industry (Intangible, Crossindustry, Same Industry), location (Domestic versus Crossborder) and advisor
presence (Afae, Non_Afae, Ea_Afae, Nea_Afae). Table 1 provides definitions of the variables.
ALL EA NON EA CASH STOCK MIXED INTANG CROSSIND SAME CROSSB DOM AFAE NAFAE EA_AFAE NEA_AFAE
ALL N 6432 1505 4927 2854 430 1644 2816 3172 3260 1853 4579 2053 4379 331 1722
% of All - 0.23 0.77 0.44 0.07 0.26 0.44 0.49 0.51 0.29 0.71 0.32 0.68 0.05 0.27
Mean of DV 134.161 22.503 168.272 78.557 209.108 313.237 67.104 79.267 187.574 301.633 66.390 375.066 21.218 51.192 437.321
Median of DV 10.965 8.855 12.110 11.325 15.015 12.955 10.225 10.430 11.680 18.880 9.000 36.170 7.040 17.130 43.665
PRIV N 3831 1281 2550 1299 195 1056 1885 1891 1940 1060 2771 866 2965 265 601
% of All 0.60 0.20 0.40 0.20 0.03 0.16 0.29 0.29 0.30 0.16 0.43 0.13 0.46 0.04 0.09
Mean of DV 26.409 18.668 30.298 24.818 34.316 36.297 21.897 23.895 28.860 40.855 20.883 64.594 15.256 35.926 77.235
Median of DV 7.950 8.450 7.555 7.010 6.650 8.940 8.010 7.500 8.435 12.845 6.840 19.730 6.460 16.560 21.910
SUB N 1995 207 1788 1290 77 422 686 968 1027 605 1390 662 1333 58 604
% of All 0.31 0.03 0.28 0.20 0.01 0.07 0.11 0.15 0.16 0.09 0.22 0.10 0.21 0.01 0.09
Mean of DV 102.370 36.490 109.997 84.500 45.586 199.443 74.182 93.792 110.455 197.575 60.932 248.175 29.960 90.813 263.286
Median of DV 13.830 9.630 14.910 14.155 9.080 17.425 11.905 13.500 14.140 28.970 10.490 47.470 8.950 21.015 49.710
PBL N 606 17 589 265 158 166 245 313 293 188 418 525 81 8 517
% of All 0.09 0.00 0.09 0.04 0.02 0.03 0.04 0.05 0.05 0.03 0.06 0.08 0.01 0.00 0.08
Mean of DV 920.006 140.163 942.515 313.056 504.524 2364.260 395.107 368.878 1508.750 2106.850 386.212 1047.200 95.600 269.609 1059.230
Median of DV 83.450 15.670 87.720 84.720 38.560 226.895 82.250 70.710 119.820 190.165 59.535 108.390 17.340 35.745 113.300
Table 5: Univariate Analysis
The table presents mean and median announcement period 5-day (t-2, t+2) abnormal returns for all acquisitions divided by target listing status. The
analysis is further categorized for those cases where there exists an advisor for the acquiring firm (financial or legal), where there exists a financial
advisor for the acquiring firm, where there exists a legal advisor for the acquiring firm and where there does not exist an advisor for the acquiring firm.
Statistical significance of difference in returns between two groups of bidders is tested using the T-test of equality of means and the Wilcoxon rank sum
test for equality of medians.
Panel A: All Acquisitions
All Cash EA Stock Mixed NEA NEA VS
EA
Cash VS
EA
Stock VS
EA
Mixed VS EA
All Mean 1.30*** 1.08*** 1.70*** 0.73* 1.47*** 1.18*** -0.52*** -0.62*** -0.97** -0.23
Median 0.49*** 0.40*** 0.64*** -0.35 0.7105*** 0.45*** -0.19* -0.2415* -0.99*** 0.07
Number 6432 2854 1505 430 1644 4927
PRIV Mean 1.40*** 0.85*** 1.61*** 1.26** 1.86*** 1.30*** -0.31 -0.76*** -0.35 0.26
Median 0.55*** 0.24*** 0.60*** -0.35 0.98*** 0.52*** -0.08 -0.3655** -0.95* 0.3735*
Number 3830 1299 1280 195 1056 2550
SUB Mean 1.56*** 1.38*** 2.25*** 3.09*** 1.47*** 1.48*** -0.78 -0.87* 0.84 -0.78
Median 0.55'*** 0.52*** 0.76*** 1.32*** 0.35*** 0.53*** -0.23 -0.24 0.56 -0.41
Number 1995 1290 207 77 422 1788
SUBPUB Mean 1.32*** 1.25*** 1.89** 3.21** 0.97* 1.27*** -0.60 -0.62 1.34 -0.90
Median 0.48*** 0.48*** 0.56** 1.87** 0.12 0.45*** -0.11 -0.08 1.31 -0.44
Number 891 586 86 32 188 805
SUBPRI Mean 1.77*** 1.38*** 2.83*** 3.57** 1.78*** 1.59*** -1.24 -1.45* 0.74 -1.06
Median 0.531*** 0.38*** 1.22*** 1.15** 0.60** 0.41*** -0.81 -0.84 -0.07 -0.62
Number 592 353 87 25 127 505
SUBSUB Mean 1.70*** 1.65*** 1.76 0.71 2.00*** 1.70*** -0.06 -0.11 -1.05 0.25
Median 0.704*** 0.85*** 0.40 0.73 0.56** 0.73*** 0.33 0.45 0.33 0.16
Number 505 347 34 17 107 471
SUBUNLI Mean 1.74*** 1.51*** 2.53*** 2.41* 2.10*** 1.64*** -0.89 -1.01 -0.12 -0.43
Median 0.60*** 0.55*** 0.99*** 0.86** 0.70*** 0.60*** -0.40 -0.45 -0.13 -0.29
Number 1097 700 121 42 355 976
UNLI Mean 1.46*** 1.11*** 1.70*** 1.78*** 1.75*** 1.37*** -0.32 -0.58*** 0.08 0.06
Median 0.55*** 0.412*** 0.63*** 0.06** 0.86*** 0.52*** -0.11 -0.22 -0.57 0.22
Number 5825 2589 1487 272 1478 4338
PBL Mean -0.16 0.80* 2.04 -1.08* -1.06* -0.23 -2.27 -1.24 -3.11* -3.1*
Median -0.40 0.18 0.92 -1.15** -0.71 -0.43 -1.34 -0.74 -2.07** -1.63*
Number 606 265 17 158 166 589
Panel B: Acquiror Financial Advisor Exists
All Cash EA Stock Mixed NEA NEA VS
EA
Cash VS
EA
Stock VS
EA
Mixed VS EA
All Mean 1.63*** 1.55*** 2.48*** 0.44 1.72*** 1.47*** -1.01** -0.93** -2.04*** -0.76
Median 0.73*** 0.76*** 1.18*** -0.64 0.96*** 0.64 -0.54** -0.43 -1.83*** -0.22
Number 2053 870 331 225 627 1722
PRIV Mean 2.18*** 1.24*** 2.16*** 2.74** 2.90*** 2.19*** 0.03 -0.92 0.58 0.73
Median 1.10*** 0.77*** 1.08*** -0.04 1.94*** 1.16*** 0.08 -0.32 -1.12 0.86
Number 866 251 265 58 292 601
SUB Mean 2.39*** 2.16*** 4.41*** 2.38 2.23*** 2.19*** -2.22** -2.25** -2.02 -2.18*
Median 1.17*** 1.02*** 2.95*** -0.06 0.99* 0.92*** -2.03*** -1.94*** -3.02* -1.96***
Number 662 388 58 28 188 604
SUBPUB Mean 1.98*** 2.00*** 3.20** 2.18 1.51** 1.87*** -1.33 -1.20 -1.02 -1.69
Median 0.90*** 0.86*** 1.89*** -0.74 0.76** 0.78*** -1.12* -1.04 -2.63 -1.13*
Number 342 210 28 14 90 314
SUBPRI Mean 2.62*** 2.06*** 5.63*** 2.97 2.21*** 2.17*** -3.46* -3.57* -2.66 -3.42*
Median 1.00*** 0.39** 3.98*** 0.12 0.68** 0.38*** -3.6*** -3.59** -3.86 -3.3**
Number 162 82 21 9 50 141
SUBSUB Mean 3.02*** 2.62*** 5.32 1.17 3.58*** 2.88*** -2.44 -2.72 -4.15 -1.74
Median 1.74*** 1.33*** 3.82* 1.60 2.97*** 1.74*** -2.08 -2.49 -2.22 -0.84
Number 157 96 9 4 48 148
SUBUNLI Mean 2.81*** 2.35*** 5.54*** 2.42 2.88*** 2.54*** -3.00* -3.18* -3.12 -2.65
Median 1.31*** 1.13*** 3.90*** 0.81 1.54*** 1.10*** -2.8** -2.76** -3.08 -2.36**
Number 319 178 30 13 98 289
UNLI Mean 2.27*** 1.80*** 2.57*** 2.62** 2.63*** 2.19*** -0.37 -0.77 0.06 0.07
Median 1.12*** 0.82*** 1.27*** -0.05 1.44*** 1.00*** -0.27 -0.44 -1.31 0.17
Number 1528 639 323 86 480 1205
PBL Mean -0.23 0.87* -0.92 -0.90 -1.28** -0.22 0.70 1.79 0.01 -0.36
Median -0.5 0.4 -0.89 -1.26** -0.77* -0.51 0.38 1.29 -0.37 0.12
Number 525 231 8 139 147 517
Table 5 (Continued)
Panel C: Acquiror Financial Advisor Does Not Exist
All Cash EA Stock Mixed NEA NEA
VS
EA
Cash
VS EA
Stock
VS EA
Mixed
VS
EA All Mean 1.15*** 0.88*** 1.48*** 1.04* 1.32*** 1.03*** -
0.45** -0.6*** -0.44 -0.16
Median 0.39*** 0.31*** 0.53*** 0.03 0.56*** 0.37*** -0.16 -0.21 -0.50 0.03
Number 4378 1984 1173 205 1017 3205
PRIV Mean 1.10*** 0.75*** 1.46*** 0.63 1.47*** 1.03*** -0.43* -
0.71*** -0.83 0.01
Median 0.38*** 0.15*** 0.56*** -0.51 0.82*** 0.35*** -0.21 -0.41* -1.06** 0.26
Number 1414 1048 1015 137 764 1949
SUB Mean 1.15*** 1.04*** 1.42*** 3.49*** 0.87** 1.12*** -0.30 -0.37 2.08* -0.55
Median 0.39*** 0.40*** 0.3 2.00*** 0.06 0.40*** 0.10 0.10 1.7*** -0.24
Number 1333 902 149 49 234 1184
SUBPUB Mean 0.92*** 0.83*** 1.22 4.01*** 0.47 0.88*** -0.35 -0.40 2.78 -0.76
Median 0.27*** 0.36** 0.11 3.36*** -0.1 0.33*** 0.23 0.25 3.25*** -0.21
Number 549 376 58 18 98 491
SUBPRI Mean 1.45*** 1.18*** 1.94** 3.91** 1.49* 1.36*** -0.58 -0.76 1.97 -0.45
Median 0.49*** 0.39*** 0.69*** 2.03*** 0.6 0.47*** -0.22 -0.31 1.34 -0.10
Number 430 271 66 16 77 364
SUBSUB Mean 1.11*** 1.29*** 0.48 0.57 0.73 1.16*** 0.68 0.81 0.09 0.25
Median 0.47*** 0.60*** 0.39 0.5 -0.06 0.50*** 0.10 0.21 0.10 -0.45
Number 348 251 25 13 59 323
SUBUNLI Mean 1.30*** 1.23*** 1.54** 2.41 1.16** 1.27*** -0.27 -0.31 0.87 -0.38
Median 0.48*** 0.49*** 0.42 1.15* 0.28 0.49*** 0.07 0.07 0.74 -0.13
Number 778 522 91 29 136 687
UNLI Mean 1.17*** 0.89*** 1.45*** 1.39** 1.33*** 1.06*** -
0.39**
-
0.57*** -0.07 -0.12
Median 0.40*** 0.33*** 0.50*** 0.12* 0.61*** 0.38*** -0.12 -0.17 -0.38 0.10
Number 4297 1950 1164 186 998 3133
PBL Mean 0.26 0.34 4.66* -2.34 0.65 -0.29 -
4.95** -4.33* -7.00** -4.02
Median -0.2 -0.28 4.34 -0.82 0.15 -0.39 -
4.73** -4.62* -5.16** -4.19
Number 81 34 9 19 19 72
Panel D: Acquiror Financial Advisor Exists VS Acquiror Financial Advisor Does Not
Exist
All Cash EA Stock Mixed NEA
All Mean
Diff. 0.48*** 0.67*** 1.00** -0.6 0.4 0.44**
Median
Diff. 0.34** 0.44*** 0.66** -0.67** 0.4 0.27
PRIV Mean
Diff. 1.08*** 0.49 0.7 2.1 1.43*** 1.16***
Median
Diff. 0.72*** 0.62 0.53 0.47 1.13*** 0.81***
SUB Mean
Diff. 1.24*** 1.12*** 2.99*** -1.11 1.36** 1.08***
Median
Diff. 0.78*** 0.62*** 2.65*** -2.06 0.93* 0.52***
SUBPUB Mean
Diff. 1.06*** 1.17*** 1.98 -1.82 1.05 0.99**
Median
Diff. 0.63** 0.50** 1.79** -4.09* 0.86 0.44*
SUBPRI Mean
Diff. 1.17** 0.88 3.69** -0.94 0.72 0.81
Median
Diff. 0.51 0.01 3.29*** -1.91 0.08 -0.09
SUBSUB Mean
Diff. 1.91*** 1.31** 4.84* 0.6 2.85** 1.72***
Median
Diff. 1.27*** 0.73* 3.42 1.1 3.03 1.24**
SUBUNLI Mean
Diff. 1.52*** 1.12** 4.00*** 0 1.72* 1.27***
Median
Diff. 0.83*** 0.65* 3.48*** -0.34 1.26* 0.61**
UNLI Mean
Diff. 1.10*** 0.91*** 1.11*** 1.24 1.31*** 1.13***
Median
Diff. 0.72*** 0.50*** 0.77** -0.16 0.84*** 0.62***
PBL Mean
Diff. -0.49 0.53 -5.58* 1.43 -1.93 0.07
Median
Diff. -0.31 0.68 -5.23* -0.44 -0.92 -0.11
Table 6: Multivariate Analysis
The table presents announcement period 5-day (t-2,t+2) excess returns of bidders are regressed against a set of explanatory variables. Regression outputs
(based on equation 3) are estimated using ordinary least squares with the coefficients adjusted for possible heteroscedasticity using White
heteroscedasticity-consistent standard errors and covariance. The intercept measures the excess returns to bidders after accounting for the effects of all
explanatory variables.
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
Constant 0.0083 0.0068 0.0148*** 0.0149*** 0.0284 0.0320
EA 0.0007 0.0013
AFAE 0.0108*** 0.0084*
EA_AFAE 0.0088*
EA_AFAE_UNLI 0.00961** 0.0097**
INTANGIBLE 0.0032* 0.0031* 0.0028 0.0028 0.0052 0.0051
BAGE 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
MV -0.0053*** -0.0036*** -0.0035*** -0.0035*** -0.0057*** -0.0057***
DV 0.0041***
RES -0.00416* -0.0041*
MTBV 0.0000 0.0000 0.0000 0.0000 0.0001 0.0001
UNLISTED 0.0188*** 0.0181*** 0.0115*** 0.0114*** 0.0036 -0.0003
CROSSB 0.0037 0.0037 0.0039 0.0039 0.0050 0.0048
CROSSIND -0.0002 -0.0008 -0.0011 -0.0011 0.0028 0.0028
COMMON -0.0010 -0.0004 -0.0004 -0.0004 -0.0012 -0.0011
CASH_RATIO 0.01946** 0.0202** 0.0214** 0.0214** 0.0176 0.0173
DEBT -0.0004 -0.0001 0.0001 0.0001 -0.0006 -0.0007
F-Test 11.18*** 10.85*** 9.48*** 9.57*** 3.12*** 3.21***
R2 (adjusted) in % 2.26 2.19 1.73 1.75 2.04 2.12
N 6432 6432 6432 6432 1505 1505