College of Business Administration University of Rhode Island 2005/2006 No. 5 This working paper series is intended to facilitate discussion and encourage the exchange of ideas. Inclusion here does not preclude publication elsewhere. It is the original work of the author(s) and subject to copyright regulations. WORKING PAPER SERIES encouraging creative research Office of the Dean College of Business Administration Ballentine Hall 7 Lippitt Road Kingston, RI 02881 401-874-2337 www.cba.uri.edu William A. Orme James E. Owers, Bing Xuan Lin and Ronald C. Rogers Cross Border Mergers and Aquisitions Using ADRs as Considerations
Transcript
College of Business Administration
University of Rhode Island
2005/2006 No. 5
This working paper series is intended tofacilitate discussion and encourage the
exchange of ideas. Inclusion here does notpreclude publication elsewhere.
It is the original work of the author(s) andsubject to copyright regulations.
WORKING PAPER SERIESencouraging creative research
Office of the DeanCollege of Business AdministrationBallentine Hall7 Lippitt RoadKingston, RI 02881401-874-2337www.cba.uri.edu
William A. Orme
James E. Owers, Bing Xuan Lin and Ronald C. Rogers
Cross Border Mergers and Aquisitions Using ADRs as Considerations
Cross Border Mergers and Acquisitions Using ADRs as Consideration
James E. Owers Department of Finance
Robinson College of Business Georgia State University
(803) 777-5960 This draft October 2005 Do not quote without authorization The excellent research assistance of Parijat Cheema, Kaysia Campbell and Girish Tamankar is gratefully acknowledged. Our thanks to the RCB of GSU for making this assistance available.
Cross Border Mergers and Acquisitions Using ADRs as Consideration
Abstract We examine mergers and acquisitions wherein American Depositary receipts (ADRs) are the primary means of consideration. The majority of these transactions involve the acquisition of U.S. Corporations by non-U.S. firms using their ADRs. We show that acquisitions using ADRs involve variations on a theme and outline the institutional details. Next we empirically examine the implications of these variations and demonstrate how different sub-samples differ in terms of the strategy for the acquisition, transactional details, and valuation consequences. We also find that acquirer’s performance is better when the target is in a different industry. We relate our findings to the recent debate on the “diversification discount.”
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Cross Border Mergers and Acquisitions Using ADRs as Consideration
I. Introduction
Mergers and acquisitions have generated research topics for many years. As these studies
have come to examine the impact of more precise attributes of transactions, both cross-border
features and the type of consideration (equity or cash) have been researched. In this paper the
cross border and type of consideration dimensions are brought together to study mergers and
acquisitions in which ADRs are used as a form of payment.
ADRs are the securities of companies domiciled in other nations trading in the U.S. with
similar institutional arrangements to the stocks of companies with headquarters in the U.S.1
Although the use of ADRs as a form of payment has received little if any attention in the
research literature, there has emerged a pattern of non-U.S. firms with ADRs to use them in
making acquisitions.2 This is an interesting overlap between the processes of mergers and
acquisitions and listing abroad from the home country. Most of the transactions in this paper are
non-U.S. companies employing their ADRs to purchase U.S. firms but in some instances the
acquirer is using ADRs traded in the U.S. to acquire a company in a third country. As such,
these transactions are interesting parts of International Finance.
The primary roles of this paper are to document this unique type of acquisition activity
and to examine whether the use of ADRs affects valuation changes or other attributes associated
with these acquisitions. While transactions using ADRs are relatively few compared to all
merger and acquisition activity, they nevertheless occur in material volume and incorporate a
1 See, for example Karoli (1998) and Nanda, Owers and Feng (1996). Although the first formal ADR was created in 1927, the essential elements of the instrument can be found in arrangements and transactions during WW I. 2 Given that ADRs are by definition issued by Non-U.S. firms, the terms “Non-U.S.” and “foreign” can be used inter-changeably from a U.S. perspective.
3
range of institutional and transactional variations. We find that the overall revaluations
associated with ADR-consideration acquisitions are similar in profile to those associated with
purely domestic acquisitions and international acquisitions not employing ADRs. However,
there are notable variations from the overall profile for particular firms and transactions,
indicating that these are unique transactions in additional to the somewhat unusual institutional
arrangements.
ADRs provide an institutionally convenient and cost-effective vehicle for international
diversification for investors. For issuing firms they provide access to the large scale U.S. capital
markets and added international visibility (from both operations and financial perspectives).3 It is
surprising that the potential benefit of using ADRs as a means of consideration in international
acquisitions has received very little (if any) attention in the research literature. In this paper, we
examine this subset of mergers and acquisitions and find that targets experience significant
increases in value on announcement and acquirers experience returns exhibiting considerable
variation. Both merger transactions and the acquisitions of part of targets produce positive
returns for acquirers. Interestingly, acquirers’ returns are higher when targets operate in different
industries from acquirers.
The remainder of the paper is organized as follows. Section II identifies the relevant
literature that provides the context for the study. The hypotheses employed to structure the
empirical analysis are spelled out in section III. Details pertaining to the sample, data and
methodology employed in the empirical analysis are described in section IV. The findings are
presented and interpreted in section V. Section VI summarizes and concludes the paper.
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II. Related Literature
There is a voluminous literature pertaining to the topic of this paper and we will address
the major papers relevant to the development of the hypotheses of this study under two headings:
(1) the literature on mergers and acquisitions and (2) the relevant international finance
literature.
The Mergers and Acquisitions Literature
The transactions examined in this paper are mergers and acquisitions. In most cases they
are the acquisition of all of a target firm. In the remainder they are either partial acquisitions of a
target (i.e. a “toehold”), or completing acquisitions where part of the target was previously
owned by the acquirer (often referred to as a “wrap-up”). In most cases there is a clear
identification of the acquirer and target, with mergers “of equals” and the formation of a new
firm/security comprising few transactions. Findings from earlier studies were summarized by
Jensen and Ruback (1983) and Jarrell, Brickley and Netter (1988). The profile of findings from
the early studies showed that targets almost universally increase in value significantly whereas
acquirers typically experience small declines in values. These transactions have been
extensively examined from perspectives such as auction theory and the “winner’s curse” is an
established part of the literature.
Subsequent studies have added significant refinement to the understanding of these
transactions. Arande, Mitchell and Stafford (2001) review some of the more recent findings and
evolving perspectives that have come forth since the earlier studies. Most details of mergers and
acquisitions have now received attention in both academic and practitioner literature. These
include analyzing the economic monetary effects in addition to the percentage abnormal returns
3 While there are 460 Non-U.S. companies listed on the NYSE and in recent years the number of ADRs traded in the U.S. has generally increased, there are both benefits to and costs of such listings and some firms have withdrawn
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(Dennis and McConnell [1984] and Bradley, Desai and Kim [1988]). The significance of the
type of consideration was noted by Asquith, Brunner and Mullins (1987), Huang and Walkling
(1987), Travlos (1987), and Heron and Lie (2002) and has now been extensively examined. The
findings from this now extensive series of method-of-payment studies are succinctly summarized
by Bharadwaj and Shivdansi (2003). They note that “It is well known that the method of
payment for an acquisition has an important influence on acquirer returns, with acquirers earning
returns that are close to zero, on average, in cash tender offers and significantly negative returns
in stock tender offers.” Recent avenues of empirical examination in determining the distribution
of gains between bidders and targets include the relative reputation of financial advisors who
provide advice on both the type of merger to pursue and the bargaining strategies. Kale, Kini
and Ryan (2003) find the relative reputation of the (respective) advisors to be significant in
determining wealth creation and its distribution in mergers and acquisitions.
Theoretical work pertaining to mergers and acquisitions has also been extensive. The
findings of average negative returns to acquirers led to theories pertaining to agency
considerations and free cash flow (Jensen and Meckling [1976], Jensen [1986]), and the role of
hubris (Roll [1986]). Behavioral finance theories have also been put forward to structure the
examination of mergers and acquisitions. In examining the way in which acquisitions are
motivated by stock market conditions, Schleifer and Vishney (2003) position their theory as
follows: “This theory is in a way the opposite of Roll’s (1986) hubris theory of corporate
takeovers, in which financial markets are rational, but corporate managers are not. In our theory,
managers rationally respond to less-than-rational markets.”
their ADRs. See for example, “Mexican Firms leave NYSE,” The Wall Street Journal, January 17, 2005.
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The International Finance literature
The directly relevant segments of the international finance literature relating to this paper
are studies of ADRs and cross-border acquisitions. We take these in turn.
ADRs.
ADRs have a long and intriguing history. After the essential features developed during
World War I, the first ADR was formally established in 1926. The role of ADRs was limited
first by the economic conditions of the 1930s and then World War II. During the 1950s ADRs
were issued first mainly by European firms. After restrictions were eased, Japanese firms began
issuing ADRs. By 1961, 150 firms from 17 countries had ADRs. But growth was limited after
the Interest Equalization Tax (IET) was put in place during 1963 to address concerns about an
outflow of American capital.
After the elimination of the IET in 1974, the ADR markets grew rapidly. As ADRs
became numerous and popular as a vehicle for implementing international portfolio
diversification strategies, their investment performance came to receive considerable attention in
studies such as Foerster and Karolyi (2000) and Nanda, Feng and Owers (2000). The overall
profile of their investment performance is generally similar to findings for purely domestic
investment vehicles and situations. For example, the investment performance of ADRs that are
IPOs has been found to be generally similar to domestic IPOs. Privatizations using ADRs have
similar investment performance to purely domestic privatizations.
Although ADRs have come to receive considerable attention in the research literature, we
are not aware of any other study that has examined the role of ADRs in mergers and acquisitions.
Hence this study examines both the institutional attributes of these transactions and the valuation
changes associated with them.
7
Cross-border acquisitions
A number of studies have examined the consequences of U.S. forms acquiring foreign
firms. Doukas and Travlos (1989) found generally insignificant valuation consequences for the
U.S. acquirers with the exception of when the acquisition was the first major step of the acquirer
into the target’s country. Lin, Madura and Picou (1994) found material variation in U.S.
acquirer valuation reactions according to the domicile of the target. Acquisition of German
firms was associated with positive abnormal returns. In contrast, acquisitions of British and
Canadian targets were associated with negative abnormal returns.
Kang (1993) examined matched-pairs of acquisitions between Japanese bidders and U.S.
targets. He found statistically significant wealth gains for both firms. As is appropriate for
cross-border acquisitions, he placed his analysis in the context of Direct Foreign Investment
(DFI). Specific attributes of bidder firms and exchange rate movements were found to be
systematically associated with bidder returns.
The contrast between this finding and the profile for purely domestic transactions of
target gains and acquirer losses (or essentially zero reaction with cash transactions) is notable.4
There are apparently different valuation consequences to be found with cross-border acquisitions
compared to purely domestic transactions. These differences indicate the potential for the
particular type of acquisition examined in this paper to add further insights into the significance
of particular details of transactions such as being cross-border and using a somewhat unusual
method of payment.
4 See Bruner (2002) for an integrated interpretation of findings of Merger and Acquisition studies from both academic and practitioner perspectives.
8
III. Hypotheses
The acquisition in 1999 of PacifiCorp by Scottish Power PLC illustrates a number of
characteristics associated with acquisition by ADR. The acquisition created the first
combination of power utilities in the U.S. and United Kingdom. It was a significant transaction
($6.5 billion) and the merged unit planned to dispose of some of PacifiCorp’s properties
(including an interest in an Australian power station). Reference to the familiar synergy and cost
efficiency motivations for acquisitions was to be found in the chief executive of the acquirer
noting that “the deal will generate significant cost savings for the merged group.” Each
PacifiCorp share was to be exchanged for 0.58 ADR of Scottish Power PLC. Each ADR
represented 4 shares of Scottish Power. More commonly, an ADR will represent 5 or 10 units of
the home country shares.5 The ADRs of Scottish Power dropped 9.48% (the CAR over [-1,+1])
on announcement of the transactions. They fell further when completion of the acquisition was
announced. On the date of announcement, the value of PacifiCorp shares experienced a 4.7%
increase. Scottish Power’s subsequent experience with PacifiCorp was not as positive as
anticipated at the time of the acquisition and in May 2005 it agreed to sell PacificCorp to the
MidAmerica unit of Berkshire Hathaway for $5.1 billion in cash plus debt assumption of $4.3
billion. This was Berkshire Hathaway’s largest acquisition since 1998 and Warren Buffet noted
that it was a transaction in line with the strategy of using some of Berkshire’s $40 billion cash for
acquisitions in the energy sector. On announcement, Berkshire Hathway A shares increased by
1.8% and those of Scottish Power (its NASDAQ traded ADR) by 5.7%.
The focus of this paper is an empirical analysis of mergers and acquisitions wherein
ADRs are employed as a form of consideration. As such, the voluminous theoretical and
5 See Muscarella and Vetsuypens (1996) for additional details on ADR/home country share relationships.
9
empirical literature pertaining to mergers and acquisitions provides context for this analysis. In
this context, we posit the following hypotheses to structure our analysis of these transactions.
Similar Overall Profile Hypotheses
The market forces and processes pertaining to acquisitions using ADRs are generally
similar to those for purely domestic acquisitions. Thus it is hypothesized that the average
valuation consequences for the target and acquirers will be consistent with the cumulative profile
of studies to date:
- H1a: That targets will experience significant positive abnormal returns
- H1b: That since equity securities are used by the acquirer, they will incur
small negative abnormal returns.
The issues associated with these hypotheses will be investigated for the separate sub-
samples of targets and acquirers and then a matched pair sub-sample.
Variations of Returns with Transaction’s Attributes There are significant variations in the details of acquisitions using ADRs. These include:
- Whether the transacting firms are from developed or developing economies;
- Whether the target is a U.S. or foreign firm;
- Whether only ADRs are used or a combinations of considerations;
- Whether 100% of the target is being acquired (in contrast to a “toehold” or “wrap-up” of the
remaining part of the target);
- Whether the size of the transaction impacts the valuation consequences; and
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- The significance of the acquirer and target having the same SIC code.
The significance of these variations in institutional transactional details will be investigated.
The null hypothesis is that these attributes will affect return outcomes for both targets and
bidders.
IV. Data & Methodology
The source of the sample of transactions came from the SDC database where it listed the
means of consideration between 1985 and 2004. From the original listing of 107 acquisition
transactions involving ADRs, we identify 107 targets and 98 acquirers wherein ADRs are
employed in the transaction. The original listing was then examined using the customary filters
for confounded events, sufficiency of transaction details, and data availability requirements
necessary to apply the methodology. We confirmed SDC dates with reference to financial press
sources such as The Wall Street Journal and Lexis/Nexus.
The transactions were tracked separately for targets and acquirers (respectively) that were
amenable to empirical examination. There are 55 targets and 78 acquirers meeting the criteria
for empirical analysis. Of the separate sub-samples, there were 41 transactions where both the
target and acquirers were examined and this is referred to as the “match set” sub-sample of
transactions. Table 1 enumerates on these and other sample attributes. Table 1 shows the wide
variation in number of transactions per year. This varies from 0 in 1986 to 29 in 2000. It also
reflects the wide value range of ADR acquisitions from a low of $4.5 million in 1989 (one
transaction) to an average of $5.5 billion in 1995 (with 4 transactions).
The ADR returns data are from the CRSP daily returns file. The returns data
requirements necessary to run the market model over an interval from 160 to 31 days before the
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transactions was a significant source of attrition between the original (unfiltered) sample listing
and the final empirical sample.
Reaction of the equity securities for transactions in the sample is examined using
established event-time methods. Parameters of the market model are estimated over the interval
extending from day -160 to day -31 relative to the announcement on day 0. Abnormal returns
are estimated for each day in the event interval (days -30, +30) and for various identified
intervals around the announcement (day 0).
For each security j, the market model is used to calculate an abnormal return (AR) for
event day t as follows:
jt jt j j mtAR = R - ( a + R )β (1)
where Rjt is the rate of return on security j for event day t, and Rmt is the rate of return on the
Center for Research in Security Prices (CRSP) value-weighted index on event day t. The
coefficients αj and βj are the ordinary least squares estimates of the intercept and slope,
respectively, of the market model regression.
The cumulative abnormal return (CAR) from day T1j to day T2j is defined as:
j
2j
1j
jCAR = T
t = TARΣ (2)
We cumulate over various intervals around the announcement date. For a sample of N
securities, the mean CAR is defined as:
CAR = j = 1
CAR / Nj
ΝΣ (3)
The expected value of CAR is zero in the absence of abnormal performance.
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The test statistic described by Dodd and Warner (1983) is the mean standardized
cumulative abnormal return. To compute this statistic, the abnormal return ARjt is standardized
by its estimated standard deviation sjt. The value of Sjt is:
))R-R(1=t
D)2/R-R(+
D1=(1S=S 2
mmt
j
mmtj
2j
2jt Σ
where
Sj2 = residual variance for security j from the market model regression
Dj = number of observations during the estimation period
Rmt = rate of return on the market index for date of the event period
Rm = mean rate of return on the market index during the estimation period
Rmt = rate of return on the market of day t of the estimation period
jt jt jtSAR = AR / s (4)
The SARs are cumulated and both Z and t test statistics for the sample of N securities are
employed.
V. Findings and Interpretation
The findings are presented first for the separate sub-samples of targets and acquirers.
The “matched-pairs” sub-sample is then examined. Given the substantial cross-sectional
variation in the individual company results, we subsequently undertake a cross-sectional analysis
in pursuit of the attributes that are most significant for variation from the overall profiles as
calibrated in the averages.
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Targets
The findings for the 52 target firms for which there were sufficient data to apply the
methodology are reported in Table 2. It comes as no surprise that targets experience significant
positive abnormal returns when a bid is initially made. Hypothesis 1A is strongly supported.
Some potentially intriguing aspects of the findings are NOT explained by the international nature
of these transactions. The day +1 AR is notable. Since the returns data are from CRSP they are
generated using U.S. data that comes at the end of the trading day. As the global markets
function, Asian markets begin the trading for a specified calendar date, following by European
and then North American. Thus the notable abnormal returns on day +1 are not explained by
“date line” considerations, making this of considerable interest and something for which we do
not have a convincing explanation or even a credible conjecture. Given the speed of
transmission of information that applied for all of the sample period, we find it somewhat
surprising that the consequences for the target firm are impounded over an interval that includes
the calendar day after the formal announcement date.
As noted above, with the exception of the Day +1 abnormal return, the positive target
abnormal returns reflect the silhouette from studies of domestic and cross border transactions.
However, there are some contrasts with the findings of previous merger and acquisition studies
in regards to the consequences for target firms. First, the percentage magnitudes are somewhat
smaller. This overall sub-sample includes transactions in which less than 100% of the target is
acquired and is a potential factor in the lower abnormal returns that is addressed below. Second,
there is a significant accumulation of CAR beginning at approximately day –12.
There is a clear economically material response to the announcements for the target
firms, including some notable pre-announcement CAR accumulation. Table 2 Panel B reports
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that there are notable pre-announcement patterns on days –7 and -3. However, a closer
examination of both the number of positive/negative individual firm ARs and the difference
between the Z and t statistics suggests these are driven by a relatively small number of specific
firms.
The notion that a small number of firms generate the pre-announcement abnormal returns
of note is further supported by the tests of significance of average CAR accumulation reported in
Table 2 Panel C. The CAR accumulation over (-10,-2) of 1.41% (encompassing 28 positive and
24 negative individual firms results) is not statistically significant at even the 10% level. In Table
2 Panel C, we also see that the ARs over (-1, 0) and (0, 0) are both positive and significant at the
1% level. These results are in line with the findings in prior researches where target firms
experience price appreciation upon deal announcements.
Figure I portrays the CAR pattern over the 41 day interval ending 10 days after the
announcement. It profiles the notable but statistically insignificant CAR accumulation from day
–10 to day –2 and stabilizes with a CAR of approximately 20%. Examination of the individual
daily ARs for the sample target firms comports with the above statistical findings. For a small
number of firms there are notable ARs before the transactions are announced. While interesting,
they are not a major focus of this paper and remain a potential subject for examination in a
subsequent study.
Acquirers
By definition, these are acquisitions wherein at least part of the consideration is equity
securities in the form of ADRs. The extensive research (both theoretical and empirical) has
established the rationale for and realization of negative equity value reactions to acquisitions
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with equity consideration. That context generated our hypothesis 1B that acquirers will
experience negative abnormal returns associated with the transaction. That is what our empirical
analysis finds and hypothesis 1B is supported. Table 3 documents and figure II profiles
significant negative average acquirer reaction to the announcements of these transactions.
The average CARs for the 78 acquirers over the event intervals are negative and the
number of negative responses does dominate. For example, on day 0 there are 47 negative
acquirer ARs. But that still leaves 31 positive. The average negative reaction should thus be
interpreted with caution. Clearly there are negative reactions that on average are greater then the
positive responses and the sign test in Table 3 Panel B attests to the significance of this
difference.
However, the lack of overwhelming predominance of negative acquirer CARs indicates
material variation in outcomes for acquirers. The difference between the “Z” and “t” test-
statistics also indicates substantial variation in the abnormal return outcomes. This aspect of the
acquirer value changes associated with the transaction will be visited in greater detail in the
analysis of the match-pair sub-sample.
The results reported in Table 3 and depicted in Figure II show acquirer negative abnormal
returns consistent with findings for domestic acquisitions wherein equity is the method of
payment. The cumulative abnormal returns over (-10, 0) are –1.64%. 0.62% of this accumulates
over (-1,0) and 52 of the 78 acquirers experience negative two-day abnormal returns. The CAR
(-1,0) is significant at the 1% level of significance as calibrated by the Z score but is not
significant according to the t statistic.
Match Pairs of Transactions
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As examined above, the sub-sample of targets is such that 52 firms had attributes (non-
confounded events, data availability) enabling the event analysis to be performed. In the case of
acquirers, the corresponding number is 78. The intersection of these two sets was 41
transactions in which both transacting firms were in the empirical analysis. We now look in
more detail at those 41 transactions to glean further insights into the nature and consequences of
these transactions.
Table 4 reports the abnormal returns for the 41 match-pairs target firms. Mirroring the
previous format, Panel A reports daily abnormal returns, the CAR from day –30 to day +10 and
the percent positive/negative. Panel B reports selected interval CARs and associated test
statistics.
As a comparison of tables 2 and 4 shows, there is not a notable difference in either
economic magnitudes or statistical significance between the sub-sample of 55 separate targets
and the 41 matched-pair targets. This is not surprising since the intersection is 75% of the
separate target sub-sample.
In a manner similar to that for the separate target sub samples, there is not a marked
difference between the 41 match-sample acquirers when compared to the separate sub-sample of
78 acquirers. Not surprisingly there is somewhat more difference than in the case of the targets
given that the intersection is only approximately 53%. Nevertheless there are not marked
indications that the match-pair sub-sample is materially different from the separate sub-samples.
For subsequent analysis we thus focus on the 41 match-pair sub-sample transactions. What is
more interesting about the match-pairs sub-sample is reported in Table 6. Here the pairs of CAR
accumulation over the various intervals identified in the table are classified according to whether
17
the pair-wise targets and acquirers in specific transactions individually experienced positive or
negative CARs.
Notably for the immediate interval around the announcement, while 25 (of the 41)
transactions generated the typical profile for equity consideration acquisitions of target positive
and acquirer negative accumulation, for 13 of these transactions both firms experienced positive
revaluations. Generally similar patterns are observed over the longer intervals around the
announcement. Over (-5, +1) the corresponding numbers are 26 and 10. For (–10, +1), they are
23 and 14. This set of outcomes indicates a generally more positive set of shared experiences
for the equity claimants of both targets and acquirers than is typically the case when equity is the
means of consideration in domestic acquisitions. It fits with the profile of more positive acquirer
experiences in cross border acquisitions such as the findings in Kang (1993) that was referenced
in the literature review section. There, studies of cross-border acquisitions noted circumstances
(such as the domicile of acquirers and targets and acquirer firms attributes) associated with
positive acquirer outcomes as calibrated by equity value reaction. Our findings suggest a
generally more positive acquirer outcome when using ADRs than in domestic transactions.
Cross Sectional Variations Hypotheses
As previously noted, there are substantial variations in the institutional details of the
overall sample of acquisitions employing ADRs examined in this paper. The significance and
consequences of these variations have been partially examined in the preceding analysis of
various sub-samples. We now undertake a cross- sectional regression in order to further
investigate the significance of different details of the transactions.
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Hypothesis #2 addresses variations of return outcomes with transaction attributes.
Among the major significant transactional details are:
- Variable 1: Whether the transacting firms are from developed or developing economies;
- Variable 2: Whether the transaction is a traditional acquisition or a merger;
- Variable 3: the significance of the acquirer already having an ownership interest in the target
(measured by the % already owned [i.e. a “wrap-up”])
- Variable 4: the significance of the acquirer purchasing part of the target rather than all the
outstanding equity interest ( measured by the % not acquired [i.e. a “toe-hold”])
- Variable 5: Whether the size of the transaction impacts the valuation consequences; and
- Variable 6: The significance of the acquirer and target having the same SIC code.
In order to examine whether these variations have a material impact of the valuation
outcomes as hypothesized, we undertook cross-sectional regression analyses. The 3-day Car (-1,
+1) is the dependent variable and it is regressed on independent variables representing these 6
attributes identified as major institutional variations across transactions in the sample. In some
cases, the subset of the samples with a particular attribute was very small. For example, “mop-
up” transactions comprised only 5 of the 55 target acquisitions (4 of the 41 matched pair sub-
sample).
This examination provided substantially more interesting insights in the case of acquirers
rather than targets. Interestingly, for target firms, none of these attributes had a significant
impact. For targets being acquired with the use of ADRs as a means of payments, none of the
six institutional attributes of the transaction had a statistically significant on the 3-day
announcement window CAR. Both the regression results and a comparison of the event study
19
results for the respective partitions indicated no significant difference based on these transaction
attributes. We thus reject the null hypothesis that these attributes significantly influence return
outcomes for targets.
This lack of systematic impact of some attributes is notable. In particular, given the
significance of the SIC matching being of consequence to acquirers (as discussed below), its lack
of significance for the target is notable. While it is shown below that it is a relative plus for
acquirers to purchase unrelated targets, this attribute does not significantly affect the returns
experienced by the target firm.
In contrast to the lack of significance for targets, for acquirers using ADRs there are some
significant influences on the return outcomes according to these transaction attributes. In this
context, we present in Table 7 and further discuss the regression results for acquirers only.
Attribute #4: “Toe-hold” Acquisitions
The most significant institutional variation relates to attribute #4 wherein the acquirer is
purchasing only a “toehold” and not all the target. This has a positive impact on acquirer
outcomes. Intuitively this is consistent with the notion that since acquisitions (employing equity
consideration) typically have a negative valuation consequence for the acquirer, purchasing only
a party of the target is a relative plus. A sample transaction that falls into this category is the
widely discussed toehold that UK–based British Telecom acquired in MCI in 1996.
Attribute #2: Mergers
In transactions that are effectively mergers (attribute #2) the consequences for the
“acquirer” are mitigated in terms of negative CAR. We are cautious about classifying one firm
an “acquirer” and the other a “target” when the transactions is effectively a merger but accepted
the SDC categorization in these transactions. We note that there are only two transactions in our
20
match-pair sample that appeared to be “mergers” in contrast to the dominant profile of
transactions with a clear delineation of “target” and “acquirer” roles.
Attribute #6 Acquisitions of Unrelated Targets:
We find the significance of attribute #6 to be of considerable interest. This is whether the
SIC codes of the target and acquirer are two-digit matches. This SIC match criterion has a
marginally important (5.7% level of significance) impact of acquirer CAR – and it is negative.
The acquirers with targets that do NOT match their Line of Business (at the two-digit SIC level)
have a less negative/more positive consequence associated with the acquisition. This is notable
in light of the ongoing analysis of whether there is a “diversification discount.” The research
into the valuation effects of diversification is now very extensive. There are numerous studies
identifying potential value enhancing effects of diversification. Weston (1970) focused on
synergies, Berger and Ofek (1995) examined tax consequences, and Stein (1997) considered
internal capital markets.
There is also an extensive literature supportive of a diversification discount. Lang and
Stultz (1994) address the multi-segment firm discount. The positive re-valuations associated by
undoing of diversification mergers by divestitures examined in works such as Bhagat, Schleifer
and Vishney (1990) and Kaplan and Weisback (1992) lend further support to the diversification
discount. Scharfstein and Stein (2000) captured a profile of thinking when they noted that “it
has become almost axiomatic among researchers in finance and strategy that a policy of
corporate diversification is typically value reducing.” Yet Akbulent and Matsuska (2003) study
announcement returns associated with mergers from 1950 to 2002 and generally challenge the
notion that diversification “destroys value.” Recent work reviewing both the existence and
interpretation of the diversification discount include Campa and Kedia (2002) and Villolonga
21
(2004). In addition to stock market evidence, some studies have been using micro-data to
examine the productivity implications of diversification. While Lichtenberg (1992) and
Maksimovic and Phillips (2002) conclude that diversification depresses productivity, Schoar
(2002) concludes that at the individual plant level, diversification is associated with increased
productivity. However, the increased productivity associated with newly acquired plants is
offset by a reduction in overall firm productivity.
The issue of the “diversification discount” is not a major theme of this paper and the
empirical finding that diversification reduces the negative effect on acquirers is the main
comment we want to make. However, in light of the diversification controversy and inconsistent
conclusions from the studies looking at micro productivity data underlying stock market
valuations, we find stock market evidence of diversification on average being positively regarded
in cross border acquisitions using ADRs to be a potentially very fruitful area for subsequent
detailed research.
VI. Summary and Conclusions
In this paper we examine a type of merger and acquisition transaction that does not
appear to have previously been examined in the research literature. These are cross-border
acquisitions wherein the means of consideration is primarily ADRs. Both cross-border mergers
and acquisitions and ADRs have separately received considerable attention in the research
literature but we are not aware of any previous study of transactions wherein they come together
in a particular institutional arrangement.
We identified an overall sample of 107 such transactions over the interval from 1985 to
2004. Of the 78 acquirers and 52 targets that met data and transactional criteria and could be
22
examined separately, there was an overlapping sample of 41 matched pair transactions wherein
the data and transaction criteria for both firms were met. Overall, the findings of these
transactions comport with the findings for purely domestic transactions. Namely, targets
experience significant increases in value on announcement and, since these are acquisitions using
equity, acquirers on average experience negative returns. However, as the statistical tests
suggested and individual acquirer outcomes indicated directly, the acquirer returns experienced
considerable variations and suggested a closer examination. The matched-pair analysis showed
that a surprisingly large portion of the transactions were associated with positive returns for both
acquirers and targets. For the interval (-1,+1), 13 of the 41 matched pair transactions had
positive returns for both the acquirer and target.
The analysis addressed several attributes on which the transactions varied. These
included the developed/developing domicile of the firms, whether the transaction was classified
by SDC as an acquisition or merger, whether the acquirer was purchasing all or part of the target,
the size of the transaction, and whether the SIC codes of the acquirer and target matched (at the
two digit level). None of these attributes significantly impacted the target returns. However,
there were some significant impacts for acquirer returns.
Both merger transactions and the acquisition of a part of a target were positives for
acquirer returns. Also positive for acquirer returns was when the target line of business did NOT
match the acquirer’s as calibrated by the two-digit SIC code. This is an interesting finding in
that it provides evidence contrary to the widely accepted “diversification discount” that is
financial market based and not productivity based as in some recent studies questioning the
existence of a diversification discount.
23
This paper is a first investigation of a type of transactions not previously examined in the
research literature. As such, several lines of subsequent investigation remain. These include a
closer examination of the “diversification discount/premium” attribute of industrial organization
and corporate restructuring. Do cross-border transactions wherein ADRs are employed have the
potential to provide further insights into this issue that was in the not so distant past considered
to be settled only to have significant questions arise from recent micro-data productivity studies?
Other avenues for further examination emanate from Kang’s (1993) lines of investigation in his
study of Japanese acquisitions of U.S. firms. These include an examination of the firm-specific
attributes of acquirers and targets and the role of country pairing so as to capture any exchange
rate influences. The pre-announcement CAR accumulation for some targets also appears to
provide potential for systematic study of how varying cross-border sanctions for insider trading
affect the use of strategies based on awareness of upcoming acquisitions.
24
Table 1: Sample Description:
The data includes cross-border mergers and acquisitions using ADRs for the sample period of 1985 – 2004. Transaction activity sourced from the SDC database. The number of transactions is the aggregate before filters for data requirements and elimination of confounded transactions.
Table 2A: Event Study Results for Target Firms For each security j, the market model is used to calculate an abnormal return (AR) for event day t as follows: where R)R + a( - R = AR mtjjjtjt β jt is the rate of return on security j for event day t, and Rmt is the value-
weighted index return on event day t. The coefficients αj and βj are the ordinary least squares estimates of the intercept and slope, respectively, of the market model regression. The cumulative abnormal return (CAR) from day
T1j to day T2j is defined as: . The mean CAR is defined as: ART = t T
= CAR j
1j
2j
j Σ N / CAR 1=j
= CAR jΣΝ
for a sample of N
securities. Abnormal returns are estimated for each day in the event interval (days -30, +30) and for various identified intervals around the announcement (day 0). The total number of observation is 52 firms. Panel A: Mean AR, CAR and Number of Firms with Positive/Negative AR
Panel B: AR is the abnormal return. Number positive/negative reports the number of observations with positive/negative AR at the specific date. The test of the null hypothesis that the abnormal return follows the work of Dodd and Warner (1983) and employs the z-statistic. The t-statistic the cross-sectional standard deviation test t, similar to the one used by Brown and Warner (1985); Generalized sign test indicating whether the proportion of positive to negative abnormal returns is significantly different from one.
Day AR Number positive/negative Z - statistic T - statistic Generalized
Panel C: Cumulative Average Abnormal Return for Different Event Windows CAAR is the cumulative average abnormal return. Number positive/negative reports the number of observations with positive/negative CAAR at the specific window. The test of the null hypothesis that the abnormal return follows the work of Dodd and Warner (1983) and employs the z-statistic. The t-statistic the cross-sectional standard deviation test t, similar to the one used by Brown and Warner (1985); Generalized sign test indicating whether the proportion of positive to negative abnormal returns is significantly different from one.
Interval (Day) CAAR Number
positive/negative Z - statistic T - statistic Generalized sign Z
***, **, and * indicate significance at the 1%, 5%, and 10% level, respectively using a 1-tail test.
27
Table 3: Event Study Results for Acquiring Firms For each security j, the market model is used to calculate an abnormal return (AR) for event day t as follows: where R)R + a( - R = AR mtjjjtjt β jt is the rate of return on security j for event day t, and Rmt is the value-
weighted index return on event day t. The coefficients αj and βj are the ordinary least squares estimates of the intercept and slope, respectively, of the market model regression. The cumulative abnormal return (CAR) from day
T1j to day T2j is defined as: . The mean CAR is defined as: ART = t T
= CAR j
1j
2j
j Σ N / CAR 1=j
= CAR jΣΝ
for a sample of N
securities. Abnormal returns are estimated for each day in the event interval (days -30, +30) and for various identified intervals around the announcement (day 0). The total number of observation is 78 firms. Panel A: Mean AR, CAR and Number of Firms with Positive/Negative AR
Panel B: AR is the abnormal return. Number positive/negative reports the number of observations with positive/negative AR at the specific date. The test of the null hypothesis that the abnormal return follows the work of Dodd and Warner (1983) and employs the z-statistic. The t-statistic the cross-sectional standard deviation test t, similar to the one used by Brown and Warner (1985); Generalized sign test indicating whether the proportion of positive to negative abnormal returns is significantly different from one.
Day AR Positive/negative Z - statistic T – statistic Generalized sign Z
Panel C: Cumulative Average Abnormal Return for Different Event Windows CAAR is the cumulative average abnormal return. Number positive/negative reports the number of observations with positive/negative CAAR at the specific window. The test of the null hypothesis that the abnormal return follows the work of Dodd and Warner (1983) and employs the z-statistic. The t-statistic the cross-sectional standard deviation test t, similar to the one used by Brown and Warner (1985); Generalized sign test indicating whether the proportion of positive to negative abnormal returns is significantly different from one. Interval
(Day) AR CAAR Positive/ negative Z - statistic T – statistic Generalized
***, **, and * indicate significance at the 1%, 5%, and 10% level, respectively using a 1-tail test.
29
Table 4: Event Study Results for Matched-Pair Target Firms For each security j, the market model is used to calculate an abnormal return (AR) for event day t as follows: where R)R + a( - R = AR mtjjjtjt β jt is the rate of return on security j for event day t, and Rmt is the value-
weighted index return on event day t. The coefficients αj and βj are the ordinary least squares estimates of the intercept and slope, respectively, of the market model regression. The cumulative abnormal return (CAR) from day
T1j to day T2j is defined as: . The mean CAR is defined as: ART = t T
= CAR j
1j
2j
j Σ N / CAR 1=j
= CAR jΣΝ
for a sample of N
securities. Abnormal returns are estimated for each day in the event interval (days -30, +30) and for various identified intervals around the announcement (day 0). The total number of observation is 41 firms. Panel A: Mean AR, CAR and Number of Firms with Positive/Negative AR
Panel B: Cumulative Average Abnormal Return for Different Event Windows CAAR is the cumulative average abnormal return. Number positive/negative reports the number of observations with positive/negative CAAR at the specific window. The test of the null hypothesis that the abnormal return follows the work of Dodd and Warner (1983) and employs the z-statistic. The t-statistic the cross-sectional standard deviation test t, similar to the one used by Brown and Warner (1985); Generalized sign test indicating whether the proportion of positive to negative abnormal returns is significantly different from one. Interval
(Day) N CAAR Positive/ negative Z - statistic T – statistic Generalized
(+1, +30) 41 3.04% 28:13 1.957** 1.622* 2.873** ***, **, and * indicate significance at the 1%, 5%, and 10% level, respectively using a 1-tail test.
31
Table 5: Event Study Results for Matched-Pair Acquiring Firms For each security j, the market model is used to calculate an abnormal return (AR) for event day t as follows: where R)R + a( - R = AR mtjjjtjt β jt is the rate of return on security j for event day t, and Rmt is the value-
weighted index return on event day t. The coefficients αj and βj are the ordinary least squares estimates of the intercept and slope, respectively, of the market model regression. The cumulative abnormal return (CAR) from day
T1j to day T2j is defined as: . The mean CAR is defined as: ART = t T
= CAR j
1j
2j
j Σ N / CAR 1=j
= CAR jΣΝ
for a sample of N
securities. Abnormal returns are estimated for each day in the event interval (days -30, +30) and for various identified intervals around the announcement (day 0). The total number of observation is 41 firms. Panel A: Mean AR, CAR and Number of Firms with Positive/Negative AR
Panel B: Cumulative Average Abnormal Return for Different Event Windows CAAR is the cumulative average abnormal return. Number positive/negative reports the number of observations with positive/negative CAAR at the specific window. The test of the null hypothesis that the abnormal return follows the work of Dodd and Warner (1983) and employs the z-statistic. The t-statistic the cross-sectional standard deviation test t, similar to the one used by Brown and Warner (1985); Generalized sign test indicating whether the proportion of positive to negative abnormal returns is significantly different from one. Interval
(Day) N CAAR Positive/ negative Z - statistic T - statistic Generalized
Regression Results for Acquirer Firms in 41 matched –pair transactions Acquisition transactions with
ADRs as a form of payment.
OLS regression
Coefficient (p-value)
Developing or non-developing economy
-0.033 (0.183)
Traditional acquisition or merger 0.124*** (0.006)
Percent ownership interest in target -0.003 (0.936)
Percent of target equity not acquired 0.144*** (0.003)
Transaction size 0.000 (0.652)
Same SIC between acquirer and target -0.046* (0.058)
Intercept 0.030 (0.326)
Number of observations 41 Adjusted R2 0.28 F-statistic 3.571 ***, **, and * indicate significance at the 1%, 5%, and 10% level, respectively using a 1-tail test.
35
Figure I
Average target CARs from -30 days through +10 days of the transaction announcement.
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