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JAASDP2007-1E

Shareholders’ Value Creation and Destruction:
The Stock Prices’ Effects of Merger Announcement in Japan

Ognjenka Zrilic
Graduate School of Systems and Information Engineering
University of Tsukuba

Yasuo Hoshino
Graduate School of Systems and Information Engineering
University of Tsukuba

February 2007

Shareholders’ Value Creation and Destruction:
The Stock Prices’ Effects of Merger Announcement in Japan

Abstract

This paper investigates the relative importance of different sources of value gains andlosses for Japanese acquirers in the post-bubble period. Based on the event study methodology,
we find an average 1.19% cumulative abnormal return in 3 days surrounding the merger
announcement. We empirically test value creation, buying growth, hubris and rescue merger
hypotheses on the sample of 62 Japanese domestic mergers with announcement in period
1993-2005. Our findings suggest that differences in financial resources allocation pattern may
provide a source of value gain. We do not find negative effect of buying growth. Moreover,mergers with fast-growing target are value enhancing when acquirer has prior ownership intarget. Consistent with hubris hypothesis by Roll (1986), announcement returns are adversely
related to acquirer’s past performance, implying that well-performing acquirers possibly
overestimate the true value of deal and overpay target. In contrast with Kang et al. (2000),
rescue mergers as evaluated through target’s industry adjusted past performance are not value
destroying. Announcement returns are significantly positive for mergers announced after 1998,
indicating that recent deregulation of financial markets resulted in improvement of conditions
for merger activity.

2Extant empirical literature has found that mergers represent mixed blessing for shareholdersof acquiring firms. Research in U.S. suggests that targets experience significant wealth gains,while gains to acquirers are often null or insignificantly positive (Jensen and Ruback, 1983;
Asquith, 1983; Bradley, Desai and Kim, 1988).
Historically, mergers in Japan have been notably fewer than in U.S. and consequently, less
explored. Due to deregulation of Japanese financial market in recent years, merger activity
has increased, in terms of both, the number and the value of deals. Increase is especiallyprominent following 1998 due to changes in Government policy and amendments to
Antimonopoly Law. During 1999 the total number of mergers first time reached more than
1000, and in consequent six years more than doubled to 2725 in 2005 (MAAR Magazine,
August 2006). After 1998, domestic mergers account for more than sixty percent of thenumber of total mergers and this trend continues in the years following. The dramatic increase
in merger activity makes it important to understand motives behind and consequences ofmergers.
Previous event studies on Japanese mergers found contrasting results for different periodsof analysis; acquirers gain (Pettway and Yamada, 1986; Kang, Shivadasani and Yamada,
2000; Inoue, 2003), acquirers experience wealth losses (Yeh and Hoshino, 2001). Moreover,skepticism regarding the consequences of merger activity has grown with studies based on
accounting data finding that mergers tend to distort long term profitability of merging parties(Odagiri and Hase, 1989; Yeh and Hoshino, 2002). A number of event studies on Japanesemergers have been focused on examining the implications of keiretsu groupings, main banksystem (Kang, Shivadasani and Yamada 2000; Yeh and Hoshino, 2001) and cross-corporateshareholdings (Van Schaik and Steenbeek, 2004). However, deregulation of Japanese financial
markets has brought substantial changes in corporate structures and weakening the role ofmain bank in recent years. Thus, it is likely that currently increased merger activity can be
attributed to different factors from previously stated.
3

This objective of this paper is to investigate the conditions under which Japaneseacquirers in domestic market earn abnormal returns by examining alternative managerial
behavioral assumptions regarding the merger activity decision making. Focus on post-bubble
period allows us to examine more confined merger activity, not extensively explored inprevious literature.

THEORY AND HYPOTHESES

Mergers have been topic extensively explored in different scientific disciplines. Abundant
literature describes motives behind merger activity. One of the most comprehensive
description of merger’s motives is provided by Trautwein (1990). The classification of
motives is based on rationality behind merger activity decision making. Theories explaining
merger’s occurrence as a result of rational choice state two possible outcomes of a merger;
benefits for acquirer’s shareholders or benefits for acquirer’s management. The former
outcome realizes when acquirer’s management is impelled by seeking possibilities for valueenhancement, while the last outcome happens when management focuses on achievement of
personal goals through merger. On the other hand, occurrence of a merger as not completely
rational decision is suggested by process theory. Process theory argues that merger occurs as aresult of individuals’ bounded rationality, organizational routines or political power.
In this paper we examine the implications of three theories described as having the highest
degree of plausibility; valuation theory, empire-building theory and process theory (Figure 2).

4

Rationality Perspective
Valuation Theory
Valuation theory argues that firm’s excess resources are not readily available to other firms
since the existing market impediments (such as government regulations, limited informationtransfer etc.) prevent smooth distribution of excess resources among firms. In light of thisview, merger occurs when acquirer has private information about target that would increase
the value of combined entity through purchase of an undervalued peer. Thus, acquirer’s
management would be motivated by valuable information about potential advantages to beachieved from combining with the target’s business (Trautwein, 1990). Barney (1988)
suggests that value for acquirer is created when private and unique (inimitable) cash flow
exists between merging parties. Unique or inimitable cash flow means that a particular target
has higher value for one acquirer than for the others. Harrison et al. (1991) provide evidence
that this type of synergy is prominent when specific differences rather than similarities inresources allocation pattern exist between merging parties, since such differences are noteasily observable, neither easy to replicate by other market participants. Consequently,
acquirer with a source of synergy based on discrepancy in allocation of resources is likely tohave an advantage, since reduced competition allows purchasing target at a lower price.
Models incorporating imbalance in financial resources and growth prospects are often used
to explore acquisition likelihood, as well as synergy potential between merging firms. Palepu(1986) provides empirical evidence that imbalance in financial resources and growth
opportunities of a firm increases its probability of becoming an acquisition target.
Myers and Majluf (1984) developed a model in which high-liquid acquirers merge
low-liquid targets with growth potential. In their model, merger has a potential for value
creation when one firm’s excess liquid resources completely cover the other firm’s investment
needs. Liquid resources are valuable since allowing firm to avoid undesirable externalfinancing, e.g. issuing of stocks in periods when firm is undervalued. The model assumes
5asymmetric information (management has information that investors do not have; e.g.
management knows more about the firm’s value). Under asymmetric information, low-liquidfirm not willing to issue stocks may not undertake all beneficial investment opportunities.
Therefore, such firm has a potential to increase its value by merging with high-liquid partner.
Thus, the resource availability of one company can be combined with investment needs of theother in order to advance shareholders’ value. We omit Myers and Majluf’s assumption
regarding the specific direction of complementary where high-liquid acquirers purchaselow-liquid, high-growing targets. Thus, the complementary in liquid resources and growth
opportunities is proposed in both ways; high-liquid acquirers purchase high-growing targets
or high-growing acquirers merge with high-liquid targets.
H1a: Merger between one party with higher liquidity and the other with higher growth
will have a positive effect on acquirer’s shareholders return at merger announcement.

The other source of synergy can arise from the difference in financial leverage of merging
parties. If one of the merging parties is leveraged and the other has unused debt capacity, thevalue of tax savings on incremental debt could provide that both parties gain from exploiting
unused debt capacity ( Sudarsanam, Holl and Salami, 1996). Bruner (1988) found that targets
prior to merger have significantly more leverage than their acquirers and the control sample,
though his result does not support hypothesis that the market value of merger is affected bythis type of financial discrepancy.
According to Jensen’s (1986) free cash flow hypothesis, high level of free cash flow andlow debt can create conflict between management and shareholders over payout of the freecash, since managers rather tend to invest excess cash flow in projects with negative netpresent value (especially oriented towards growth) than pay it to shareholders. Thus,
additional debt creation through merger with leveraged target would constrain free cash flow
and managerial discretion.
6

H1b: Purchasing target with higher financial leverage will have a positive effect onacquirer’s shareholders return at merger announcement date.

Empire Building Theory
Empire building theory has origins based on separation of ownership and control in
corporation. Management in a public company act as agent for shareholders, performing withdelegated authority on shareholders’ behalf. Agency problems can occur when managers serve
their own interest that is not aligned with shareholders’ interest. Evidence of interest conflicts
can be perceived through large compensations, excessive perquisites or offensive growth,often referred to as “empire building”. Model first proposed by Baumol (1967) suggests thatmanagement pursue growth maximization at the expense of shareholders’ wealth. Morck,
Shleifer and Vishny (1990) for the sample of US acquisitions provide evidence that acquirer’s
returns decrease when company acquires fast growing target, result consistent with hypothesisthat management expropriate shareholders’ value by pursuing growth maximization.
Previous studies of Japanese management commonly indicate internal growth as theirpreference in comparison to American management (Odagiri and Hase, 1989). This difference
is attributed to the practice of long-term employment, management attitudes to retain
employees and employees’ loyalty to company. Nevertheless, the recent surge of mergers inJapan requires the reexamination of underlying factors that shape merger activity.

H2a: Purchasing fast growing target will have a detrimental effect on acquirer’s
shareholders’ return at merger announcement date.
However, this detrimental effect could be mitigated if acquirer has ownership in target prior tomerger.
H2b: The detrimental effect of purchasing fast growing target will be weaker if acquirer
has greater ownership in target prior to merger announcement.
7

Non-Rationality Perspective
Process Theory
Historically, scholars have commonly adopted perspective that portrays managerial
decision to merge companies based on rationality assumption. According to non-rationality
notion of process theory, individuals have limited ability to process information, leading toincomplete evaluations and tendency to make irrational decisions. The scarcity of empiricalevidence in respect to process theory perspective can be seen as caused by managerial
common attempt to rationalize their actions (Trautwein, 1990). In this study we examine theimplications of management overconfidence, denoted as hubris (Roll, 1986).
Roll (1986) argues that management on the basis of previous success mistakenly
overestimates synergy potential and overpays target, resulting in the decrease of acquirer’s
shareholders wealth. Even in mergers with synergy potential, management can still commit
valuation errors. Thus, hubris can be viewed as factor affecting the size of bid, rather than amotive for merger and can be present in all types of mergers; value creating and value
destroying (Mueller and Sirower, 2003).
Contrasting empirical evidence suggests that performance has a negative relationship withrisk taking decisions; poorly performing organizations tend to engage in riskier projects thanwell-performing organizations (Singh, 1986). Morck, Shleifer and Vishny (1990) provide
evidence that better-performing U.S. acquirers also make better mergers.
However, according to Roll’s (1986) hypothesis, successful managers are more prone tooverconfidence on the basis of previous success. Thus, if Roll’s theory holds, we can expectthat well-performing bidders might overestimate the value of merger and overpay target.

H3: Acquirer’s past performance will be negatively related to shareholders’ return atmerger announcement date.

8

Rescue Merger
It has been suggested that mergers in Japan sometimes have “rescue motives”; whereacquirers merge business partners in financial distress. These mergers could increase value if
the benefits of continuing business relationship are larger than the costs associated withrescuing target. On the other hand, if rescue merger is forced by regulatory agencies or banks,
the effect on acquirer’s shareholder wealth could be detrimental. Kang, Shivadasani andTakeshi (2000) provide empirical evidence that rescue mergers in Japan during 1977-1993
resulted in negative, statistically significant market reaction. Lang, Stulz and Walking (1989)
examine hypothesis that more value will be created when well-performing acquirers take overpoorly-performing targets. Their findings for U.S. mergers suggest that financial market
rewards well-performing firms acquiring poorly-performing targets.

H4: If merger with poorly performing target creates less value, we expect that target’s
past performance is positively related to acquirer’s shareholders return at merger
announcement.

METHODOLOGY

Sample and Data
We identify merger events from M&A Data Book for period 1993 to 2002 and MAAR
magazines from 2003 to 2005. The final sample consists of 62 domestic merger events
between stock listed companies that had the announcement date in the period 1993 to 2005.
Following previous studies (Yeh and Hoshino, 2001), financial industry mergers are excluded
due to different accounting practices. Mergers in which acquirer purchases two or moretargets during one year are screened out since this would represent confounding event with9

difficulty to measure the effect of stock price’s changes. Mergers in which parent acquires
already owned subsidiary are also eliminated since they represent cases of legal statuschanges rather than merger in its pure form. Since stock prices for targets are not available,
the final sample consists of 62 acquirers for which we could obtain daily stock prices from
Toyo Keizai Kabuka CD-ROM 2002, 2005 and Yahoo.jp finance. Accounting and ownershipdata are sourced from Nikkei NEEDs CD-ROM 2006, various issues of Nikkei Kaisha
Nenkan and Kigyo Keiretsu Soran.

Event Study Methodology
In order to access the market reaction at merger announcement we use traditional event
study methodology as proposed by Brown and Warner (1985). The price change at merger
announcement is referred to as abnormal return, calculated as the difference between theobserved return of the security and the predicted (normal) return that would occur if themerger was not announced. This can be mathematically expressed as follows:u it = Rit − (αˆ i + βˆi Rmt )(1),

where u it is abnormal return of acquirer security on day t, R it is daily return of acquirer
security on day t, R mt is the daily return of Topix on day t, α̂ and βˆ are estimatedparameters from the market model Rit = α i + β i Rmt + eit(2).

The estimation period used in this paper is 180 days, from 211 days before the merger
announcement date to 31 days before the merger announcement. The abnormal return iscalculated on the basis of estimated parameters from the market model for test period from 30
days before the merger announcement date to 60 days following merger announcement date.
The average abnormal return for N securities on a common day t is calculated as follows:N

AAR t = (∑ u it ) / N

(3).

i =1

10

T

Cumulative abnormal returns up to date T are calculated as: CAR T = ∑ AARt

(4).

t =1

In order to access statistical significance, average abnormal return on day t is standardized
by its standard deviation; the standard deviation is estimated from the initial 180 days
time-series of average abnormal returns. The standardization procedure insures that abnormal
returns are identically distributed, while time-series of average abnormal returns provide
cross-sectional independence in the security-specific abnormal returns across time. The test
statistic for any event day t is

AAR t / Sˆ ( AARt )(5)t = −31

whereSˆ ( AARt ) = ( ∑ ( AARt − A ) 2 ) / 179 (6)t = −210A=

1 t = −31
∑ AARt
180 t = −210

(7)

For tests over the multi-day intervals ( t1 , t 2 ) , the test statistics is the ratio of the cumulative
mean abnormal return to its estimated standard deviation, given by
t2

t2

t =t1

t =t1

1

∑ AARt /(∑ Sˆ 2 ( AARt )) 2

(8).

Dependent Variable
As dependent variable we use Cumulative Abnormal Return (CAR) from 3 days prior themerger announcement to 1 day after, as employed in previous study (Yeh and Hoshino, 2001).
In order to check for robustness we also use as dependent variable CAR from 5 days prior tomerger announcement to 2 days following the announcement.

Independent Variables
To evaluate the effect of merging partners’ liquidity-growth complementary (H1a) we use
the product of (Acquirer’s Liquidity – Target’s Liquidity) and (Target’s Growth – Acquirer’s
Growth) as proposed by Sudarsanam, Holl and Salami (1996). The interaction term is positive11

in case when one party is more liquid and the other has higher growth. Liquidity is measured
as the ratio of working capital and total assets in the year before merger announcement.
Growth is estimated as three years average sales growth prior to announcement year. We also
tested H1a as proposed by Myers and Majluf (1984), by using dummy variable that equals 1
when high-liquid acquirer purchases high-growing, low-liquid target (high/low defined asabove/below the respective acquirers’ and targets’ medians), but the coefficient is not
significant.
The second independent variable is the difference between target’s and acquirer’s financial
leverage (H1b). We define leverage as the ratio of total liabilities and shareholders’ equity inyear before merger announcement.
In order to test H2a and H2b we use target’s growth, as well as the interaction term oftarget’s growth and dummy variable that equals 1 when acquirer owns more that five percent
of target’s outstanding shares in year before merger announcement. We use five percent
ownership level since, for listed companies, disclosure of ownership above this level isrequired according to shareholders’ rules.
Bidder’s past performance (H3) and rescue merger (H4) we measure as three years industry
adjusted ordinary income growth of acquirer and target respectively.

Control Variables
Commonly used variable in mergers and acquisitions research is the relative size ofmerging parties. The relative size of target to acquirer is usually used as a proxy for gains
from economies of scale and scope. Asquith, Bruner and Mullins (1983) found for sample ofU.S. mergers that acquirers’ returns are positively related to relative size of target andacquirer; a bid for a target half the acquirer’s size produced 1.8 percent larger return
comparing to bid for a target one tenth of acquirer’s size. Villalonga and McGahan (2005) on
the basis of Hennart’s digestibility theory argue that merger is more complex to pursue when12

size of partners is more balanced, since it is difficult for them to become digested by the otherparty. We measure relative size as log (Total Assets of Target/Total Assets of Acquirer).
Based on previous literature, we also include acquirers’ large block-holders andmanagement ownership as control variables (Kang, Shivadasani and Takeshi, 2000; Yeh andHoshino, 2001). In large public companies, ownership components such as large
block-holders and management ownership can be used in order to mitigate agency problems.
According to Prowse (1992), large block-holders are usual in Japan with top five shareholders
owning on average 33 percent of firm’s outstanding shares. Such concentrated ownership can
provide strong incentives for institutional investors to monitor management. We measureinstitutional ownership as a percentage of outstanding shares owned by top ten shareholders at
the end of the year prior the merger announcement. Similarly, we define management
ownership as the percentage of outstanding shares owned by top management at the end ofyear prior to merger announcement date.
Historically, M&A have not been attractive tools for business restructuring in Japan. The
significant increase of merger activity is evident following “Tokyo Big Bang” reforms in
April 1998, focused on deregulation of financial markets, as well as requirements fortransparency in accounting practices and corporate governance. The increase in the number ofdeals was especially prominent in 1999 due to the revision of corporate laws; exchange(transfer) of shares for creating a 100 percent owned subsidiary was allowed in the majoramendment. The changes in policy and government attitude could result in mergers following
1998 as differently perceived by market. We use dummy variable equal to one for mergers
after 1998 in order to test for effects of government policy changes.

13

ANALYSIS AND RESULTS

Univariate Analysis-------Insert Table 1 about here------Table 1 shows abnormal returns cumulated during specific window intervals. The results
suggest significantly positive market reaction prior to merger announcement (-5,-1). Also,
market reacts favorably in various window intervals surrounding the merger announcement. If
we examine the pattern following the deal announcement, cumulative abnormal return
becomes significantly negative (1, 5). Kang, Shivadasani and Takeshi (2000) investigate
mergers from 1977 to 1993. Their findings confirm positive abnormal returns in the shortwindow around the deal announcement. Yeh and Hoshino’s (2001) study for 1981-1998 show
statistically significant losses around announcement date.
In order to preliminary access the effects of merging parties’ pre-merger characteristics
on acquirer’s announcement returns, we bifurcate the sample as shown in the Table 3. We
compare the five-days ( t = -3 to t =1) announcement return across pre-merger characteristics
of merging parties. The mean value of bidders’ CAR(-3,1) is 1.36 percent, statisticallysignificant at 10 percent level. Further, we try to answer the question what characteristics ofmatched firms affect the return more positively.
------Insert Table 3 about here------Table 3 represents the five-days mean acquirers’ return for various sub-samples of firms,
t-tests of the difference in means across sub-samples and chi-squared tests for the differencein CAR percent positive.
We check whether the relative size of merging parties affects acquirer’s shareholders’return. After comparing return of acquirers with relatively small target (ratio less than 50% of
acquirer’s size) to return of acquirers with relatively large target (ratio larger or equal to 50%
of acquirer’s size), we found no difference across sub-samples. The cumulative abnormal
14

returns are 1.17 percent and 1.48 percent respectively. These differences are not statisticallysignificant. In contrast, Asquith at al. (1983) found that the relationship of CAR and size ratiofor U.S. mergers is significantly positive, suggesting that merger with larger target advances
value of acquiring firm.
As a preliminary observation on the effects of liquidity–growth differences, we divide
the sample into sub-categories according to positive and negative Liqdif_Grdif variable. For a
sub-group (36 companies) with positive value, the mean acquirer’s return is 3.05 percent
statistically significant at 1 percent level. The mean acquirer’s return for negative value
sub-category (26 companies) is -0.98 percent, statistically insignificant. The t-test ofdifference in means significantly differs from zero at 5 percent level, suggesting that mergers
with either partner being more liquid and other having higher growth are attractive andfavorably evaluated by market in comparison with deals by partners without such discrepancy.
Statistically significant Chi-squared test for the difference in CAR percent positive at 5
percent level confirms that mergers by parties with growth-liquidity difference are attractive
options for business restructuring. Similarly, findings by Sudarsanam et al. (1996) for United
Kingdom mergers during 1980 to 1990 suggest that combination of firms with acomplementary fit in terms of liquid resources and growth opportunities enhances
shareholders’ value.
Second, we separate the sample according to the difference in financial leverage between
target and acquirer. In particular, we test whether the possibility to infuse capital intoleveraged target can be regarded as a source of gain for acquirer. The mean acquirer’s returnfor a sub-group with positive leverage difference (38 companies) is 1.74 percent, weakly
statistically significant at 10 percent level. Sub-group with a negative leverage difference (24companies) has mean acquirer’s return of 0.75 percent, statistically insignificant. Acquiring
target with higher financial leverage than bidder is relatively attractive in comparison tomerging target with lower leverage. However, the t-test of difference in means is not15

statistically significant, neither Chi-squared test for the difference CAR in percent positive.
Slusky and Caves (1991) report significant positive relationship between leverage difference
and bid premium in U.S. merger market.
Third, in order to access the effect of target’s growth on acquirer’s return, we divide
sample into mergers with target growing faster than median and mergers with target growing
slower than median. The mean acquirer’s return of mergers with target growing faster than
median is 1.59 percent, weakly statistically significant (p=0.108). For mergers with target
growing slower than median, the mean return is 1.12 percent, statistically insignificant. Bothsub-groups have positive acquirers’ return above 1 percent, suggesting that in Japanese
domestic mergers, target growth is not factor significantly influencing acquirers’ return. T-testshows statistically insignificant difference, confirming the previous finding. However,Chi-squared test significant at 5 percent level indicates that mergers with fast-growing targets
are relatively more attractive, since large percent of acquirers in fast-growing target
sub-sample have positive CAR (67.7%). This finding implies that in Japanese domestic
mergers ‘buying growth’ does not affect negatively firm’s value, as opposite to prediction of
our Hypothesis 2a. Our result contrasts with Morck et al. (1990) finding for U.S. merger
market that suggests the destructive effect of ‘buying growth’ on firm’s value.
Fourth, we bifurcate acquirers on sub-sample with ordinary income growth higher thanindustry average and ordinary income growth lower than industry average in order to examine
Hypothesis 3. We use ordinary income growth as a proxy for the quality of past performance.
Acquirers with past performance higher than industry average have statistically insignificant
mean return of 0.75 percent, while acquirers with below-industry performance have mean
return of 1.27 percent, also not significant at conventional level (p=0.12). The pattern ofacquirers’ returns across sub-groups is as predicted in Hypothesis 3. However, insignificant
t-test and Chi-squared test do not support the predicted difference in returns across two
sub-groups. The more explicit regression analysis examining the effect of acquirer’s past16

performance on acquirer’s stock returns indicates that we cannot reject Hypothesis 3.
Finally, we test the impact of target’s past performance as a proxy for rescue mergers inJapan. For acquirers merging targets with above-industry performance, the mean return is0.48 percent, statistically indistinguishable from zero. On the other hand, acquiring
below-industry performing target resulted in statistically significant mean return of 1.99
percent. According to t-test and Chi-squared test, the difference across sub-samples is not
significant. However, above finding implies that acquiring poor-performing target does notaffect negatively acquirer’s return at merger announcement. At contrary, Kang’s et al. (2000)
study for 1977 to 1993 period indicates significantly negative effect of rescue mergers on
acquirers’ shareholders’ value. Also, study by Inoue and Kato (2003) during 1990 to 2002
signifies negative impact of rescue merger on shareholders’ return. It is possible that our result
differs due to use of different measurement. We proxy rescue merger with target’s industry
adjusted ordinary income growth, while in previous studies data on rescue mergers are basedon information from newspapers.

Multivariate Analysis
In this section we show results of regression analysis using as the dependent variable
five-days cumulative abnormal return (t= -3 to t=1). All models include as control variables
relative size of merging partners, bidders’ management ownership, bidders’ top ten
block-holders’ ownership, year dummy equaling 1 for mergers after 1998.
-------Insert Table 4 about here------Table 4 shows the results of Model 1 containing only control variables, Model 2 withvaluation theory variables (H1a & H1b) added, Model 3 with empire building theory variables(H2a & H2b) added and the Model 4 with all variables (H3 & H4) included. The F test ofmodel significance is not significant for Model 1, and significantly increases as the main
variables are added. The first two hypotheses (H1a & H1b) test the impact of differences in17

merging parties’ financial resources allocation on acquirer’s returns and predict the positiveeffect of respective differences on acquirer’s firm value at announcement. The coefficients on
Liqdif_Grdif and Levdif are positive and significant in all models; the results support H1a &H1b.

In H2a we predict negative effect of ‘buying growth’ behavior on acquirer’s return. We

argue that prior ownership of acquirer in target will act as a factor buffering this detrimental
effect (H2b). The coefficient on Tgrowth is negative, but insignificant in all models. Thus, we
do not find support for detrimental effect of buying growing target in Japanese domestic
mergers. Moreover, positive and significant coefficient on Tgrowth_Own5 in all models
indicates that buying growing target is beneficial for acquirers with prior ownership in target
above five percent. In H3 we examine the effect of acquirer’s industry adjusted past
performance on returns at announcement. The logically expected effect would be that market
favors mergers by above-industry performing acquirers, since such firms have already proven
their ability to make good business decisions. However, the coefficient on Bperf is negativeand significant, implying that market is suspicious at announcement of mergers by successfulacquirers. In Hypothesis 4 we test for the impact of target’s past performance on acquirer’s
return. The coefficient on Tperf is negative and insignificant. Thus, the result does not support
the prediction that acquiring well-performing target is perceived favorably by market.
-------Insert Table 5 about here------In order to check for robustness, we estimate the models using as the dependent variable
8-days cumulative abnormal return (t=-5 to t=2). Table 5 shows that results are unaltered,essentially supporting the same hypotheses.

18

DISCUSSION AND CONCLUSION
Domestic mergers in Japan have expanded rapidly in recent years, in terms of both, thenumber and the value of deals. Considering the rising prominence of mergers in Japan,
important questions that can be posed are how mergers affect firm’s value, as well as what are
the underlying sources of value gains and losses.
Earlier studies on Japanese mergers commonly focus on implications of keiretsu
groupings, main bank, rescue mergers and cross-corporate shareholding (Kang et al, 2000;
Yeh and Hoshino, 2002; Schaik and Steenbeek, 2004). However, due to recent deregulationof Japanese financial markets, currently increased merger activity could be possibly attributed
to different factors from previously stated.
The key objective of this study is to potentially add to understanding of mechanisms
through which firm’s value is created and destroyed in Japanese domestic mergers.
Our findings indicate that value is advanced in mergers when one partner has higher
liquidity while the other has higher growth prospect, due to ability of liquid party to financepartner with growth opportunity. Also, acquiring target with higher financial leverage canbecome a source of gain, possibly due to tax savings on incremental debt for newly merged
entity or decreasing the level of acquirer’s free cash flow, therefore lessening managerial
discretion and possibilities for conflict between management and shareholders (Jensen, 1986).
Thus, differences in financial resources allocation pattern may provide a source of valueenhancement. This view supports Harrison et al. (1991) argument that uniquely valuable
synergy might be generated when differences exist between resources of merging parties.
Such differences are difficult to perceive and emulate by potential competitive bidders due toasymmetric information, therefore lessening the probability of competitive bids and an
auction. Similarly to our findings, Sudarsanam et al. (1996) study for United Kingdom
provide empirical evidence that combination of firms with a complementary fit in terms ofliquid resources and growth opportunities elevates shareholders’ value.
19

Further, our study examines managerial objectives in terms of ‘buying growth’. Extant
research in U.S. and U.K. suggested that management compensation depends on the size offirm (Firth, 1980). Study by Morck et al. (1990) provides evidence that U.S. market perceives
unfavorably mergers with rapidly growing targets. They also found the negative effect ofdiversifying mergers on shareholders’ return. Nevertheless, in our sample there are only eightcases of mergers between parties belonging to different industries. This suggests that mergers
in Japan are largely concentrated in adjacent business field, where newly acquired business iscomplementary to the acquirer’s main business in order to strengthen utilization of existing
resources, market power and economies of scale and scope. Thus, growth throughdiversifying mergers in Japan is not popular as in the case of U.S. merger market. Mergers
concentrated in related field of business are compatible to Japanese management preference
for internal growth, possibly occurring when internal growth efforts are hindered by internal
resource constraints (Odagiri and Hase, 1989). Therefore, tendency of Japanese management
to merge complementary business versus motivation of American management to growthrough conglomerates might be reason for different result we obtain in terms of buying
growth. Japanese market does not perceive unfavorably buying growth due to promising
benefits stemming from economies of scale/scope and increased market power throughmergers between same industry companies.
Further on, we explore the relation between the quality of acquirer’s past performanceand stock return. Morck et al. (1990) provide evidence that U.S. market favors mergers bywell-performing acquirers, in contrast to our findings for Japanese mergers.

In Japan,stockholders’ return is lower following the announcement of mergers by well-performing
firms than by poor-performing firms. This finding indicates that well-performing acquirers
might have overoptimistic expectation on a particular deal. Our finding is consistent withhubris theory by Roll (1986), indicating that management of well performing firms is prone tooverconfidence, resulting in overvaluation of merger and detrimental effect for acquirer’s
20

shareholders.

Since large scale mergers in Japan are often described as friendly deals

between firms with established relationships (Kestner, 1991; Kruse et al, 2006) it can beargued that problem of winner’s curse combined with hubris is less likely to occur in theJapanese market. However, due to lack of market for corporate control, management in Japando not face monitoring by external market forces. Thus, increase in merger activity byoveroptimistic management is quite possible.
Another factor we examine is the effect of target’s past performance as a proxy forrescue merger.

Finding for domestic mergers by Kang et al. (2000) indicates destructive

effect of rescue merger on acquirer’s value at announcement. In contrast, our result does notconfirm negative impact of merging poor-performing target. Moreover, mergers withpoor-performing target resulted with higher return. It is possible that nature of rescue merger
is changing with deregulation and decreasing the role of main bank. Previously focused on
costly salvation of distressed target under the pressure of main bank, the nature of rescue
merger could shift to supporting partner in cases when continuing business relationship isworthwhile for acquirer. Otherwise, our result may differ due to use of different measurement.
In conclusion, our findings support the view that focus on specific resources combination
between acquirer and target could become essential for shareholders’ value upturn. In
particular, financial resources spillover between merging companies has a potential togenerate value enhancing synergy. Future research could access the impact of differences inresources on long-term performance of a merger. We find that well-performing acquirers
achieve lower stock return at merger announcement, indicating that successful managers
might be overconfident in their valuation of target firms. This evidence requires further
consideration especially through examining long run performance of mergers by above
industry performing acquirers. Our results are a subject to constraints due to, most importantly,
short-run event study methodology. In order to access the full impact of complex events
such as mergers, it should be accounted for longer-term measurements as well.
21

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25

Total Deals

Domestic Deals

3000
2500
2000
1500
1000
500

19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
20
0
06 2 4
0
/( 0
01 5
-0
6)

0

Figure 1. Number of Total Mergers Vs. Domestic Mergers
Note: Total mergers account for the sum of cross-border mergers by Japanese acquirers,
domestic mergers by foreign acquirers and domestic mergers by Japanese acquirers.

Figure 2. Theories of Merger Motives by Trautwein (1990)

26

Table 1. Cumulative Abnormal Returns (CARs) for Various Windows
Window Interval
AD – 5 to
AD – 3 to
AD – 1 to
AD – 1 to
AD – 3 to
AD – 5 to
AD – 5 to
AD – 10 to
AD – 20 to
AD – 30 to
AD – 30 to
AD + 1 to
AD +1to

Mean CAR(%)

t-statistic(Two-tailed)

1.22
0.90
1.64
1.19
1.36
1.51
0.84
0.51
1.39
2.17
4.14
-0.31
-1.28

1.705*
1.622
3.605***
2.148**
1.892*
1.661
0.719
0.347
0.679
0.865
1.350
-0.569-1.783*

AD – 1
AD – 1AD
AD + 1AD + 1AD + 2AD + 5AD + 10
AD + 20
AD + 30
AD + 60
AD + 3AD + 5***,**,* denote statistical significance level at 1%, 5%, and 10% respectively

27

Table 2.

Variable Definitions

Hypotheses

Variable Name

Variable Definition

Liquidity(Current Assets – Current Liabilities)/Total Assets in theyear before merger AD year

GrowthAverage annual sales growth in the 3-year interval before
merger AD year

Leverage

Total Liabilities/Equity in the year before merger AD year

LiqdifBidder’s Liquidity -Target’s Liquidity

Grdif

Target’s Growth -Bidder’s Growth

H1a

Liqdif_Grdif

Product of LIQDIF and GRDIF

H1b

LevdifTarget’s Leverage –Bidder’s Leverage

Own5

1 if bidder owns more than 5% of target’s outstanding shares
before the AD year;0 otherwise

H2a

TgrowthTarget’s Growth

H2b

Tgrowth_Own5

Product of TGROWTH and OWN5

H3

Bperf

Bidder’s 3-year Industry Adjusted Ordinary Income Growth

H4

Tperf

Target’s 3-year Industry Adjusted Ordinary Income Growth

Control
Variables
Rsize

Log(Target’s Assets/Bidder’s Assets) in the year prior tomerger announcement

Block

Sum of shares owned by top 10 acquirer’s shareholders in theyear before merger announcement

Mown

Acquirer’s top management ownership of outstanding sharesin the year before merger announcement

Ydummy1 if the announcement date is after 1998; 0 otherwise

Bankruptcy

Log(Number of Bankruptcies in the year before merger
announcement)28

Table 3.

Sample Divided According to Firms’ Pre-Merger Characteristics for CAR (-3,1)

Pre-Merger

Number of

Mean CAR(%)

t-Test of

Chi-Squared

Characteristics

Observations && (p-value)

Difference

Test ofin Means

Difference in % > 0(% of CAR positive)
24

1.17

t=-0.18

χ 2 = 0.01

(38.7)(0.31)(0.85)(0.906)38

1.48(61.3)(0.19)

36

3.05***

t=2.57**

χ 2 = 6.23**(66.6)(0.010)(0.0125)(0.0126)

26

-0.98

(34.6)(0.312)38

1.74*

t=0.58χ 2 = 2.84

(44.7)(0.101)(0.557)(0.091)24

0.75(66.6)(0.569)Tgrowth faster

31

1.59

t=0.29χ 2 = 5.25**

than Sample Median(67.7)(0.108)0.77(0.022)Tgrowth slower

31

1.12

than Sample Median(38.7)(0.39)

Bperf higher than

32

0.76

t=-0.75

χ 2 = 1.07

Industry Average(46.8)(0.45)

0.454(0.300)

Bperf lower than

30

1.27

Industry Average(60)(0.12)

Tperf higher than

26

0.48

t=-0.92

χ 2 = 0.19

Industry Average(50)(0.643)0.36(0.665)Tperf lower than

36

1.99*

Industry Average(55.5)(0.099)Rsize > 0.5
Rsize < 0.5
Liqdif_Grdif > 0
Liqdif_Grdif < 0Levdif> 0
Levdif < 0***,**,* indicates significance at 1%, 5% and 10% respectively.

29

Table 4.

Dependent Variable Cumulative Abnormal Return CAR(-3,1)

Variable

Hypotheses(1)

LiqdifGrdif
Liqdif_Grdif
LevdifTgrowthTgrowth_Own5

H1a
H1b

(2)

(3)

(4)

-0.039-0.037-0.045(0.87)(0.81)(0.92)-0.007

0.002

0.053

(0.24)(0.04)(0.59)

0.365

0.335

0.340

(3.24)***(3.08)***(2.60)**

0.00030.00040.0005(2.18)**(3.61)***(3.79)***-0.085-0.111(0.53)(0.62)

0.974

0.988

(3.14)***(3.03)***

0.003

0.008

(0.22)(0.49)

H2a
H2b

Own5
Bperf

H3

-0.008(2.75)***

Tperf

H4

-0.002(1.48)

Rsize
Block
Mown
Year (After 98)
Constant-0.013

0.012

0.011

0.014

(0.51)(0.43)(0.38)(0.49)

0.034-0.013-0.027-0.028(0.58)(0.28)(0.57)(0.56)-0.0450.0002-0.030-0.039(0.53)(0.03)(0.37)(0.45)

0.044

0.043

0.044

0.047

(2.73)***(2.77)***(2.81)***(3.10)***-0.023-0.012-0.001-0.004(0.80)(0.49)(0.04)(0.15)

62

62

62

62

0.122

0.275

0.333

0.361

1.98

2.52 a2.27 a2.08 aObservations
R

2

F(1) Absolute value of t statistics in parentheses. (2)***,**,* indicates significance
at 1%, 5% and 10% respectively. (3)ap < 0.05

30

Table 5.

Dependent Variable Cumulative Abnormal Return CAR(-5,2)Variable

Hypotheses(1)

LiqdifGrdif
Liqdif_Grdif
LevdifTgrowthTgrowth_Own5

H1a
H1b

(2)

(3)

(4)

-0.020-0.018-0.029(0.49)(0.42)(0.64)

0.049

0.044

0.064

(1.37)(0.86)(0.81)

0.260

0.240

0.214

(2.65)**(2.42)**(1.76)*

0.00030.00040.0005(2.56)**(2.99)***(3.09)***-0.043-0.043(0.26)(0.24)

0.964

0.975

(2.10)**(2.01)**

0.003

0.011

(0.18)(0.56)

H2a
H2b

Own5
Bperf

H3

-0.010(3.53)***

Tperf

H4

-0.001(0.65)

Rsize-0.021

0.001

0.002

0.011

(0.85)(0.05)(0.07)(0.35)

0.017-0.012-0.026-0.022(0.32)(0.24)(0.51)(0.42)-0.062-0.006-0.043-0.050(0.79)(0.08)(0.49)(0.56)

0.052

0.050

0.050

0.057

(3.39)***(3.30)***(3.32)***(4.00)***-0.014-0.0090.001-0.011(0.47)(0.31)(0.03)(0.37)

Observations

62

62

62

62

2

0.168

0.256

0.315

0.365

F

2.88 a2.28 a2.09 a2.13 aBlock
Mown
Year (After 98)
Constant

R(1) Absolute value of t statistics in parentheses. (2)***,**,* indicates significance
at 1%, 5% and 10% respectively. (3)ap < 0.

31

Table 6.

Descriptive Statistics and Correlations
Mean

S.D.

1

2

3

4

5

6

7

1

CAR(-3,1)

0.013

0.063

1

2

CAR(-5,2)

0.015

0.062

0.86

3

Liqdif0.035

0.220 -0.27 -0.16

1

4

Grdif

-0.022

0.131

0.03

0.16

0.03

1

5

Levdif-1.593

27.51

0.06

0.09

0.12

0.04

1

6

Rsize

0.736

0.546 -0.02 -0.04

0.16

-0.13

-0.40

1

7

Own5

0.112

0.319 -0.13 -0.13

0.07

-0.02

0.15

-0.15

1

8

Tgrowth-0.0010.071 -0.03

0.10

0.01

0.68

0.10

-0.23

-0.14

9

Bperf

-0.2101.581 -0.07 -0.13

-0.04

-0.02

0.05

0.14

0.13

10

Tperf

0.294

5.102

0.03

0.13

-0.05

0.56

-0.01

-0.25

-0.03

11

Year

0.645

0.482

0.33

0.38

0.002

0.09

-0.08

0.21

-0.05

12

Mown

0.034

0.075 -0.05 -0.08

-0.13

-0.25

0.02

0.14

0.03

13

Block

0.499

0.158

0.10

0.06

-0.32

-0.04

-0.06

0.12

0.06

8

9

10

11

1

12

8

1

9

0.02

1

10

0.21

-0.44

1

11

0.08

0.25

-0.12

1

12

0.02

0.11

-0.33

0.002

1

13

-0.01

0.15

-0.14

0.11

0.16

32

13

1

Table 7.
AD

The List of Merging Companies with Announcement Dates
Stock#

Acquirer

Stock#

Target29/1/1993

3861

Oji Paper Co.

3867

Kanzaki Paper Mfg.

12/11/1993

5233

Onoda Cement

5236

Chichibu Cement

24/12/1993

4010

Mitsubishi Kasei

4184

Mitsubishi Petrochemical

10/3/1994

5232

Sumitomo Cement

5235

Osaka Cement

27/7/1994

4103

Taiyo Sanso

4090

Toyo Sanso Co.

11/2/1995

1850

Nankai Construction Co.

1859

Tatsumura Gumi Co.

30/3/1996

3861

New Oji Paper

3862

Honshu Paper Co.

9/9/1996

4183

Mitsui Petrochemicals

4001

Mitsui Toatsu Chemicals

21/9/1996

5390

Ube Chemical Industry

5385

Calceed Co.

2/11/1996

1912

Misawa Cheramics Co.

4230

Misawa Cheramics Chemical Co.

25/2/19974509

Yoshitomi Pharmaceutical

4522

The Green Cross Corp.

5/5/1997

6311

Seirei Industry Co.

6115

Shoun Machine Tool Co.

25/7/1997

9987

Suzuken9933

Akiyama Inc.

3/10/1997

5233

Chichibu Onoda Cement

5231

Nihon Cement

9/2/1998

3941

Rengo

3883

Setsu

13/3/1998

8110

Kawasho Corp.

8055

Nozaki & Co.

28/3/1998

9101

Nippon Yusen K.K

9126

Showa Line Ltd.

18/4/1998

9896

Maruyoushi Co.

8121

Kokoku Housing Co.

21/8/1998

7526

Valeo Co.

9851

Hoshi Ito

2/9/1998

6448

Brother Ind.

8162

Brother Sales

28/10/1998

5001

Nippon Oil Co.

5004

Mitsubishi Oil Co.

21/11/1998

9104

Mitsui O.S.K Lines Ltd.

9105

Navix Line Ltd.

14/1/1999

2579

Kita Kyusyu C.C Bottling

2574

Sanyp C.C Bottling

23/1/1999

9894

Kyuko Pharmaceutical

7436

Unik Co.

11/2/1999

3868

Takasaki Paper Mfg.

3885

Sanko Paper Mfg.

1/3/1999

7270

Fuji Heavy Industry

8294

Chuo Subaru Inc.

24/3/1999

7248

Calsonic

7281

Kansei2/4/1999

7868

Kosaido Printing Co.

7924

Kansai Kosaido Co.

21/5/1999

2538

Chuyou2803

Marukin Shoyu

26/8/1999

6107

Amada Sonoike

6108

Amada Wasino

19/10/1999

4088

Daido Hokusan

4108

Kyodo Oxigen Co.

25/11/1999

8015

Toyota Tsusho

8069

Kasho

13/1/2000

1951

Kyowa Exeo

1842

Showa Technos

17/2/2000

5012

General Sekiyu K.K

5005

Tonen Corp.

23/3/2000

5728

Tokyo Tungsten

6126

Osaka Diamond Inc. Co.

23/3/2000

5391

Ask Corp.

5272

Asano Slate Co.Ltd.

33

27/3/2000

3863

Nippon Paper Ind.

3871

Daishowa Paper Mfg.

23/5/2000

1987

Hiroshima Kensetsu C.T

1746

Konwa Kensetsu

17/11/2000

4005

Sumitomo Chemical Co.

4183

Mitsui Chemical Ind.

22/3/2001

2114

Nihon Sugar Refining

2111

Fuji Seito

14/4/2001

5403

Kawasaki Steel Corp.

5404

NKK Corp.

8/5/2001

8199

Deo Deo

8161

Eiden

7/9/2001

7583

Tsusho Co.

7489

Ochi Sangyo Co.

17/9/2001

4535

Taisho Pharmaceutical

4508

Tanabe Seiyaku Co.

26/4/2002

1871

PS

1996

Mitsubishi Construction

13/6/2002

6421

Canon Aptex

6442

Copyer Co.

7/1/2003

4902

Konica Corp.

7753

Minolta Co. Ltd.

14/2/2003

6426

Sammy Corp.

7964

Sega Corp.

19/5/2003

1805

Tobishima Corp.

1861

Kumagai Gumi

12/7/2003

6933

Yuasa Corp.

6931

Japan Storage Battery Co.

10/10/2003

6712

Tamura Electric Works Ltd.

6710

Taiko Electric Works

25/2/2004

4503

Yamanouchi Pharmaceutical4511

Fujisawa Pharmaceutical

28/2/2004

3947

Dainippon Shigyo

3949

Nippon Hi-Pack

25/6/2004

7972

Itoki Krebio

9871

Itoki

10/7/2004

9204

Skymark Airlines

4697

Zero Inc.

8/12/2004

7254

Fuji Univance7295

IS Precission Machinery

1/2/2005

3877

Chuetsu Pulp&Paper

3864

Mitsubishi Paper Mills

4/2/2005

6473

Koyo Seiko Co. Ltd.

6206

Toyoda Machine Works

17/2/2005

7603

Mac House

7495

Leo Co.

1/4/2005

9719

Sumisho Computer Systems

7556

Sumisho Electronics Co.

10/9/2005

5989

Hirata Technical Co.

3425

Hongo Co.

14/9/2005

2001

Nippon Flour Mills Co.

2007

Fuji Flour Milling34