Wealth creation versus wealth redistributions in
pure stock-for-stock mergers1
Carlos P. Maquieiraa, William L. Megginsonb, * and Lance Nailc
a
University of Chile, Santiago, Chile
Terry College of Business, University of Georgia, Athens, GA 30602, U.S.A.
c
School of Business, University of Alabama-Birmingham, Birmingham, AL
35299, U.S.A.
b
Received 3 November 1995; revised 6 August 1997. Available online 27 July
1998.
Abstract
We examine wealth changes for all 1283 publicly traded debt and equity
securities of firms involved in 260 pure stock-for-stock mergers from 1963
to 1996. We find no evidence that conglomerate stock-for-stock mergers
create financial synergies or benefit bondholders at stockholders'
expense. Instead, we document significant net synergistic gains in
nonconglomerate mergers and generally insignificant net gains in
conglomerate mergers. Conglomerate bidding-firm stockholders lose; all
other securityholders at least break even. Convertible securityholders
experience the largest gains, due mostly to their attached option values.
Certain bond covenants are value-enhancing while leverage increases are
value-reducing.
Author Keywords: Conglomerate mergers; Stock-for-stock mergers; Bond
valuation
1. Introduction
Although finance theorists have examined corporate mergers from many
different perspectives, most of these models predict one of two primary
effects. Either mergers create net new wealth from operating or financial
synergies, or they redistribute existing wealth between stakeholder
classes. Though empirical support exists for most models, it has proven
difficult to examine wealth creation and wealth transfers in a single
analysis. Our study accomplishes this by examining the wealth changes of
all 1283 publicly traded debt and equity securities of a matched sample
1
of 520 companies involved in 260 pure stock-for-stock mergers from January
1963 through March 1996.
Pure stock-for-stock mergers offer an ideal opportunity to test for wealth
creation and/or wealth redistributions because there are no cash outflows
or asset changes. Thus, the sum of the market values of the merged firm's
securities should equal the sum of the market values of the merging firms'
securities (adjusted for overall market movements in financial asset
values), unless the merger creates net wealth gains or losses. If net
wealth is created by the capture of operating and/or financial synergies,
there should be an increase in the summed market values of the combined
firm's securities – and most or all of this ‘net synergistic gain' should
accrue to stockholders, the firm's residual claimants. Ravenscraft and
Scherer (1987), Bhagat et al. (1990), and Kaplan and Weisbach (1992)
generally predict that operating synergies will be created only in mergers
between firms in the same or related industries, and Healey et al. (1992)
document particularly strong performance improvements for mergers
involving firms with overlapping businesses.
Models predicting the creation of financial synergies, such as those
presented in Levy and Sarnat (1970), Lewellen (1971), Weston and
Mansinghka (1971), Williamson (1975), Amihud and Lev (1981), Stapleton
(1982), and Amihud et al. (1986) almost invariably assume that these
synergies are to be found only in conglomerate mergers, or mergers between
firms in different industries. Because conglomerate mergers, in general,
neither reduce competition nor provide operating economies of scale, it
is often assumed that these mergers do not yield any operating synergies
or create product or factor market power, though they may increase a firm's
debt capacity or create other types of financial benefits.2 Financial
synergies can arise from: (1) reduction of default risk (and thus
borrowing costs) by joining together firms with imperfectly correlated
cash flow streams, (2) diversification of equity risk for stockholders,
or (3) contracting efficiencies created by allowing managers to reduce
their employment risk by creating larger, less risky firms.
In contrast to synergistic wealth creation, wealth redistributions are
usually expected to occur when a merger merely changes the relative
riskiness of the cash flow streams of two or more securities. The
theoretical models of Higgins and Schall (1975) and Galai and Masulis
(1976) suggest that conglomerate mergers will lower equity values and
raise bond values (leaving total firm value unchanged), while Shastri
(1990) shows that these mergers can have many different effects, such as
wealth redistributions from stockholders to bondholders (or vice versa)
or within securityholder classes, depending upon the covariance between
the returns of the merging firms.3 To date, however, only Eger (1983) has
2
documented wealth redistributions between bondholders and stockholders;
studies by Kim and McConnell (1977), Asquith and Kim (1982), Dennis and
McConnell (1986), and Travlos (1987) show no significant redistributions.
Our empirical design, with its matched bidder and target firms and large
sample of senior securities, allows for more direct testing of these
wealth transfers.
We employ a new valuation methodology that is a modification of standard
event-study methodology. Our technique compares the actual post-merger
values of different security classes with the values that would be
predicted without a merger, and allows us to easily handle widely varying
merger completion periods. Since we collect price data for all publicly
traded nonconvertible preferred stock, nonconvertible bonds, and
convertible security issues of the firms in our sample, we are also able
to reexamine Dennis and McConnell's (1986) senior-security results using
only stock-for-stock mergers (rather than a mixture of cash and stock
transactions) and by using a much larger sample of matched bidder/target
pairs. Also, our sample of 602 bonds and 130 preferred stocks represents
the largest sample of senior securities employed in any published merger
study.
Though not the principal objective of this study, we also examine whether
transactions that increase corporate ‘focus' create more value than
transactions that decrease focus. As the term is defined and used in
Comment and Jarrell (1995) and John and Ofek (1995), focus-increasing
transactions are those that reduce the number of lines of business a firm
operates in, and increasing focus is consistent with the popular notion
of concentrating corporate activities on the firm's core competencies or
principal lines of business.4 In the context of our study, conglomerate
mergers tend to decrease corporate focus, while nonconglomerate mergers
(i.e., those between firms in the same or related industries) tend to
preserve or even increase it. By analyzing the differential wealth
creation and redistribution effects of conglomerate and nonconglomerate
mergers, we thus provide indirect evidence on the economic benefits of
focus-preserving (or focus-increasing) versus focus-decreasing mergers.
We find little evidence that conglomerate stock-for-stock mergers create
financial synergies, or that bondholders in these mergers benefit more
than either stockholders or bondholders in nonconglomerate mergers.
Instead, we find that real operating synergies are created by
stock-for-stock mergers, particularly in nonconglomerate mergers, and
that the increases in market value resulting from these synergies are
shared by almost all securityholder classes. Purely financial factors
(i.e., leverage changes) influence merger-induced security value changes,
but they are not dominant. On average, common stockholders experience
3
significant wealth increases which are greater for target than for bidder
firm shareholders. However, bidding firm stockholders in nonconglomerate
mergers experience wealth increases while bidding firm stockholders in
conglomerate mergers suffer significant wealth losses. Virtually all
classes of nonconvertible bondholders and preferred stockholders
experience net wealth increases, but these are dwarfed by the positive
unexpected wealth increases accruing to convertible bondholders in both
merger categories as well as to convertible preferred stockholders in
nonconglomerate mergers, which are driven by a relatively small fraction
of in-the-money securities that experience very large unexpected wealth
increases as a result of the merger.
The value changes documented in this study are not caused by changes in
systematic risk, since we find that the typical merged firm's actual
market-model beta is almost exactly equal to its weighted-average
predicted value. On the other hand, we find that the actual return variance
of the typical merged firm's equity (and assets) is significantly higher
than its predicted value. Regression analyses confirm that more total
wealth is created in nonconglomerate than in conglomerate mergers, that
the wealth gains accruing to bondholders decline after 1980, and that the
wealth change to bondholders is directly related to the presence of two
specific covenants in individual bond contracts. Wealth changes are also
inversely related to the merger-induced change in firm leverage for most
security classes. Although unsurprising – no securityholder would
voluntarily exchange a less-levered claim for a more-levered one without
compensation – this result has been heretofore undocumented.
Our study is organized as follows. Section 2 discusses the sample
selection criteria and presents summary statistics, and Section 3
presents our new valuation methodology. Section 4 presents the results
of the univariate difference in means and medians tests, as well as
supplemental multivariate regression tests for wealth redistributions
and synergistic gain creation. Section 5 concludes.
2. Data sources and sample selection criteria
Since this study's objective is to examine non-cash mergers that are
self-contained financial systems (no cash outflow to investors), we
select only pure stock-for-stock mergers and collect data on all
outstanding public and private security classes of the matched pairs of
merging firms. While we collect aggregate private debt and preferred stock
measures, these are not included in our valuation measures since we lack
market prices. However, our other bond and preferred stock estimates
suggest that these issues also increased in value after the merger. To
4
be included in our sample, a merger must meet the following selection
criteria.
1. The merger is initiated between January 1963 and December 1995 and is
completed by March 1996. The announcement of the intention to merge in
the Wall Street Journal Index (WSJI) is taken as the merger announcement
date, while the merger effective date is obtained from the Center for
Research in Security Prices (CRSP) database as the delisting date.
2. The merger is completed, so partial exchanges of stock are excluded
from the sample. (Roughly 6% of the combinations examined are ‘clean-up'
mergers, in which a controlling corporate parent purchases all the
subsidiary shares not already owned.)
3. Both firms are listed on either the New York Stock Exchange or the
American Stock Exchange, and daily stock returns are available on the CRSP
tapes.
4. Only common or preferred stock is used as payment to the target firm's
shareholders. We define the payment method as the one actually used, not
necessarily the method mentioned in the initial merger announcement. We
also use the actual exchange ratio in our computations of post-1977
acquired firm shareholder returns when this differs from the exchange
ratio announced initially. Since we are not performing a merger
announcement event study, our reliance on ex post data is not problematic,
as the actual terms of the merger are always known two months after
completion (the post-event measurement date we use).
5. There are no major contaminating events such as another merger
announcement, major asset sale or purchase, or large security issue during
the event period from two months before the merger announcement date
through two months after the effective date. This event period also solves
a measurement problem recently identified by Schwert (1996), who finds
that pre-bid stock price runup can often lead to a material increase in
the total cost of acquiring a given firm. This runup only begins to be
material one and one-half months prior to the bid announcement date,
however.
6. Capital structure, security issue, and line of business data are
available from the appropriate Moody's Manual for the bidder, target, and
combined firms.
The final sample contains 260 mergers, involving 520 firms. In 18 cases,
the same firm is the acquirer in two mergers, and there are two cases
(Colgate–Palmolive and Pepsico) of a firm being the bidder in three
5
completed mergers. We also eliminate roughly ten mergers with multiple
bidders. In addition to common stock, we also collect prices and issue
terms (maturity, coupon rate, amount outstanding, sinking fund payments
due, etc.) for all publicly traded securites of the merging and merged
firms. This process yields usable information on 78 nonconvertible
preferred stock, 83 convertible preferred stock (including 31 new
securities issued as a means of payment), 535 nonconvertible bond, and
67 convertible bond issues. Combined with the common stocks of the merging
firms, this yields a total sample of 1283 individual security issues.
Concentrating on successful pure stock-for-stock mergers that are
uncontaminated by contemporaneous security issues or other major
transactions clearly costs us in three important ways. First, cash
payments are more common than stock payments in U.S. mergers and
acquisitions, and this disparity has varied over time (see Comment and
Schwert, 1995). Second, research indicates that stock-for-stock mergers
have systematically lower offer premiums for target firm stockholders,
significantly negative abnormal returns for acquiring firm stockholders,
and lower net synergistic gains created.5 Third, focusing on successful
stock-for-stock mergers, which generally will be friendly as well,
eliminates many contested and resisted (hostile) transactions from our
study (see Huang and Walkling, 1987; Jennings and Mazzeo, 1993; Cotter
and Zenner, 1994). We trade off these drawbacks for a self-contained
system that encompasses all the financial effects of a specific, and
important, type of merger.
2.1. Classification of conglomerate and nonconglomerate mergers
Since we predict different wealth effects in conglomerate and
nonconglomerate mergers, we need a consistent method of classifying our
transactions into one of these two groups. Unfortunately, firms were not
required to disclose the detailed line of business data needed to compute
revenue-based Herfindahl measures of focus until 1977, and our sample
includes mergers from as early as 1963. We therefore classify mergers
based on a direct examination of the primary line of business listing for
each company in the appropriate annual edition of the Moody's Manual. If
the merging firms have the same primary line of business, the merger is
classified as nonconglomerate; if the two firms have different primary
lines, the merger is classified as conglomerate.
Although there is no ‘consensus' definition of conglomerate versus
nonconglomerate mergers in the finance or economics literature, we feel
our classification scheme is defensible, and a very similar technique
(matching by two-digit SIC codes from CRSP) has been employed by other
6
researchers, including Berger and Ofek (1995), Mann and Sicherman (1991),
Sicherman and Pettway (1987), and Smith (1990). Tighter definitions of
nonconglomerate mergers, or of ‘industry matches' for control samples
are employed by Eckbo (1983) and Eckbo (1985), Demsetz and Lehn (1985),
Morck et al. (1990) and Lang and Stulz (1994). Since, for our purposes,
it best to use a definition of conglomerate merger that embodies a
combination between truly dissimilar firms, we opt for a definition that
involves firms in different industrial groups (two-digit codes) rather
than firms that simply produce different product lines (three- or
four-digit codes). While this classification seems very imprecise,
Megginson et al. (1997) document that over 85% of the post-1977 mergers
in their sample that are classified as conglomerate (focus-decreasing)
or nonconglomerate (focus-preserving or focus-increasing) using this
simple SIC code/line of business screen would have been classified the
same way using the more sophisticated revenue-based Herfindahl measure.
Kahle and Walkling (1996) find substantial differences between the SIC
codes reported in CRSP and Compustat for the same firm. To examine the
potential impact of this industrial code ambiguity on our study, we
compare our merger classifications with those that would have been
assigned based solely on CRSP, solely on Compustat, and on the use of both
databases. We find that our classifications would have resulted in exact
matches with CRSP 81.2% of the time and 79.7% of the time with Compustat.
In 68.0% of the cases, all three classification schemes yield the same
classification. Our method agrees with CRSP in classifying mergers as
conglomerate 92.6% of the time, with Compustat 82.5% of the time; and all
three methods agree 74.6% of the time. Naturally, the nonconglomerate
classification agreement percentages are much lower, but this simply adds
a conservative bias to our analyses.
The time period distribution of the full sample, as well as of the
conglomerate and nonconglomerate merger subsamples, is presented in Table
1. Of the 260 stock exchange mergers in our sample, 135 are classified
as conglomerate and 125 as nonconglomerate. Consistent with Comment and
Jarrell (1995), the fraction of conglomerate mergers declines
monotonically over time.
Table 1. Distribution of sample mergers by type and by year of announcement.Distribution
of pure stock-for-stock mergers in the sample, by year of initial announcement, over
the period 1963–1995. The sample mergers are grouped as conglomerate or nonconglomerate
mergers based on whether the combining firms have the same primary lines of business
7
listings in the appropriate annual Moody's Industrial, Financial, or Utilities Manual.
Table 2. Relative size and leverage ratios for sample companies involved in
stock-for-stock mergers over the period 1963–1996 (announcement period ends in 1995,
but several mergers are completed in 1996).
The relative sizes of bidder and target firms are computed as the book value of the target
firm's total assets divided by the book value of the bidding firm's total assets in the
reporting period immediately prior to the announcement date of the merger. The leverage
8
ratios of the bidder, target, and combined firms are computed as the book value of total
debt divided by the book value of total assets.
The first section of Table 2describes the relative size of the bidder and
target firms in the full sample. On average (median), the target firm's
pre-merger equity market value is equal to 23.1% (18.2%) of that of the
bidder. The relative size of targets to bidders is much higher in
nonconglomerate mergers than in conglomerate combinations (27.1% mean and
22.8% median versus 19.4% and 15.6% mean and median). These differences
may reflect the ‘portfolio' acquisition strategy of conglomerate bidders,
as well as the practical fact that there may be only a limited number of
(relatively large) firms within an industry for a nonconglomerate
acquirer to bid for.
The second part of Table 2 shows that the firms in the full sample
have mean and median book value leverage ratios of 41.2%, with leverage
defined as the ratio of total debt to total assets. There is remarkably
little variation in leverage, either by type of merger or by whether a
firm is a bidder or a target. Target firms in nonconglomerate mergers have
an average (median) leverage ratio of 47.2% (44.0%), and acquiring firms
in both types of mergers have average leverage ratios of 41.2% (39.8% and
41.6% for conglomerate and nonconglomerate mergers, respectively), but
average leverage ratios for all other subsamples fall in the range of 41.8%
to 44.4%.
3. Methodology for computing security valuation
changes
Our objectives in this study require us to determine the wealth effect
of mergers on all of the publicly traded securities of the combining firms.
Unfortunately, the length of time it takes a merger to be completed ranges
from a low of 11 months to a high of 31 months for the mergers in our sample.
We thus develop a method of computing valuation changes that allows
adjustment both for overall market movements and for changes in the number
of securities outstanding over any appropriate holding period. Our
principal methodology for determining merger-related value changes is to
generate predicted post-merger valuations for all of the securities of
the merged firm. These are based on:
1. The pre-merger valuations of each outstanding security issue of the
merging firms,
9
2. overall market movements in matching asset prices during the event
period (t−2 months before merger announcement to t+2 months after the
effective date) between the merger announcement and effective dates,
3. any cash distributions made to securityholders during the event period,
and
4. any changes in the number of outstanding securities in a class due to
conversions, calls, sinking fund payments, or open-market repurchases.
Once predicted values are computed for each security issue, we compute
a valuation prediction error (VPE) for that security by subtracting the
predicted post-merger value from the actual post-merger value. While this
technique is just a variant of event-study methodology (which other
researchers have used to measure event-related senior security valuation
changes), we are unaware of any other study that uses precisely the same
procedure. The VPE is computed in essentially the same manner for all
security classes, and can thus easily be aggregated by class, firm, or
merger. The prediction methodology used for each security is described
below.
3.1. Generating predicted values for merged-firm common and
preferred stock
Of all the security classes for which predictions are generated,
merged-firm common stock is unique in that at least one (and sometimes
both) of the pre-merger common stocks outstanding invariably ceases to
exist after the merger effective date. Depending upon the accounting
treatment of the combination, either the acquiring firm's common stock
continues to trade after the merger or a new class of common stock of the
merged firm begins trading. In either case, the single common stock class
resulting from the merger should be equal to the market-adjusted summed
value of the merging firms' common stocks, plus any wealth transfers from
other securityholders or net synergistic gains. (From 1977 on, we can
reliably obtain exchange ratios for all of our sample mergers, allowing
us to compute separate VPEs for the common stock of both the bidder and
target firms, as well as for the merged firm's equity; we report these
individual results in Table 3 as well.)
10
Table 3. Valuation prediction errors for conglomerate and nonconglomerate
stock-for-stock mergers over the period 1963–1996 (announcement period ends in 1995,
but several mergers are completed in 1996).
Valuation prediction errors (VPEs) are computed as the percentage difference from
predicted market value for equity and debt securities from two months before the merger
announcement date through two months after the effective date of merger for individual
securities. Predicted market values are computed based on overall market movements in
the same classes of securities over the measurement period ( t−2 months to t+2 months),
and t-statistics (mean and percent positive) and Wilcoxon statistics (median) are
presented in parentheses. This table presents mean and median VPEs, and percent positive
statistics for 260 pure stock-for-stock mergers, classified according to whether the
combination is a conglomerate or a nonconglomerate merger. This classification is made
based on whether the combining firms have the same primary lines of business listings
in the appropriate annual Moody's Industrial, Financial, or Utilities Manual.
To adjust for market movements over our study period, we compute an index
value of the CRSP value-weighted return (including all distributions)
over the period beginning two months before the merger announcement
through two months after the merger effective date. We then calculate the
predicted merged-firm equity value, (Pred MVCS Comb)i, as the sum of the
beta-adjusted product of this index number and the equity value of each
the merging firms:
where (MVCS Bidder)i is the pre-merger market value of bidder firm common
stock in merger i, (MVCS Target)i the pre-merger market value of target
firm common stock in merger i, (CSIndex)i the cum-dividend geometric
return on the CRSP value-weighted index from two months before merger
announcement to two months after merger completion, B the market-model
beta for bidder firm, estimated over months t−62 to t−2, and T the
market-model beta for target firm, estimated over months t−62 to t−2.
The actual market value of the combined firm's common stock in merger i,
(MVCS Comb)i, is computed as the price per share of the merged firm times
the number of shares outstanding, plus the dividends per share paid on
the merging firms' stocks during the security holding period. We then
compute a valuation prediction error for the common stock in merger i,
(VPE CS Comb)i. This is our measure of the synergistic gain (or loss) and/or
wealth redistribution accruing to the common stockholders of the merging
firm as a result of the merger.
11
Beginning with preferred stocks, we find that multiple issues of a given
security class (preferred stock or debt) will often be traded before and
after the merger, though the number of securities outstanding might well
change due to redemption or partial conversion. We therefore compute
predicted valuations and VPEs for each individual security issue as well
as for all of the issues of that class involved in a merger. The basic
methodology for generating these results for preferred stock is very
similar to that for common stock. Instead of the CRSP index, we adjust
for market movements using the S&P Preferred Stock Index. We also use this
process to compute predicted values for the convertible preferred stocks
in our sample. In effect, we are correcting only for changes in the value
of the fixed claim portion of the convertible preferred shares. We will
assume that any dramatic change in the common equity portion (the
conversion privilege) of the convertible preferred share is caused by the
merger itself. A similar assumption is made for convertible bonds.
To avoid double-counting equity gains, we subtract from the combined
firm's stock market value the value of new common stock created by the
conversion of previously issued convertible preferred stock or
convertible bonds. We also document that 31 mergers involve the
distribution of newly created convertible preferred stock to target firm
shareholders as payment for their shares. In some cases, target
stockholders are given their choice of common or preferred stock, while
in others only preferred stock is used as payment. We combine the market
value of this newly created stock with the outstanding stock of the merged
firm to calculate a measure of the actual market value of common equity
that is truly comparable to the predicted value.
3.2. Generating predicted values for convertible and
nonconvertible bonds
For each individual bond issue k in the sample, we find the U.S. Treasury
bond outstanding at that time that most closely matches bond k in maturity
and coupon rate. We then subtract the matched T-bond's yield to maturity
(YTM) from bond k's YTM to compute a pre-merger yield spread for bond k,
(Pre-Merger Spread)k. To operationalize this measure, we assume that the
pre-merger yield spread will remain unchanged over time, even though the
level and shape of the yield curve can change. This assumption allows the
computation of an expected YTM value for each bond k (Exp YTM Corp Bond)k,
after the merger effective date based on the observed value of its matching
Treasury bond at that time. With an expected YTM, the expected post-merger
price of bond k can be computed using the terms of the issue (remaining
maturity, coupon rate) and a standard internal rate of return bond pricing
12
formula. The valuation prediction error for each bond k (VPE Corp Bond)k,
is then computed as before, after adjusting for bond redemptions,
conversions, and sinking fund payments. A full description of the VPE
methodology for each security class is presented in Nail (1996).
4. Empirical results
Table 3 presents VPE results for the securities in our sample categorized
by bidder and target and, more importantly, by whether the merger is
classified as conglomerate or nonconglomerate. Panel A presents commmon
and preferred stock results, while Panel B examines convertible and
nonconvertible bonds as well as our measure of net synergistic gains.
The first significant result is that the common stockholders in
nonconglomerate mergers experience average VPEs that are economically and
statistically significantly higher (8.58% versus 3.28%) than do
shareholders in conglomerate mergers. The median difference (8.55% versus
1.98%) is even larger. Further, a significant 66.4% of the nonconglomerate
mergers result in positive overall VPEs, while an insignificant 56.3% of
the conglomerate mergers yield positive results. These findings are
consistent with theoretical models predicting that new wealth will be
created only in nonconglomerate mergers through the creation of operating
synergies, and that most of these wealth increases will accrue to common
stockholders. For comparison purposes, Bradley et al. (1988) document
that successful tender offers increase the combined value of the target
and acquiring firm by an average of 7.4% over the period 1963–1984, and
similar figures are provided by Lang et al. (1991), Eckbo (1992), and
Berkovitch and Narayanan (1993).
For the 102 mergers occurring after 1976, VPEs can be computed for common
stockholders of bidder and target firms individually. These results
strongly suggest that bidding firm stockholders benefit in
nonconglomerate mergers, while bidding firm stockholders in conglomerate
mergers are harmed. The differences in mean (6.14% versus −4.79%) and
median (4.64% versus −7.36%) VPEs, and in the fraction of positive VPEs
(61.8% versus 36.2%), between the 55 nonconglomerate acquiring firms and
the 47 conglomerate acquiring firms are highly significant, both
statistically and economically. We also find that the difference between
combined stockholder VPEs becomes much more pronounced after 1977.
Stockholders in the 55 nonconglomerate mergers in this subsample
experience sigificantly positive mean (9.86%), median (9.84%), and
percent positive (70.9%) VPEs, while stockholders in the 47 conglomerate
mergers from this period earn insignificant 0.12% and −2.37% mean and
median VPEs, and only 46.8% of these mergers are value-increasing. Since
13
these mergers can be classified quite precisely as either
focus-preserving or focus-increasing (nonconglomerate) and
focus-decreasing (conglomerate), these results provide strong – and as
yet unique – evidence supporting the corporate focus hypothesis.
The wealth transfers from acquiring firm to target firm stockholders in
conglomerate mergers represent the only true wealth redistributions we
document. Furthermore, only nonconglomerate mergers create significant
net wealth for the combined firm's stockholders. Although most of this
new wealth accrues to target firm stockholders, bidder firm stockholders
also experience net wealth increases. This result is consistent with a
gains-sharing explanation for nonconglomerate mergers. Based on the
findings in Lang et al. (1989), we also examine whether market-to-book
ratios are different for bidders in conglomerate versus nonconglomerate
mergers in our sample. We find that the 1.32 mean (0.98 median)
market-to-book ratio (defined as the market value of equity plus the book
value of debt and preferred stock divided by the book value of total assets)
of our nonconglomerate acquirers is significantly greater than the 1.16
mean (0.89 median) market-to-book ratio of our conglomerate acquirers at
the 1% significance level (t=2.94).
We also find that acquiring-firm senior securityholders in
nonconglomerate mergers almost always experience net wealth increases
that are not only significant in their own right but are also generally
greater than for their counterparts in conglomerate mergers. The sole
exception to this pattern is observed in convertible bonds, where the
holders of these securities experience extremely large, positive VPEs,
which are actually slightly larger for conglomerate than for
nonconglomerate mergers. The mean (median) VPE for convertible
bondholders in conglomerate mergers is 20.92% (9.48%) versus 17.51%
(9.04%) for nonconglomerate mergers.
More generally, we find that convertible securityholders experience
surprisingly large, positive returns in stock-for-stock mergers. With the
exception of convertible preferred stockholders in conglomerate mergers,
who experience insignificant mean (median) returns of 2.15% (−0.20%), the
mean (median) VPEs for holders of convertible securities range from 12.45%
(4.00%) for bonds to 24.30% (14.18%) for preferred stocks.
The final two rows of Table 3 present the summed VPEs for all of the
securities of the merged firms, which is our measure of the net synergistic
gains created by stock-for-stock mergers. Given the individual security
results, it is not surprising that we document significant mean (6.91%)
and median (6.79%) net synergistic gains for nonconglomerate mergers
which are significantly larger than the insignificant mean (3.91%) and
14
median (1.25%) gains for conglomerate mergers. Furthermore, fewer than
half (48.2%) of conglomerate mergers create net synergistic gains for
securityholders, while almost two-thirds (64.0%) of nonconglomerate
mergers are wealth-creating.6
4.1. Why are convertible securityholder returns so large?
In an attempt to determine the causes of the surprisingly large, positive
wealth effects for both convertible bonds and preferred stock, we perform
three supplemental analyses. First, we examine what actually happens to
these senior securities after the merger to see if they are called or if
their holders voluntarily redeem most of the securities outstanding.
Second, we compare the conversion terms of bond and preferred stock issues
to determine whether the high returns to convertible bondholders are the
result of more favorable average conversion ratios. Finally, we analyze
the two convertible security classes to determine which variables are
driving these unusually large returns.
We find that 91.3% of the convertible preferred stock outstanding at the
time of the merger remains outstanding six months after the merger
completion date (8.7% has been either called or voluntarily converted)
and 79.1% remains outstanding a year after the merger has been completed.
Far less of the convertible debt remains outstanding six months (77.4%)
and 12 months (58.8%) after the merger effective date. These differences
could result from more favorable conversion terms enjoyed by convertible
bondholders relative to convertible preferred stockholders, and we
examine this possibility.
We compare the ratio of the common stock values of the convertible bonds
to their market values (the value of shares represented by full bond
conversion divided by the current value of the bonds themselves) to the
same ratio computed for convertible preferred stocks. Securities that
have a ratio value greater than or equal to one are classified as in the
money (since their conversion options have positive intrinsic value), and
those that have a ratio value of less than one are classified as out of
the money. We find that the average ratio is 1.13 (median=0.88) for bonds
and 0.79 (median=0.92) for preferred stock, and that 38.2% of the bonds
are in the money prior to the merger but only 22.6% of the preferred stocks
are in the money. The average VPE is 24.6% for in the money bonds and 18.1%
for in the money preferred stocks. Thus, the large difference between
convertible security VPEs is driven by a greater proportion of outlier
bonds that are in the money due to more favorable conversion terms relative
to preferred stockholders.
15
Using our conversion option framework also allows us to help explain the
seemingly anomalous convertible bond VPEs, as well as to present an
interesting result worthy of further research. While all other security
classes clearly exhibit superiority in wealth creation for
nonconglomerate mergers, convertible bond VPEs are actually higher in
conglomerate mergers. Given the previously reported results that common
stock VPEs of nonconglomerate mergers are significantly higher than those
for conglomerate mergers, one would expect the conversion option values
and VPEs of nonconglomerate convertible bonds to also be significantly
higher. However, our subsample of the common stock VPEs associated with
convertible securities is not representative of our full sample. While
the average common stock VPE is 8.58% and 3.28% for nonconglomerate and
conglomerate mergers, respectively, in the full sample of mergers, these
averages are reversed in the subsample of mergers with convertible bonds,
with values of 2.4% and 11.6% for nonconglomerate and conglomerate mergers,
respectively.
4.2. Merger-induced beta and variance changes
The VPE results documented above suggest that stock-for-stock mergers
create value through the anticipated creation of operating synergies,
rather than through the creation of financial synergies or for some other
purely ‘financial' reason. Before accepting this analysis, however, we
test two other possible explanations for the documented value increases:
changes in equity betas and changes in equity (or asset) return variances.
While there is little reason to expect that the act of merging will cause
the systematic or idiosyncratic risk of the resulting firm to differ
fundamentally from a weighted average of the combining firms' betas and
return variances (and covariances), we concede that there is much about
how assets are priced in real capital markets that we do not yet understand.
If stock-for-stock mergers result in reduced systematic risk for the
combined firm, this could translate into a valuation increase for both
stockholders and bondholders.
We examine whether the actual market-model beta of the resulting firm,
m, is significantly different from its expected value,
M, computed as
a weighted average of the betas of the bidder, B, and target firm, T.
As in Bhagat et al. (1987) and Kaplan and Stein (1990), we use the equity
beta calculated from a market model regression to proxy for a stock's
systematic risk. We find little evidence that changes in beta are
systematically influencing the study results, though they do appear to
add noise to our estimates. The 0.024 unit difference between the
predicted beta of the merged firm, M=1.004, and its actual beta, m=0.980,
is statistically insignificant. An examination of the distribution of
16
actual versus expected betas, however, indicates that the insignificant
average beta change is at least partly caused by a ‘washing out' of
extreme positive and negative changes. While 46% of actual merged-firm
betas are within 0.15 units of their expected value, almost 20% are more
than 0.35 units from their predicted values.
We also examine whether the actual stock return variance of the merged
firm,
, is equal to its predicted value,
, calculated as the sum
of the weighted variances and covariances between bidder firm return
variance,
, and target firm return variance,
. The methodology
described in Ohlson and Penman (1985) and Cox and Rubinstein (1985) is
used to calculate these variances using historical (daily) stock price
data. We find clear evidence that the actual (daily) stock return variance
of the merged firm is significantly higher than predicted for the combined
sample of all mergers and for the conglomerate and nonconglomerate
subsamples. The actual daily stock return variance (standard deviation,
M) of the merged firms in the full sample is 0.00042 ( M=0.0203 or 2.03%
per day), while the predicted variance is 0.00034 ( M=1.83%). The
difference between the predicted and actual values is significant at the
0.001% level (t=−4.91) and fully 67.0% of the mergers have actual
variances higher than their predicted values. Since a
higher-than-expected stock return variance might explain our
surprisingly high equity and convertible security wealth changes, this
variable is included in our regression analyses of VPEs, which are
discussed below.
When we repeat these analyses using asset betas, rather than equity betas,
our results are qualitatively identical. An asset variance is derived from
an equity variance by assuming that all of a firm's outstanding debt is
riskless and that all of the variability of the return on that firm's
assets loads on the stock price. In effect, the equity variance is
multiplied by the equity-to-capital ratio. This obviously yields a
variance estimate that is lower than the ‘true' variance of returns on
the firm's assets, but since the computed stock return variance yields
the highest possible variance estimate, computing both measures provides
polar estimates of actual variance.
4.3. Regression analysis of VPE results
So far we have documented far fewer true wealth redistributions than
predicted by the conglomerate merger/financial synergy literature, as
well as a surprising number of wealth gains and anomalously large VPEs
17
for convertible securities. We now examine these results further using
regression analysis, and provide two sets of analyses for each security
class. First, the combined sample of all common stocks is examined, then
bidder and target stocks are examined separately. For preferred stocks
and corporate bonds, we examine the full sample of each class together,
with a dummy variable indicating when an issue is a convertible security,
and then examine nonconvertible and convertible preferred stocks and
bonds separately.
We first describe three factors common to all four regressions, and then
describe factors that are expected to affect only individual security
issues. The first variable is a dummy variable (Nonconglom) used to proxy
for the type of merger, where one stands for nonconglomerate and zero
stands for conglomerate merger. The second (Pre-Williams) and third
(Post-1980) variables are temporal dummy variables, motivated by the
findings in Bradley, et al. (1988), that proxy for whether the merger
occurred prior to the implementation date of the Williams Act in July 1968
or after the Reagan Administration came to power in January 1981.
Variables four through six are used in the regression analyses of
individual common stock, preferred stock, and bond issues. Variable four
(Target) is a dummy variable taking a value of one if the security in
question is issued by a target firm and zero if it is a bidding firm
security issue. As before, we also perform separate regressions on bidder
and target firm common stock VPEs (but not preferred stock or bond), since
there is overwhelming evidence that target firm stockholders earn
significantly higher merger-related returns than do bidder firm
stockholders. The fifth variable, change in leverage (ΔLeverage),
measures the absolute percentage point change in market value leverage
that the securityholders of a given company are expected to experience.
Since no rational investor would willingly trade a less-heavily-indebted
financial claim for a more-indebted one, a merger-induced increase in
leverage should decrease VPEs for all security classes. To see how this
is computed,consider a bidding firm with a 50% debt-to-total capital ratio
(with all values in market value terms) and total capital of $1 billion,
that acquires a firm with total capital of $500 million and a
debt-to-capital ratio of 20%. The resulting combined firm will have a
leverage ratio of 40%, so the securities of the bidding firm will
experience a ten percentage point decrease (from 50% to 40%) in leverage,
while the target firm's securities will experience a 20 percentage point
increase.
The sixth variable is the predicted change in asset return variance
(Δvariance) computed as discussed in Section 4.2. Since the asset return
measure is the one suggested by Shastri (1990), we use it rather than the
18
stock return variance featured earlier. Shastri predicts that an increase
in variance will cause common stock to increase in value, but the same
variance increase will cause nonconvertible preferred stock and
bondholders to suffer a decline in the value of their securities.
Predictions regarding convertible securities are ambiguous since they
combine elements of both equity and debt.
The seventh and last variable refers only to preferred stock and bond
issues. It is a dummy variable (Convertible) that takes on a value of one
if the bond or preferred issue in question is convertible into common stock,
and takes a value of zero if the issue is nonconvertible. As mentioned,
we also perform separate regression analyses on convertible and
nonconvertible preferred stocks and bonds, since our VPE results are so
dramatically different (higher) for convertible securities. The
combined-security regressions we use to estimate the cross-sectional
determinants of the VPEs for common stock, preferred stock, corporate
bonds, and net synergistic gain are summarized in Eq. 2, Eq. 3 and Eq.
4 below.
Common stock issue j, in merger i:
(2)
Preferred stock or corporate bond issue j, in merger i:
(3)
Net synergistic gains (summed values of all merged firm securities) for
merger i:
(4)
The supplemental regressions are performed separately for bidder and
target firm common stocks and for convertible and nonconvertible
preferred stocks and bonds, and are identical to Eq. 2 and (3) except that
the appropriate dummy variables are not included. Note that both preferred
stock and bond issues are examined using Eq. 3. Note also that the dummy
variables in these equations are designed so that the base case, where
all the dummy variables have zero values, corresponds to a conglomerate
merger from the period July 1968 through December 1980 involving a
nonconvertible security issued by a bidding firm. Table 4 presents the
results of these regression analyses.
19
Table 4. Regression analyses of valuation prediction errors for individual security
classes and for net synergistic gains of the merged firm securities for sample firms
involved in stock-for-stock mergers over the period 1963–1996.
Ordinary least-squares regressions in which the dependent variable is the valuation
prediction error computed for each security of the merging firms and the independent
variables are a measure of the expected variance of the merged firm's stock
return–computed using the value-weighted average of the pre-merger variances and return
correlation coefficients of the merging firms' stocks ( Variance); the expected change
in firm leverage (ΔLeverage), measured as the absolute percentage change in market value
leverage that the securityholders of a given firm are expected to experience; and a series
of dummy variables proxying for whether the merger is a nonconglomerate combination
(Nonconglomerate), whether the merger occurred prior to the implementation date of the
Williams Act in July 1968 (Pre-Williams), whether the merger occurred after the Reagan
Administration took power in January 1981 (Post-1980), whether the security being
examined is from a target firm (Target), and whether the security being examined is
convertible into common stock (Convertible). Coefficient t-statistics from the
regressions are presented in parentheses.
4.3.1. Common stock regression results
The first line of Table 4 analyzes VPEs for the combined bidder and target
common stocks for the entire sample of 260 mergers. The only significant
variable is the nonconglomerate merger dummy (t=2.41), and the
coefficient value implies that common stockholders earn an average 6.2
percentage points extra return if they are involved in a nonconglomerate
rather than a conglomerate merger. The second set of common stock results,
analyzing individual VPEs for bidder and target firm stocks for 102
mergers occurring after 1976, indicates that the only significant
variable in the combined sample is the target dummy variable. Being the
recipient of a takeover bid is associated with a 38.1% VPE, and this
coefficient is highly significant (t=4.26). The overall F-value (11.58)
of the regression is also significant, and the adjusted R2 indicates that
this equation explains almost 21% of the variation in stock VPEs.
When bidder and target stockholder VPEs are examined separately, the
explanatory power and overall significance of each regression equation
is much reduced, and the only significant coefficient in the target firm
20
regression is the intercept ( =0.436, t=3.42). However, we document both
a significant negative (t=−1.74) relationship between the change in
leverage and acquiring firm stock VPE and a significant positive (t=2.01)
relationship between acquirer VPE and merger type. On average, a one
percentage point increase in leverage for the acquiring firm's
stockholders (in the merged firm) is associated with a 0.51 percentage
point reduction in VPE. Being involved in a nonconglomerate merger yields
a VPE that is 7.98 percentage points higher than that earned by acquiring
firm stockholders in conglomerate mergers. These results suggest that
nonconglomerate mergers create valuable operating synergies and that
increasing leverage decreases financial asset values.
On the other hand, the fact that the variance change measure is also
insignificant in both bidder and target regressions suggests that while
stock return variance is larger than expected, this increase is not priced.
The post-1980 variable is also insignificant for both targets and bidders,
and neither of the time period dummy variables is significant for the
combined-stock sample, so no significant difference in equity returns is
detected based on the regulatory environment within which the merger
occurs. This contrasts with Bradley et al. (1988) finding that the
division of gains between bidder and target changed in favor of the target
firm after the Reagan Administration came to power in January 1981.
Although the exact reasons for the differences between our results and
theirs cannot be determined, it is possible that tender offers (and the
inherently competitive nature of open-market cash takeover bids) were
affected much more fundamentally by the regulatory changes they study than
were (inherently friendly) stock-for-stock mergers.
4.3.2. Preferred stock regression results
When all 135 convertible and nonconvertible preferred stock issues are
analyzed together, two variables are significant. First, the
nonconglomerate variable again implies that preferred stockholders in
these mergers earn a significant 18.1 percentage point premium (t=2.23)
over their counterparts in conglomerate combinations. Second, being
fortunate enough to be a preferred stockholder in a target (rather than
a bidder) provides a 24.2 percentage point premium (t=1.90). Examining
nonconvertible and convertible preferred stock issues separately yields
a striking result. While none of the nonconvertible regression variables
are significant (nor is the overall F-value), the nonconglomerate
variable is both large and highly significant in the convertible preferred
stock regression. Being involved in a nonconglomerate versus a
conglomerate merger earns a convertible preferred shareholder a 20.6
percentage point premium (t=2.91), which is over three times the premium
common stockholders receive and over fifteen times what nonconvertible
21
bondholders receive for being involved in nonconglomerate mergers. The
absolute and relative size of this premium for convertible preferred
stockholders (but not bondholders) in nonconglomerate mergers remains a
puzzle.
4.3.3. Corporate bond regression results
The overall pattern of bond regression results is similar to that for
common stock, in that when both convertible and nonconvertible securities
are analyzed together an impressively large adjusted R2 (0.1871) and
F-value (18.35) is obtained, while the separate regressions of
convertible and nonconvertible bonds yield lower overall explanatory
power but a greater number of (and more interesting) significant
explanatory variables. The combined-security regression indicates, first,
that convertible bondholders receive a VPE that is 18.42 percentage points
higher (t=10.44) than that earned by the average nonconvertible
bondholder and, second, that each one percentage point increase in
leverage is associated with a 0.37% reduction in the VPE that bondholders
receive (t=−4.06).7
Analyzing nonconvertible bonds separately confirms that increasing
leverage reduces bondholder VPEs (coefficient=−0.122, t=−2.11), but also
yields the intriguing result that bond returns are 1.86 percentage points
higher (t=2.59) in nonconglomerate than in conglomerate mergers and that
bondholder VPEs declined by 1.92 percentage points (t=−2.06) after 1980.
The nonconglomerate and leverage results strengthen the conclusion that
nonconglomerate mergers create more value than do conglomerate
combinations and that merger-induced leverage increases harm all classes
of securityholders.
The significant negative coefficient (−0.019, t=−2.08) on the post-1980
dummy variable suggests that the takeover market changed during the 1980s
in a way that was harmful to nonconvertible bondholders. As with the equity
results, it is unclear why nonconvertible bondholders in stock-for-stock
mergers experienced the same post-1980 diminution in merger-related
returns that Bradley et al. (1988) document for stockholders in firms
making cash tender offers, particularly since we cannot identify who might
have benefited at bondholders' expense during this period (all of the
other post-1980 coefficients in our security return regressions are
insignificant).
As a sensitivity check, we also examine whether some of these bondholder
returns can be explained by differences in bond covenants, and to our
surprise find some evidence that this is occurring. Table 5 presents a
description of the frequency with which nine types of bond covenants are
22
observed in a randomly selected subsample of 125 bonds (18 convertible,
107 nonconvertible). This table also presents the frequency of call
provisions, sinking funds, and specific pledges of security as well as
the results of a regression analysis of the impact the presence of these
covenants and other features on bondholder VPEs.8
Table 5. The effect of bond covenants and other features on bondholder valuation
prediction errors for sample firms involved in stock-for-stock mergers over the period
1963–1996.
For a randomly selected subsample of 107 nonconvertible and 18 convertible bonds, this
table provides the frequency with which certain covenants and other features are observed
in the bond descriptions presented in the appropriate annual Moody's Manuals, and also
provides a summary of the regression coefficients and p-values from a regression in which
bondholder valuation prediction errors are the dependent variable and the independent
variables include dummy variables indicating the presence of these covenants and other
features. The following categories of bond covenants are documented: restrictions on
the ability of firms to pay dividends ( Dividend restrictions); covenants specifying
minimum asset coverage ratios (Asset coverage); restrictions on indebted-firm
management's ability to execute asset sale and leaseback agreements ( Sale and leaseback
restrictions); covenants specifying maximum levels of additional debt that can be
assumed (Total debt restrictions); covenants mandating minimum acceptable levels of
financial liquidity (Liquidity); covenants mandating that any newly issued debt be of
the same or junior status (Seniority restrictions); restrictions on the firm's ability
to engage in mergers or other corporate control activities ( Merger restrictions);
covenants specifying minimum or maximum capital investment spending ( Capital investment
restrictions); and restrictions on management's ability to sell firm assets (Asset sale
restrictions). The other features examined are the presence of a call option held by
the issuing firm (Call provision), the presence of a mandated sinking fund (Sinking fund
provision), and whether the bond is secured by specific pledged assets (Secured debt).
Only three types of bond covenants are observed in at least 20% of the
subsample of bonds: dividend restrictions (46.4%), minimum asset coverage
ratios (20.0%), and restrictions on asset sale and leaseback agreements
(20.0%). On the other hand, call provisions and sinking funds are
pervasive, showing up in 88.8% and 58.4% of all bond issues, respectively.
Only two of the covenants (asset coverage and merger restrictions)
significantly affect bondholder VPEs. On average, the presence of a
23
minimum asset coverage ratio covenant increases bondholder returns by 5.1
percentage points, and the presence of a covenant restricting mergers and
other corporate control events increases bondholder VPEs by 6.8
percentage points. The presence of call features, sinking funds, or
specific collateral pledges does not significantly affect the returns
earned by bondholders in stock-for-stock mergers. These results are
actually quite satisfying, because they suggest that the two covenants
that arguably offer the best protection against merger-induced wealth
redistributions from bondholders to stockholders are significantly
positively related to bondholder returns. This conclusion is strengthened
by the results of a supplemental bondholder VPE regression that includes
a dummy variable proxying for the presence of two or more covenants, rather
than dummy variables for the individual covenants. This dummy variable
is insignificant, indicating that it is the protection offered by the
asset coverage and merger restriction variables themselves that is valued,
rather than the mere presence of multiple covenants.
4.3.4. Net synergistic gains regression results
The final line of Table 4 details regression results for the combined
change in value for all of the securities of the 520 firms involved in
the full sample of 260 stock-for-stock mergers over the period 1963–96.
Two key findings emerge from this analysis. First, the time period dummy
variables are neither statistically nor economically significant. Total
gain creation does not vary according to whether a merger occurred prior
to the Williams Act of 1968, after the Reagan Administration came to power
in January 1981, or during the 1969–1980 period, mirroring the results
documented in Bradley, Desai, and Kim. Second, the significant
coefficient on the nonconglomerate merger dummy variable indicates that
these mergers typically yield a 7.1 percentage point higher net wealth
creation than do conglomerate mergers.
5. Summary and conclusions
We examine wealth changes for 1283 publicly traded debt and equity
securities of firms involved in 260 pure stock-for-stock mergers from 1963
to 1996. Using a new methodology for computing market-adjusted security
valuation changes, we find no evidence that conglomerate stock-for-stock
mergers create financial synergies or that these mergers benefit
bondholders more than stockholders. Instead, we find economically and
statistically significant net synergistic gains for the securityholders
of firms involved in nonconglomerate mergers, but generally insignificant
net gains for securityholders in conglomerate mergers. Apart from bidding
firm stockholders in conglomerate mergers, all major classes of debt and
24
equity securityholders of both bidders and targets either break even or
experience significant wealth gains. Target firm shareholders always
experience net wealth gains, as do bidding firm stockholders in
nonconglomerate mergers, clearly suggesting that, on average, acquiring
firm managers who execute nonconglomerate mergers are acting in their
shareholders' best interests, while those who launch conglomerate mergers
most definitely are not. Further, almost all subsamples of nonconvertible
preferred stockholders and bondholders experience significant wealth
increases.
Surprisingly, we find that holders of convertible securities earn
extremely large and significant wealth increases as a result of
stock-for-stock mergers. This result is not driven solely by the gains
accruing to target firm convertible securityholders (who could capture
the higher returns earned by target firm common shareholders by converting
their securities), but is instead often higher for bidding firm
convertible securityholders. The high average convertible securityholder
returns result from a relatively small fraction of in-the-money
convertibles that experience very large (greater than 30%) wealth
increases as a result of the merger. The larger average wealth gains for
convertible bonds (19.65%) than preferred stocks (9.59%) is driven by a
greater proprtion of outlier bonds that are in the money due to more
favorable conversion terms relative to preferred stockholders.
The overall and security-specific wealth changes we document cannot be fully explained either by
changes in systematic risk (since beta appears to add linearly) or by merger-induced changes in
asset return variance. The actual post-merger variance is indeed higher than predicted, but this
higher variance is not reflected in a higher VPE for the merging firms' securityholders. Instead,
regression analysis documents that stock-for-stock mergers benefit securityholders of the
more-levered firm at the expense of the less-levered firm's securityholders, and also confirms that
nonconglomerate mergers create more total wealth than do conglomerate mergers. Clearly,
nonconglomerate stock-for-stock mergers create significant net new wealth for securityholders,
conglomerate mergers at best do not destroy value, and there appear to be fewer actual
inter-securityholder wealth redistributions than our theories would suggest.
25