*Corresponding author. Tel: 706 542 3648; fax: 706 542 9434; e-mail: wmegginson@cbacc.cba.uga.edu.

1We are grateful to Tom Arnold, Sanjai Bhagat, James Bicksler, David Blackwell, EkkehartBoehmer, Ted Bos, Robert Brokaw, Bill Carleton, Bob Comment, Chris Cornwell, Mary Dehner, BobEisenbeis, Jimmy Hilliard, Randy Howard, Steve Jones, Ed Kane, Josef Lakonishok, Larry Lang, BillLewellen, Marc Lipson, Paul Malatesta, Jeff Netter, Cathy Niden, Volker Pollmann, Annette Poulsen,Jay Ritter, Richard Ruback, Louis Scott, Joe Sinkey, Bill Schwert (the editor), Ralph Walkling (thereferee), Ron Warren, J. Fred Weston, Karen Wruck, and seminar participants at the University ofArizona, the University of Delaware, the University of Illinois, the University of Georgia, theUniversity of Miami, Seattle University, the 1995 European Finance Association, the 1996 FinancialManagement Association, and the 1996 American Finance Association meetings for their helpfulcomments and recommendations. We also gratefully acknowledge the financial support provided for thisproject by the University of Georgia Research Foundation. Finally, Steve Henry, Rick McKinney, DavidQuillian, and Ryan Vaughn provided vital assistance with data collection and assisted with data input.

Journal of Financial Economics 48 (1998) 3—33

Wealth creation versus wealth redistributions in purestock-for-stock mergers1

Carlos P. Maquieira!, William L. Megginson",*, Lance Nail#! University of Chile, Santiago, Chile

" Terry College of Business, University of Georgia, Athens, GA 30602, U.S.A.# School of Business, University of Alabama-Birmingham, Birmingham, AL 35299, U.S.A.

Received 3 November 1995; received in revised form 6 August 1997

Abstract

We examine wealth changes for all 1283 publicly traded debt and equity securities offirms involved in 260 pure stock-for-stock mergers from 1963 to 1996. We find noevidence that conglomerate stock-for-stock mergers create financial synergies or benefitbondholders at stockholders’ expense. Instead, we document significant net synergisticgains in nonconglomerate mergers and generally insignificant net gains in conglomeratemergers. Conglomerate bidding-firm stockholders lose; all other securityholders at leastbreak even. Convertible securityholders experience the largest gains, due mostly to theirattached option values. Certain bond covenants are value-enhancing while leverageincreases are value-reducing. ( 1998 Elsevier Science S.A. All rights reserved.

JEL classification: G34; G12

Keywords: Conglomerate mergers; Stock-for-stock mergers; Bond valuation

0304-405X/98/$19.00 ( 1998 Elsevier Science S.A. All rights reservedPII S 0 3 0 4 - 4 0 5 X ( 9 7 ) 0 0 0 0 2 - 6

2 It is still unresolved whether mergers between firms in the same or related industries createwealth for the securityholders of the merging firms by creating and/or exploiting market power. Theempirical studies of Stillman (1983), Eckbo (1983, 1985, 1992), and Eckbo and Wier (1985) all castserious doubt on the anticompetitive nature of these mergers, but Singal (1996) and Kim and Singal(1993) find persuasive evidence that market power creation is an important factor in explaining thepositive returns earned by merging airlines.

1. Introduction

Although finance theorists have examined corporate mergers from manydifferent perspectives, most of these models predict one of two primary effects.Either mergers create net new wealth from operating or financial synergies, orthey redistribute existing wealth between stakeholder classes. Though empiricalsupport exists for most models, it has proven difficult to examine wealthcreation and wealth transfers in a single analysis. Our study accomplishes thisby examining the wealth changes of all 1283 publicly traded debt and equitysecurities of a matched sample 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 wealthcreation and/or wealth redistributions because there are no cash outflows orasset changes. Thus, the sum of the market values of the merged firm’s securitiesshould equal the sum of the market values of the merging firms’ securities(adjusted for overall market movements in financial asset values), unless themerger creates net wealth gains or losses. If net wealth is created by the captureof operating and/or financial synergies, there should be an increase in thesummed 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 mergersbetween firms in the same or related industries, and Healey et al. (1992)document particularly strong performance improvements for mergers involvingfirms with overlapping businesses.

Models predicting the creation of financial synergies, such as those presentedin 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 inconglomerate mergers, or mergers between firms in different industries. Becauseconglomerate mergers, in general, neither reduce competition nor provideoperating economies of scale, it is often assumed that these mergers do not yieldany operating synergies or create product or factor market power, though theymay increase a firm’s debt capacity or create other types of financial benefits.2Financial synergies can arise from: (1) reduction of default risk (and thus

4 C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33

3There is also no reason that financial synergies could not be found in mergers between firms inthe same or related industries — it is just that the covariance of returns is likely to be higher in suchcombinations and thus the opportunity for financial synergies is presumed to be lower. We thank thereviewer for pointing this out to us.

borrowing costs) by joining together firms with imperfectly correlated cash flowstreams, (2) diversification of equity risk for stockholders, or (3) contractingefficiencies created by allowing managers to reduce their employment risk bycreating larger, less risky firms.

In contrast to synergistic wealth creation, wealth redistributions are usuallyexpected to occur when a merger merely changes the relative riskiness of thecash flow streams of two or more securities. The theoretical models of Higginsand Schall (1975) and Galai and Masulis (1976) suggest that conglomeratemergers will lower equity values and raise bond values (leaving total firm valueunchanged), while Shastri (1990) shows that these mergers can have manydifferent effects, such as wealth redistributions from stockholders to bond-holders (or vice versa) or within securityholder classes, depending upon thecovariance between the returns of the merging firms.3 To date, however, onlyEger (1983) has documented wealth redistributions between bondholders andstockholders; studies by Kim and McConnell (1977), Asquith and Kim (1982),Dennis and McConnell (1986), and Travlos (1987) show no significant redis-tributions. Our empirical design, with its matched bidder and target firms andlarge sample of senior securities, allows for more direct testing of these wealthtransfers.

We employ a new valuation methodology that is a modification of standardevent-study methodology. Our technique compares the actual post-mergervalues of different security classes with the values that would be predictedwithout a merger, and allows us to easily handle widely varying merger comple-tion periods. Since we collect price data for all publicly traded nonconvertiblepreferred stock, nonconvertible bonds, and convertible security issues of thefirms in our sample, we are also able to reexamine Dennis and McConnell’s(1986) senior-security results using only stock-for-stock mergers (rather thana mixture of cash and stock transactions) and by using a much larger sample ofmatched bidder/target pairs. Also, our sample of 602 bonds and 130 preferredstocks represents the largest sample of senior securities employed in any pub-lished merger study.

Though not the principal objective of this study, we also examine whethertransactions that increase corporate ‘focus’ create more value than transactionsthat decrease focus. As the term is defined and used in Comment and Jarrell(1995) and John and Ofek (1995), focus-increasing transactions are those thatreduce the number of lines of business a firm operates in, and increasing focus isconsistent with the popular notion of concentrating corporate activities on the

C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33 5

4 In addition to the two articles mentioned above, studies by Morck et al. (1990), Bhagat et al.(1990), Healey et al. (1992), Lang and Stulz (1994), Berger and Ofek (1995, 1996), and Servaes (1996)have all documented a direct relationship between increasing focus and shareholder wealth.

firm’s core competencies or principal lines of business.4 In the context of ourstudy, conglomerate mergers tend to decrease corporate focus, while noncon-glomerate mergers (i.e., those between firms in the same or related industries)tend to preserve or even increase it. By analyzing the differential wealth creationand redistribution effects of conglomerate and nonconglomerate mergers, wethus provide indirect evidence on the economic benefits of focus-preserving (orfocus-increasing) versus focus-decreasing mergers.

We find little evidence that conglomerate stock-for-stock mergers createfinancial synergies, or that bondholders in these mergers benefit more thaneither stockholders or bondholders in nonconglomerate mergers. Instead, wefind that real operating synergies are created by stock-for-stock mergers, parti-cularly in nonconglomerate mergers, and that the increases in market valueresulting from these synergies are shared by almost all securityholder classes.Purely financial factors (i.e., leverage changes) influence merger-induced securityvalue changes, but they are not dominant. On average, common stockholdersexperience significant wealth increases which are greater for target than forbidder firm shareholders. However, bidding firm stockholders in nonconglomer-ate mergers experience wealth increases while bidding firm stockholders inconglomerate mergers suffer significant wealth losses. Virtually all classes ofnonconvertible bondholders and preferred stockholders experience net wealthincreases, but these are dwarfed by the positive unexpected wealth increasesaccruing to convertible bondholders in both merger categories as well as toconvertible preferred stockholders in nonconglomerate mergers, which aredriven by a relatively small fraction of in-the-money securities that experiencevery large unexpected wealth increases as a result of the merger.

The value changes documented in this study are not caused by changes insystematic risk, since we find that the typical merged firm’s actual market-modelbeta is almost exactly equal to its weighted-average predicted value. On theother hand, we find that the actual return variance of the typical merged firm’sequity (and assets) is significantly higher than its predicted value. Regressionanalyses confirm that more total wealth is created in nonconglomerate than inconglomerate mergers, that the wealth gains accruing to bondholders declineafter 1980, and that the wealth change to bondholders is directly related to thepresence of two specific covenants in individual bond contracts. Wealth changesare also inversely related to the merger-induced change in firm leverage for mostsecurity classes. Although unsurprising — no securityholder would voluntarilyexchange a less-levered claim for a more-levered one without compensation— this result has been heretofore undocumented.

6 C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33

Our study is organized as follows. Section 2 discusses the sample selec-tion criteria and presents summary statistics, and Section 3 presents our newvaluation methodology. Section 4 presents the results of the univariate differ-ence in means and medians tests, as well as supplemental multivariate regressiontests for wealth redistributions and synergistic gain creation. Section 5concludes.

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 purestock-for-stock mergers and collect data on all outstanding public and privatesecurity classes of the matched pairs of merging firms. While we collect aggreg-ate private debt and preferred stock measures, these are not included in ourvaluation measures since we lack market prices. However, our other bond andpreferred stock estimates suggest that these issues also increased in value afterthe merger. To be included in our sample, a merger must meet the followingselection criteria.

1. The merger is initiated between January 1963 and December 1995 and iscompleted by March 1996. The announcement of the intention to merge inthe ¼all Street Journal Index (¼SJI) is taken as the merger announcementdate, while the merger effective date is obtained from the Center for Researchin Security Prices (CRSP) database as the delisting date.

2. The merger is completed, so partial exchanges of stock are excluded from thesample. (Roughly 6% of the combinations examined are ‘clean-up’ mergers,in which a controlling corporate parent purchases all the subsidiary sharesnot already owned.)

3. Both firms are listed on either the New York Stock Exchange or theAmerican Stock Exchange, and daily stock returns are available on theCRSP tapes.

4. Only common or preferred stock is used as payment to the target firm’sshareholders. We define the payment method as the one actually used, notnecessarily the method mentioned in the initial merger announcement. Wealso use the actual exchange ratio in our computations of post-1977 acquiredfirm shareholder returns when this differs from the exchange ratio announcedinitially. Since we are not performing a merger announcement event study,our reliance on ex post data is not problematic, as the actual terms of themerger are always known two months after completion (the post-eventmeasurement date we use).

5. There are no major contaminating events such as another merger announce-ment, major asset sale or purchase, or large security issue during the event

C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33 7

5See Elgers and Clark (1980), Travlos (1987), Hansen (1987), Nathan and O’Keefe (1989), Amihudet al. (1990), and Martin (1996).

period from two months before the merger announcement date through twomonths after the effective date. This event period also solves a measurementproblem recently identified by Schwert (1996), who finds that pre-bid stockprice runup can often lead to a material increase in the total cost of acquiringa given firm. This runup only begins to be material one and one-half monthsprior to the bid announcement date, however.

6. Capital structure, security issue, and line of business data are available fromthe 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 completed mergers.We also eliminate roughly ten mergers with multiple bidders. In addition tocommon stock, we also collect prices and issue terms (maturity, coupon rate,amount outstanding, sinking fund payments due, etc.) for all publicly tradedsecurites of the merging and merged firms. This process yields usable informa-tion on 78 nonconvertible preferred stock, 83 convertible preferred stock (in-cluding 31 new securities issued as a means of payment), 535 nonconvertiblebond, and 67 convertible bond issues. Combined with the common stocks of themerging firms, this yields a total sample of 1283 individual security issues.

Concentrating on successful pure stock-for-stock mergers that are uncon-taminated by contemporaneous security issues or other major transactionsclearly costs us in three important ways. First, cash payments are more commonthan stock payments in U.S. mergers and acquisitions, and this disparity hasvaried over time (see Comment and Schwert, 1995). Second, research indicatesthat stock-for-stock mergers have systematically lower offer premiums for targetfirm stockholders, significantly negative abnormal returns for acquiring firmstockholders, and lower net synergistic gains created.5 Third, focusing onsuccessful stock-for-stock mergers, which generally will be friendly as well,eliminates many contested and resisted (hostile) transactions from our study (seeHuang and Walkling, 1987; Jennings and Mazzeo, 1993; Cotter and Zenner,1994). We trade off these drawbacks for a self-contained system that en-compasses 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 nonconglomer-ate mergers, we need a consistent method of classifying our transactions into oneof these two groups. Unfortunately, firms were not required to disclose the

8 C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33

detailed line of business data needed to compute revenue-based Herfindahlmeasures of focus until 1977, and our sample includes mergers from as early as1963. We therefore classify mergers based on a direct examination of theprimary line of business listing for each company in the appropriate annualedition of the Moody’s Manual. If the merging firms have the same primary lineof business, the merger is classified as nonconglomerate; if the two firms havedifferent primary lines, the merger is classified as conglomerate.

Although there is no ‘consensus’ definition of conglomerate versus noncon-glomerate mergers in the finance or economics literature, we feel our classifica-tion scheme is defensible, and a very similar technique (matching by two-digitSIC codes from CRSP) has been employed by other researchers, includingBerger 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, 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 thatembodies a combination between truly dissimilar firms, we opt for a definitionthat involves firms in different industrial groups (two-digit codes) rather thanfirms that simply produce different product lines (three- or four-digit codes).While this classification seems very imprecise, Megginson et al. (1997) documentthat over 85% of the post-1977 mergers in their sample that are classified asconglomerate (focus-decreasing) or nonconglomerate (focus-preserving orfocus-increasing) using this simple SIC code/line of business screen wouldhave been classified the same way using the more sophisticated revenue-basedHerfindahl measure.

Kahle and Walkling (1996) find substantial differences between the SICcodes reported in CRSP and Compustat for the same firm. To examinethe potential impact of this industrial code ambiguity on our study, wecompare our merger classifications with those that would have been as-signed based solely on CRSP, solely on Compustat, and on the use ofboth databases. We find that our classifications would have resulted in exactmatches 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 classifica-tion. Our method agrees with CRSP in classifying mergers as conglomerate92.6% of the time, with Compustat 82.5% of the time; and all three methodsagree 74.6% of the time. Naturally, the nonconglomerate classification agree-ment percentages are much lower, but this simply adds a conservative bias toour analyses.

The time period distribution of the full sample, as well as of the conglomerateand nonconglomerate merger subsamples, is presented in Table 1. Of the 260stock exchange mergers in our sample, 135 are classified as conglomerate and125 as nonconglomerate. Consistent with Comment and Jarrell (1995), thefraction of conglomerate mergers declines monotonically over time.

C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33 9

Table 1Distribution 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. Thesample mergers are grouped as conglomerate or nonconglomerate mergers based on whether thecombining firms have the same primary lines of business listings in the appropriate annual Moody’sIndustrial, Financial, or Utilities Manual.

Year Totalmergers

Conglomeratemergers

Nonconglomeratemergers

1963 9 6 31964 10 7 31965 14 6 81966 18 13 51967 23 14 91968 21 10 111969 11 7 41970 16 9 71971 2 1 11972 9 7 21973 10 3 71974 5 3 21975 4 2 21978 6 2 41977 14 8 61978 3 1 21979 5 4 11980 6 5 11981 8 5 31982 8 5 31983 5 3 21984 5 3 21985 4 1 31986 8 2 61987 4 1 31988 1 0 11989 5 1 41990 4 1 31991 2 0 21992 3 1 21993 5 1 41994 6 3 31995 6 0 6

Total 260 135 125

The first section of Table 2 describes the relative size of the bidder andtarget firms in the full sample. On average (median), the target firm’s pre-mergerequity market value is equal to 23.1% (18.2%) of that of the bidder. The relativesize of targets to bidders is much higher in nonconglomerate mergers than in

10 C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33

Table 2Relative size and leverage ratios for sample companies involved in stock-for-stock mergers over theperiod 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 totalassets divided by the book value of the bidding firm’s total assets in the reporting period immediatelyprior to the announcement date of the merger. The leverage ratios of the bidder, target, andcombined firms are computed as the book value of total debt divided by the book value of totalassets.

Mean Median

Relative size of target to bidder firmFull sample (all mergers) 23.1% 18.2%

Conglomerate merger subsample 19.4 15.6Nonconglomerate merger subsample 27.1 22.8

¸everage ratios of bidder, target, and combined firmsFull Sample

Bidder firm 44.4% 42.1%Target firm 42.2 41.4Combined firm 41.2 41.2

Conglomerate merger subsampleBidder firm 41.2% 39.8%Target firm 41.8 39.4Combined firm 41.2 39.8

Nonconglomerate merger subsampleBidder firm 41.2% 41.6%Target firm 47.2 44.0Combined firm 43.3 42.4

conglomerate combinations (27.1% mean and 22.8% median versus 19.4% and15.6% mean and median). These differences may reflect the ‘portfolio’ acquisi-tion strategy of conglomerate bidders, as well as the practical fact that there maybe only a limited number of (relatively large) firms within an industry fora nonconglomerate acquirer to bid for.

The second part of Table 2 shows that the firms in the full sample have meanand median book value leverage ratios of 41.2%, with leverage defined as theratio 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 firmsin nonconglomerate mergers have an average (median) leverage ratio of 47.2%(44.0%), and acquiring firms in both types of mergers have average leverageratios of 41.2% (39.8% and 41.6% for conglomerate and nonconglomeratemergers, respectively), but average leverage ratios for all other subsamples fall inthe range of 41.8% to 44.4%.

C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33 11

3. Methodology for computing security valuation changes

Our objectives in this study require us to determine the wealth effect ofmergers on all of the publicly traded securities of the combining firms. Unfortu-nately, the length of time it takes a merger to be completed ranges from a low of11 months to a high of 31 months for the mergers in our sample. We thusdevelop a method of computing valuation changes that allows adjustment bothfor overall market movements and for changes in the number of securitiesoutstanding over any appropriate holding period. Our principal methodologyfor 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 mergingfirms,

2. overall market movements in matching asset prices during the event period(t!2 months before merger announcement to t#2 months after the effec-tive date) between the merger announcement and effective dates,

3. any cash distributions made to securityholders during the event period, and4. 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 computea valuation prediction error (VPE) for that security by subtracting the predictedpost-merger value from the actual post-merger value. While this technique isjust a variant of event-study methodology (which other researchers have used tomeasure event-related senior security valuation changes), we are unaware of anyother study that uses precisely the same procedure. The VPE is computed inessentially the same manner for all security classes, and can thus easily beaggregated by class, firm, or merger. The prediction methodology used for eachsecurity 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-firmcommon stock is unique in that at least one (and sometimes both) of thepre-merger common stocks outstanding invariably ceases to exist after themerger effective date. Depending upon the accounting treatment of the combi-nation, either the acquiring firm’s common stock continues to trade after themerger or a new class of common stock of the merged firm begins trading. Ineither case, the single common stock class resulting from the merger should beequal to the market-adjusted summed value of the merging firms’ commonstocks, plus any wealth transfers from other securityholders or net synergisticgains. (From 1977 on, we can reliably obtain exchange ratios for all of our

12 C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33

Table 3Valuation prediction errors for conglomerate and nonconglomerate stock-for-stock mergers overthe period 1963—1996 (announcement period ends in 1995, but several mergers are completed in1996).

Valuation prediction errors (VPEs) are computed as the percentage difference from predictedmarket value for equity and debt securities from two months before the merger announcement datethrough two months after the effective date of merger for individual securities. Predicted marketvalues are computed based on overall market movements in the same classes of securities over themeasurement period (t!2 months to t#2 months), and t-statistics (mean and percent positive) andWilcoxon statistics (median) are presented in parentheses. This table presents mean and medianVPEs, and percent positive statistics for 260 pure stock-for-stock mergers, classified according towhether the combination is a conglomerate or a nonconglomerate merger. This classification ismade based on whether the combining firms have the same primary lines of business listings in theappropriate annual Moody’s Industrial, Financial, or Utilities Manual.

Security descriptionSample or subsample

Number ofobservations

MeanVPE

MedianVPE

Percentpositive

Panel A: Common and preferred stockCommon stock

Conglomerate mergers 135 3.28% 1.98% 56.3%(1.45) (1.01) (1.48)

Acquiring firms 47! !4.79 !7.36 36.2(!1.79) (!1.78) (!1.97**)

Target firms 47! 41.65 38.79 83.0(6.55*) (5.04*) (6.02*)

Nonconglomerate mergers 125 8.58% 8.55% 66.4%(3.75*) (3.79*) (3.88*)

Acquiring firms 55 6.14 4.64 61.8(2.27*) (2.48*) (1.80)

Target firms 55 38.08 24.33 80.0(4.94*) (4.67*) (5.56*)

Nonconvertible preferred stockConglomerate mergers 38 4.00% 3.82% 76.3%

(1.81) (1.81) (3.81*)Acquiring firms 37 3.55 3.78 75.7

(1.92) (1.77) (3.65*)Target firms 1 20.31 20.31 100.0

na na naNonconglomerate mergers 40 6.11% 7.78% 75.0%

(4.57*) (2.04*) (3.65*)Acquiring firms 26 5.47 7.41 65.4

(3.01*) (1.69) (1.65)Target firms 14 7.30 8.14 92.9

(4.00*) (2.67*) (6.23*)Convertible preferred stock

Conglomerate mergers 36" 2.15% !0.20 36.1(0.59) (!0.79) (!1.75)

Acquiring firms 32 2.04 !0.20 34.4(0.16) (!1.03) (!1.86)

C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33 13

Table 3 Continued

Security descriptionSample or subsample

Number ofobservations

MeanVPE

MedianVPE

Percentpositive

Target firms 4 3.10 2.27 50.0(0.23) (0.73) (0.00)

Nonconglomerate mergers 16" 26.33 17.25 68.8(3.16*) (1.59) (1.62)

Acquiring firms 15 24.30 14.18 66.7(2.81*) (1.41) (1.37)

Target firms 1 56.33 56.33 100.00

Panel B: Bonds and net synergistic gains (combined firm, all securities)

Nonconvertible bondsConglomerate mergers 253 0.44% 0.28% 53.0%

(1.45) (1.37) (0.96)Acquiring firms 222 0.33 0.24 52.3

(0.73) (1.31) (0.90)Target firms 31 1.22 3.89 51.6

(1.44) (1.55) (0.18)Nonconglomerate mergers 282 1.44% 0.82% 59.6%

(3.00*) (3.65*) (3.28*)Acquiring firms 189 1.90 1.39 64.0

(3.18*) (3.55*) (4.02*)Target firms 93 0.50 0.24 50.5

(0.63) (0.58) (0.10)Convertible bonds

Conglomerate mergers 42 20.92% 9.48% 69.0%(3.15*) (3.04*) (2.66*)

Acquiring firms 31 22.15 10.71 67.7(3.21*) (2.08**) (2.11*)

Target firms 11 17.44 8.28 72.7(2.08**) (1.48) (1.69)

Nonconglomerate mergers 25 17.51% 9.04% 68.0%(2.57*) (2.25*) (1.93)

Acquiring firms 14 12.45 4.00 50.0(1.36) (0.78) (0.00)

Target firms 11 23.94 16.41 90.0(2.31*) (2.45*) (4.72*)

Net synergistic gainsConglomerate mergers 135 3.91% 1.25% 48.2%

(1.81) (1.02) (!0.28)Nonconglomerate mergers 125 6.91 6.79 64.0

(3.73*) (3.65*) (3.26*)

! Bidder and target stockholder VPEs computed based on merger exchange ratio. Data availableonly from 1977." Does not include 31 new convertible preferred stocks issued by acquiring firms as payment fortarget firm shares. These are included in common stock VPEs.* Indicates significance at the 1% level.** Indicates significance at the 5% level.

14 C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33

sample mergers, allowing us to compute separate VPEs for the common stock ofboth the bidder and target firms, as well as for the merged firm’s equity; wereport these individual results in Table 3 as well.)

To adjust for market movements over our study period, we compute an indexvalue of the CRSP value-weighted return (including all distributions) over theperiod beginning two months before the merger announcement through twomonths after the merger effective date. We then calculate the predicted merged-firm equity value, (Pred M»CS Comb)

i, as the sum of the beta-adjusted product

of this index number and the equity value of each the merging firms:

(PredM»CSComb)i"[(M»CSBidder)

ix(1#(CSIndex)

i)xb

B]

#[(M»CS¹arget)ix(1#(CSIndex)

i)xb

T], (1)

where (M»CS Bidder)iis the pre-merger market value of bidder firm common

stock in merger i, (M»CS ¹arget)ithe pre-merger market value of target firm

common stock in merger i, (CSIndex)ithe cum-dividend geometric return on the

CRSP value-weighted index from two months before merger announcement totwo months after merger completion, b

Bthe market-model beta for bidder firm,

estimated over months t!62 to t!2, and bT

the market-model beta for targetfirm, estimated over months t!62 to t!2.

The actual market value of the combined firm’s common stock in merger i,(M»CS 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 mergingfirms’ stocks during the security holding period. We then compute a valuationprediction error for the common stock in merger i, (»PE CS Comb)

i. This is our

measure of the synergistic gain (or loss) and/or wealth redistribution accruing tothe common stockholders of the merging firm as a result of the merger.

Beginning with preferred stocks, we find that multiple issues of a givensecurity class (preferred stock or debt) will often be traded before and after themerger, though the number of securities outstanding might well change due toredemption or partial conversion. We therefore compute predicted valuationsand VPEs for each individual security issue as well as for all of the issues of thatclass involved in a merger. The basic methodology for generating these resultsfor preferred stock is very similar to that for common stock. Instead of the CRSPindex, we adjust for market movements using the S&P Preferred Stock Index.We also use this process to compute predicted values for the convertiblepreferred stocks in our sample. In effect, we are correcting only for changes inthe value of the fixed claim portion of the convertible preferred shares. We willassume that any dramatic change in the common equity portion (the conversionprivilege) 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’sstock market value the value of new common stock created by the conversion of

C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33 15

previously issued convertible preferred stock or convertible bonds. We alsodocument that 31 mergers involve the distribution of newly created convertiblepreferred stock to target firm shareholders as payment for their shares. In somecases, target stockholders are given their choice of common or preferred stock,while in others only preferred stock is used as payment. We combine the marketvalue of this newly created stock with the outstanding stock of the merged firmto calculate a measure of the actual market value of common equity that is trulycomparable 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. Treasurybond outstanding at that time that most closely matches bond k in maturity andcoupon 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 shapeof the yield curve can change. This assumption allows the computation of anexpected YTM value for each bond k (Exp ½¹M Corp Bond)

k, after the merger

effective date based on the observed value of its matching Treasury bond at thattime. With an expected YTM, the expected post-merger price of bond k can becomputed using the terms of the issue (remaining maturity, coupon rate) anda standard internal rate of return bond pricing formula. The valuation predictionerror for each bond k (»PE Corp Bond)

k, is then computed as before, after adjusting

for bond redemptions, conversions, and sinking fund payments. A full descrip-tion 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 bybidder and target and, more importantly, by whether the merger is classified asconglomerate or nonconglomerate. Panel A presents commmon and preferredstock results, while Panel B examines convertible and nonconvertible bonds aswell as our measure of net synergistic gains.

The first significant result is that the common stockholders in nonconglomer-ate mergers experience average VPEs that are economically and statisticallysignificantly higher (8.58% versus 3.28%) than do shareholders in conglomeratemergers. The median difference (8.55% versus 1.98%) is even larger. Further,a significant 66.4% of the nonconglomerate mergers result in positive overallVPEs, while an insignificant 56.3% of the conglomerate mergers yield positiveresults. These findings are consistent with theoretical models predicting that new

16 C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33

wealth will be created only in nonconglomerate mergers through the creation ofoperating synergies, and that most of these wealth increases will accrue tocommon stockholders. For comparison purposes, Bradley et al. (1988) docu-ment that successful tender offers increase the combined value of the target andacquiring firm by an average of 7.4% over the period 1963—1984, and similarfigures are provided by Lang et al. (1991), Eckbo (1992), and Berkovitch andNarayanan (1993).

For the 102 mergers occurring after 1976, VPEs can be computed for com-mon stockholders of bidder and target firms individually. These results stronglysuggest that bidding firm stockholders benefit in nonconglomerate mergers,while bidding firm stockholders in conglomerate mergers are harmed. Thedifferences 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 conglomerateacquiring firms are highly significant, both statistically and economically. Wealso find that the difference between combined stockholder VPEs becomesmuch more pronounced after 1977. Stockholders in the 55 nonconglomeratemergers in this subsample experience sigificantly positive mean (9.86%), median(9.84%), and percent positive (70.9%) VPEs, while stockholders in the 47conglomerate 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 these mergers can be classified quite precisely as either focus-preserving orfocus-increasing (nonconglomerate) and focus-decreasing (conglomerate), theseresults provide strong — and as yet unique — evidence supporting the corporatefocus hypothesis.

The wealth transfers from acquiring firm to target firm stockholders inconglomerate mergers represent the only true wealth redistributions we docu-ment. Furthermore, only nonconglomerate mergers create significant net wealthfor the combined firm’s stockholders. Although most of this new wealth accruesto target firm stockholders, bidder firm stockholders also experience net wealthincreases. This result is consistent with a gains-sharing explanation for noncon-glomerate mergers. Based on the findings in Lang et al. (1989), we also examinewhether market-to-book ratios are different for bidders in conglomerate versusnonconglomerate mergers in our sample. We find that the 1.32 mean (0.98median) market-to-book ratio (defined as the market value of equity plus thebook 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 nonconglomeratemergers almost always experience net wealth increases that are not only signifi-cant in their own right but are also generally greater than for their counterpartsin conglomerate mergers. The sole exception to this pattern is observed in

C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33 17

6We also examine the correlation coefficients (o) between stockholder and senior securityholderreturns in the two types of mergers, and find generally higher correlations in nonconglomeratetransactions. The o between stockholder and bondholder returns in nonconglomerate mergers isa highly significant 0.24 (z"2.10), while in conglomerate mergers o is an insignificant 0.13 (t"1.20).On the other hand, the o for common stock versus preferred stock is quite similar for both mergertypes, as it is for preferred versus debt as well. For common versus preferred, o is an insignificant 0.10and 0.11 for conglomerate and nonconglomerate mergers, respectively. For preferred versus debt,o is statistically significant for both conglomerate and nonconglomerate mergers, with values of 0.35and 0.43. For common stock versus senior securities generally (combined preferred stock and debt),o is an insignificant 0.08 and 0.15 for conglomerate and nonconglomerate mergers. These resultschange substantially when we examine only the post-1977 sample of firms. Here, the o betweenstockholders and senior securityholders in nonconglomerate mergers is a highly significant 0.45(z"4.28), while in conglomerate mergers it is an insignificant !0.02 (z"!0.16). As a whole,these results offer some additional support for a gains-sharing explanation of security returns innonconglomerate mergers, and for a wealth-redistribution explanation of returns in conglomeratemergers.

convertible bonds, where the holders of these securities experience extremelylarge, positive VPEs, which are actually slightly larger for conglomerate than fornonconglomerate mergers. The mean (median) VPE for convertible bondhol-ders in conglomerate mergers is 20.92% (9.48%) versus 17.51% (9.04%) fornonconglomerate mergers.

More generally, we find that convertible securityholders experience surpris-ingly large, positive returns in stock-for-stock mergers. With the exception ofconvertible preferred stockholders in conglomerate mergers, who experienceinsignificant mean (median) returns of 2.15% (!0.20%), the mean (median)VPEs for holders of convertible securities range from 12.45% (4.00%) for bondsto 24.30% (14.18%) for preferred stocks.

The final two rows of Table 3 present the summed VPEs for all of thesecurities of the merged firms, which is our measure of the net synergistic gainscreated by stock-for-stock mergers. Given the individual security results, it is notsurprising that we document significant mean (6.91%) and median (6.79%) netsynergistic gains for nonconglomerate mergers which are significantly largerthan the insignificant mean (3.91%) and median (1.25%) gains for conglomeratemergers. Furthermore, fewer than half (48.2%) of conglomerate mergers createnet synergistic gains for securityholders, while almost two-thirds (64.0%) ofnonconglomerate 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 wealtheffects for both convertible bonds and preferred stock, we perform three supple-mental analyses. First, we examine what actually happens to these senior

18 C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33

securities after the merger to see if they are called or if their holders voluntarilyredeem most of the securities outstanding. Second, we compare the conversionterms of bond and preferred stock issues to determine whether the high returnsto convertible bondholders are the result of more favorable average conversionratios. Finally, we analyze the two convertible security classes to determinewhich variables are driving these unusually large returns.

We find that 91.3% of the convertible preferred stock outstanding at the timeof the merger remains outstanding six months after the merger completion date(8.7% has been either called or voluntarily converted) and 79.1% remainsoutstanding a year after the merger has been completed. Far less of the convert-ible debt remains outstanding six months (77.4%) and 12 months (58.8%) afterthe merger effective date. These differences could result from more favorableconversion terms enjoyed by convertible bondholders relative to convertiblepreferred stockholders, and we examine this possibility.

We compare the ratio of the common stock values of the convertible bonds totheir market values (the value of shares represented by full bond conversiondivided by the current value of the bonds themselves) to the same ratio com-puted for convertible preferred stocks. Securities that have a ratio value greaterthan or equal to one are classified as in the money (since their conversionoptions have positive intrinsic value), and those that have a ratio value of lessthan 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 that38.2% of the bonds are in the money prior to the merger but only 22.6% of thepreferred stocks are in the money. The average VPE is 24.6% for in the moneybonds and 18.1% for in the money preferred stocks. Thus, the large differencebetween convertible security VPEs is driven by a greater proportion of outlierbonds that are in the money due to more favorable conversion terms relative topreferred stockholders.

Using our conversion option framework also allows us to help explain theseemingly anomalous convertible bond VPEs, as well as to present an interest-ing result worthy of further research. While all other security classes clearlyexhibit superiority in wealth creation for nonconglomerate mergers, convertiblebond VPEs are actually higher in conglomerate mergers. Given the previouslyreported results that common stock VPEs of nonconglomerate mergers aresignificantly higher than those for conglomerate mergers, one would expect theconversion option values and VPEs of nonconglomerate convertible bonds toalso be significantly higher. However, our subsample of the common stockVPEs associated with convertible securities is not representative of our fullsample. While the average common stock VPE is 8.58% and 3.28% for noncon-glomerate 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.

C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33 19

4.2. Merger-induced beta and variance changes

The VPE results documented above suggest that stock-for-stock mergerscreate value through the anticipated creation of operating synergies, rather thanthrough the creation of financial synergies or for some other purely ‘financial’reason. Before accepting this analysis, however, we test two other possibleexplanations for the documented value increases: changes in equity betas andchanges in equity (or asset) return variances. While there is little reason to expectthat the act of merging will cause the systematic or idiosyncratic risk of theresulting firm to differ fundamentally from a weighted average of the combiningfirms’ betas and return variances (and covariances), we concede that there ismuch about how assets are priced in real capital markets that we do not yetunderstand. If stock-for-stock mergers result in reduced systematic risk for thecombined firm, this could translate into a valuation increase for both stockhol-ders and bondholders.

We examine whether the actual market-model beta of the resulting firm, b., is

significantly different from its expected value, bM, computed as a weighted

average of the betas of the bidder, bB, and target firm, b

T. As in Bhagat et al.

(1987) and Kaplan and Stein (1990), we use the equity beta calculated froma market model regression to proxy for a stock’s systematic risk. We find littleevidence that changes in beta are systematically influencing the study results,though they do appear to add noise to our estimates. The 0.024 unit differencebetween the predicted beta of the merged firm, b

M"1.004, and its actual beta,

b."0.980, is statistically insignificant. An examination of the distribution of

actual versus expected betas, however, indicates that the insignificant averagebeta change is at least partly caused by a ‘washing out’ of extreme positive andnegative changes. While 46% of actual merged-firm betas are within 0.15 unitsof their expected value, almost 20% are more than 0.35 units from theirpredicted values.

We also examine whether the actual stock return variance of the merged firm,p2M, is equal to its predicted value, p2

M, calculated as the sum of the weighted

variances and covariances between bidder firm return variance, p2B, and target

firm return variance, p2T. The methodology described in Ohlson and Penman

(1985) and Cox and Rubinstein (1985) is used to calculate these variances usinghistorical (daily) stock price data. We find clear evidence that the actual (daily)stock return variance of the merged firm is significantly higher than predicted forthe combined sample of all mergers and for the conglomerate and noncon-glomerate subsamples. The actual daily stock return variance (standard devi-ation, p

M) of the merged firms in the full sample is 0.00042 (p

M"0.0203 or 2.03%

per day), while the predicted variance is 0.00034 (pM"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 thantheir predicted values. Since a higher-than-expected stock return variance might

20 C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33

explain our surprisingly high equity and convertible security wealth changes,this variable is included in our regression analyses of VPEs, which are discussedbelow.

When we repeat these analyses using asset betas, rather than equity betas, ourresults are qualitatively identical. An asset variance is derived from an equityvariance by assuming that all of a firm’s outstanding debt is riskless and that allof the variability of the return on that firm’s assets loads on the stock price. Ineffect, the equity variance is multiplied by the equity-to-capital ratio. Thisobviously yields a variance estimate that is lower than the ‘true’ variance ofreturns on the firm’s assets, but since the computed stock return variance yieldsthe highest possible variance estimate, computing both measures provides polarestimates of actual variance.

4.3. Regression analysis of VPE results

So far we have documented far fewer true wealth redistributions than pre-dicted by the conglomerate merger/financial synergy literature, as well as a sur-prising number of wealth gains and anomalously large VPEs for convertiblesecurities. We now examine these results further using regression analysis, andprovide two sets of analyses for each security class. First, the combined sampleof all common stocks is examined, then bidder and target stocks are examinedseparately. For preferred stocks and corporate bonds, we examine the fullsample of each class together, with a dummy variable indicating when an issue isa convertible security, and then examine nonconvertible and convertible prefer-red stocks and bonds separately.

We first describe three factors common to all four regressions, and thendescribe factors that are expected to affect only individual security issues. Thefirst variable is a dummy variable (Nonconglom) used to proxy for the type ofmerger, where one stands for nonconglomerate and zero stands for conglomer-ate merger. The second (Pre-¼illiams) and third (Post-1980) variables aretemporal dummy variables, motivated by the findings in Bradley, et al. (1988),that proxy for whether the merger occurred prior to the implementation date ofthe Williams Act in July 1968 or after the Reagan Administration came to powerin January 1981.

Variables four through six are used in the regression analyses of individualcommon stock, preferred stock, and bond issues. Variable four (¹arget) isa dummy variable taking a value of one if the security in question is issued bya target firm and zero if it is a bidding firm security issue. As before, we alsoperform separate regressions on bidder and target firm common stock VPEs(but not preferred stock or bond), since there is overwhelming evidence thattarget firm stockholders earn significantly higher merger-related returns than dobidder firm stockholders. The fifth variable, change in leverage (D¸everage),

C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33 21

measures the absolute percentage point change in market value leverage that thesecurityholders of a given company are expected to experience. Since no rationalinvestor would willingly trade a less-heavily-indebted financial claim fora more-indebted one, a merger-induced increase in leverage should decreaseVPEs for all security classes. To see how this is computed,consider a biddingfirm with a 50% debt-to-total capital ratio (with all values in market valueterms) 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 firmwill have a leverage ratio of 40%, so the securities of the bidding firm willexperience a ten percentage point decrease (from 50% to 40%) in leverage, whilethe target firm’s securities will experience a 20 percentage point increase.

The sixth variable is the predicted change in asset return variance (Dvariance)computed as discussed in Section 4.2. Since the asset return measure is the onesuggested by Shastri (1990), we use it rather than the stock return variancefeatured earlier. Shastri predicts that an increase in variance will cause commonstock to increase in value, but the same variance increase will cause nonconvert-ible preferred stock and bondholders to suffer a decline in the value of theirsecurities. Predictions regarding convertible securities are ambiguous since theycombine elements of both equity and debt.

The seventh and last variable refers only to preferred stock and bond issues. Itis a dummy variable (Convertible) that takes on a value of one if the bond orpreferred issue in question is convertible into common stock, and takes a valueof zero if the issue is nonconvertible. As mentioned, we also perform separateregression analyses on convertible and nonconvertible preferred stocksand bonds, since our VPE results are so dramatically different (higher)for convertible securities. The combined-security regressions we use to estimatethe cross-sectional determinants of the VPEs for common stock, preferredstock, corporate bonds, and net synergistic gain are summarized in Eqs. (2)—(4)below.

Common stock issue j, in merger i:

»PEij"a#b

1Nonconglom#b

2Pre!¼illiams

#b3Post-1980#b

4¹arget#b

9D¸everage#b

6D»ariance. (2)

Preferred stock or corporate bond issue j, in merger i:

»PEij"a#b

1Nonconglom#b

2Pre!¼illiams

#b3Post-1980#b

4¹arget#b

5D¸everage

#b6D»ariance#b

7Convertible. (3)

22 C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33

Net synergistic gains (summed values of all merged firm securities) for merger i:

»PEi"a#b

1Nonconglom#b

2Pre!¼illiams#b

3Post-1980. (4)

The supplemental regressions are performed separately for bidder andtarget firm common stocks and for convertible and nonconvertible preferredstocks and bonds, and are identical to Eq. (2) and (3) except that the appro-priate dummy variables are not included. Note that both preferred stock andbond issues are examined using Eq. (3). Note also that the dummy variables inthese equations are designed so that the base case, where all the dummyvariables have zero values, corresponds to a conglomerate merger from theperiod July 1968 through December 1980 involving a nonconvertible securityissued by a bidding firm. Table 4 presents the results of these regressionanalyses.

4.3.1. Common stock regression resultsThe first line of Table 4 analyzes VPEs for the combined bidder and target

common stocks for the entire sample of 260 mergers. The only significantvariable is the nonconglomerate merger dummy (t"2.41), and the coefficientvalue implies that common stockholders earn an average 6.2 percentage pointsextra return if they are involved in a nonconglomerate rather than a conglomer-ate merger. The second set of common stock results, analyzing individual VPEsfor bidder and target firm stocks for 102 mergers occurring after 1976, indicatesthat the only significant variable in the combined sample is the target dummyvariable. 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) ofthe regression is also significant, and the adjusted R2 indicates that this equationexplains almost 21% of the variation in stock VPEs.

When bidder and target stockholder VPEs are examined separately, theexplanatory power and overall significance of each regression equation is muchreduced, and the only significant coefficient in the target firm regression is theintercept (a"0.436, t"3.42). However, we document both a significant nega-tive (t"!1.74) relationship between the change in leverage and acquiring firmstock VPE and a significant positive (t"2.01) relationship between acquirerVPE and merger type. On average, a one percentage point increase in leveragefor the acquiring firm’s stockholders (in the merged firm) is associated witha 0.51 percentage point reduction in VPE. Being involved in a nonconglomeratemerger yields a VPE that is 7.98 percentage points higher than that earned byacquiring firm stockholders in conglomerate mergers. These results suggest thatnonconglomerate mergers create valuable operating synergies and that increas-ing leverage decreases financial asset values.

On the other hand, the fact that the variance change measure is also insignific-ant in both bidder and target regressions suggests that while stock return

C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33 23

Tab

le4

Reg

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anal

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ofv

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pred

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—199

6.

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).C

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711

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24 C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33

Nonc

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C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33 25

variance is larger than expected, this increase is not priced. The post-1980variable is also insignificant for both targets and bidders, and neither of the timeperiod dummy variables is significant for the combined-stock sample, so nosignificant difference in equity returns is detected based on the regulatoryenvironment within which the merger occurs. This contrasts with Bradley et al.(1988) finding that the division of gains between bidder and target changed infavor of the target firm after the Reagan Administration came to power inJanuary 1981. Although the exact reasons for the differences between our resultsand theirs cannot be determined, it is possible that tender offers (and theinherently competitive nature of open-market cash takeover bids) were affectedmuch more fundamentally by the regulatory changes they study than were(inherently friendly) stock-for-stock mergers.

4.3.2. Preferred stock regression resultsWhen all 135 convertible and nonconvertible preferred stock issues are

analyzed together, two variables are significant. First, the nonconglomeratevariable again implies that preferred stockholders in these mergers earn a signifi-cant 18.1 percentage point premium (t"2.23) over their counterparts in con-glomerate combinations. Second, being fortunate enough to be a preferredstockholder in a target (rather than a bidder) provides a 24.2 percentage pointpremium (t"1.90). Examining nonconvertible and convertible preferred stockissues separately yields a striking result. While none of the nonconvertibleregression variables are significant (nor is the overall F-value), the noncon-glomerate variable is both large and highly significant in the convertiblepreferred stock regression. Being involved in a nonconglomerate versus a con-glomerate merger earns a convertible preferred shareholder a 20.6 percentagepoint premium (t"2.91), which is over three times the premium commonstockholders receive and over fifteen times what nonconvertible bondholdersreceive for being involved in nonconglomerate mergers. The absolute andrelative size of this premium for convertible preferred stockholders (but notbondholders) in nonconglomerate mergers remains a puzzle.

4.3.3. Corporate bond regression resultsThe overall pattern of bond regression results is similar to that for common

stock, in that when both convertible and nonconvertible securities are analyzedtogether an impressively large adjusted R2 (0.1871) and F-value (18.35) is ob-tained, while the separate regressions of convertible and nonconvertible bondsyield lower overall explanatory power but a greater number of (and moreinteresting) significant explanatory variables. The combined-security regressionindicates, first, that convertible bondholders receive a VPE that is 18.42 per-centage points higher (t"10.44) than that earned by the average nonconvertiblebondholder and, second, that each one percentage point increase in leverage is

26 C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33

7We also estimate this equation using a Target*DLeverage interaction dummy variable, withqualitatively similar results. Most of the coefficient values on the previously estimated variables areunchanged (to the third decimal place), as is the adjusted R2 of the estimation, but the leveragevariable’s coefficient declines from !0.367 to !0.203 and becomes statistically insignificant(t"!1.03). The interaction variable is also insignificant (t"!0.93), indicating that the leverageeffect is not specific to target firm securityholders.

8These 125 bonds are selected from the full sample using a random number generator, and theappropriate Moody’s Manual is consulted to determine which covenants are present at the time ofthe merger offer announcement. Covenants are then classified into one of the nine categories inTable 5 based on one researcher’s reading of the Moody’s entry. Since these classifications areinherently subjective in many cases, a subsample of 25 bonds is then examined by a secondresearcher — without referrring to the classification assigned by the first person — and in 70 of 77 casesin which one researcher says a covenant was present the second researcher agrees. Even this mostrestrictive measure of agreement (where no weight is assigned if both parties say a covenant isabsent) implies an inter-rater reliability rate of 91%, and gives us comfort that our covenantregression results are not being driven by inaccurate classifications.

associated with a 0.37% reduction in the VPE that bondholders receive(t"!4.06).7

Analyzing nonconvertible bonds separately confirms that increasing leveragereduces bondholder VPEs (coefficient "!0.122, t"!2.11), but also yieldsthe intriguing result that bond returns are 1.86 percentage points higher(t"2.59) in nonconglomerate than in conglomerate mergers and that bond-holder VPEs declined by 1.92 percentage points (t"!2.06) after 1980. Thenonconglomerate and leverage results strengthen the conclusion that noncon-glomerate mergers create more value than do conglomerate combinations andthat merger-induced leverage increases harm all classes of securityholders.

The significant negative coefficient (!0.019, t"!2.08) on the post-1980dummy variable suggests that the takeover market changed during the 1980s ina way that was harmful to nonconvertible bondholders. As with the equityresults, it is unclear why nonconvertible bondholders in stock-for-stock mergersexperienced the same post-1980 diminution in merger-related returns thatBradley et al. (1988) document for stockholders in firms making cash tenderoffers, particularly since we cannot identify who might have benefited at bond-holders’ expense during this period (all of the other post-1980 coefficients in oursecurity return regressions are insignificant).

As a sensitivity check, we also examine whether some of these bondholderreturns can be explained by differences in bond covenants, and to our surprisefind some evidence that this is occurring. Table 5 presents a description of thefrequency with which nine types of bond covenants are observed in a randomlyselected subsample of 125 bonds (18 convertible, 107 nonconvertible). This tablealso presents the frequency of call provisions, sinking funds, and specific pledgesof security as well as the results of a regression analysis of the impact thepresence of these covenants and other features on bondholder VPEs.8

C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33 27

Table 5The effect of bond covenants and other features on bondholder valuation prediction errors forsample 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 tableprovides the frequency with which certain covenants and other features are observed in the bonddescriptions presented in the appropriate annual Moody’s Manuals, and also provides a summary ofthe regression coefficients and p-values from a regression in which bondholder valuation predictionerrors are the dependent variable and the independent variables include dummy variables indicatingthe presence of these covenants and other features. The following categories of bond covenants aredocumented: restrictions on the ability of firms to pay dividends (Dividend restrictions); covenantsspecifying minimum asset coverage ratios (Asset coverage); restrictions on indebted-firm manage-ment’s ability to execute asset sale and leaseback agreements (Sale and leaseback restrictions);covenants specifying maximum levels of additional debt that can be assumed (¹otal debt restrictions);covenants mandating minimum acceptable levels of financial liquidity (¸iquidity); covenants man-dating that any newly issued debt be of the same or junior status (Seniority restrictions); restrictionson 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 restric-tions); and restrictions on management’s ability to sell firm assets (Asset sale restrictions). The otherfeatures examined are the presence of a call option held by the issuing firm (Call provision), thepresence of a mandated sinking fund (Sinking fund provision), and whether the bond is secured byspecific pledged assets (Secured debt).

Covenant or other feature Number ofobservations

Frequency ofobservation

Coefficientvalue

Coefficientp-value

Panel A: Bond CovenantsDividend restrictions 58 46.4% !0.022 15%Asset coverage 25 20.0 0.051 2**Sale & leaseback restrictions 25 20.0 !0.011 56Total debt restrictions 18 14.4 0.005 82Liquidity 15 12.0 !0.007 84Seniority restrictions 9 7.2 !0.010 67Merger restrictions 6 4.8 0.068 3**Capital investment restrictions 3 2.4 0.009 86Asset sale restrictions 2 1.6 0.031 55

Panel B: Other FeaturesCall provision 111 88.8% !0.007 75%Sinking fund provision 73 58.4 0.0004 98Secured debt 34 27.2 !0.006 70

** Indicates significance at the 5% level.

Only three types of bond covenants are observed in at least 20% of thesubsample of bonds: dividend restrictions (46.4%), minimum asset coverageratios (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

28 C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33

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 minimum asset coverage ratio covenant increasesbondholder returns by 5.1 percentage points, and the presence of a covenantrestricting mergers and other corporate control events increases bondholderVPEs by 6.8 percentage points. The presence of call features, sinking funds, orspecific collateral pledges does not significantly affect the returns earned bybondholders in stock-for-stock mergers. These results are actually quite satisfying,because they suggest that the two covenants that arguably offer the bestprotection against merger-induced wealth redistributions from bondholders tostockholders are significantly positively related to bondholder returns. Thisconclusion is strengthened by the results of a supplemental bondholder VPEregression that includes a dummy variable proxying for the presence of two ormore covenants, rather than dummy variables for the individual covenants. Thisdummy variable is insignificant, indicating that it is the protection offered by theasset coverage and merger restriction variables themselves that is valued, ratherthan the mere presence of multiple covenants.

4.3.4. Net synergistic gains regression resultsThe 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 260stock-for-stock mergers over the period 1963—96. Two key findings emerge fromthis analysis. First, the time period dummy variables are neither statistically noreconomically significant. Total gain creation does not vary according towhether a merger occurred prior to the Williams Act of 1968, after the ReaganAdministration came to power in January 1981, or during the 1969—1980 period,mirroring the results documented in Bradley, Desai, and Kim. Second, thesignificant coefficient on the nonconglomerate merger dummy variable indicatesthat these mergers typically yield a 7.1 percentage point higher net wealthcreation than do conglomerate mergers.

5. Summary and conclusions

We examine wealth changes for 1283 publicly traded debt and equity secur-ities of firms involved in 260 pure stock-for-stock mergers from 1963 to 1996.Using a new methodology for computing market-adjusted security valuationchanges, we find no evidence that conglomerate stock-for-stock mergers createfinancial synergies or that these mergers benefit bondholders more than stock-holders. Instead, we find economically and statistically significant net synergisticgains for the securityholders of firms involved in nonconglomerate mergers, butgenerally insignificant net gains for securityholders in conglomerate mergers.

C.P. Maquieira et al. /Journal of Financial Economics 48 (1998) 3—33 29

Apart from bidding firm stockholders in conglomerate mergers, all major classesof debt and equity securityholders of both bidders and targets either break evenor experience significant wealth gains. Target firm shareholders always experi-ence net wealth gains, as do bidding firm stockholders in nonconglomeratemergers, clearly suggesting that, on average, acquiring firm managers whoexecute 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 bondhol-ders experience significant wealth increases.

Surprisingly, we find that holders of convertible securities earn extremelylarge and significant wealth increases as a result of stock-for-stock mergers. Thisresult is not driven solely by the gains accruing to target firm convertiblesecurityholders (who could capture the higher returns earned by target firmcommon shareholders by converting their securities), but is instead often higherfor bidding firm convertible securityholders. The high average convertiblesecurityholder returns result from a relatively small fraction of in-the-moneyconvertibles that experience very large (greater than 30%) wealth increases asa 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 outlierbonds that are in the money due to more favorable conversion terms relative topreferred stockholders.

The overall and security-specific wealth changes we document cannot be fullyexplained either by changes in systematic risk (since beta appears to addlinearly) or by merger-induced changes in asset return variance. Theactual post-merger variance is indeed higher than predicted, but this highervariance is not reflected in a higher VPE for the merging firms’ securityholders.Instead, regression analysis documents that stock-for-stock mergers benefitsecurityholders of the more-levered firm at the expense of the less-levered firm’ssecurityholders, and also confirms that nonconglomerate mergers create moretotal 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 befewer actual inter-securityholder wealth redistributions than our theories wouldsuggest.

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