Nicholas F. Carline, Scott C. Linn and Pradeep K. Yadav
Can the Stock Market Systematically make Use of Firm- and Deal-Specific Factors When Initially Capitalizing the Real Gains
from Mergers and Acquisitions
CFR Working Paper No. 04-08
Can the Stock Market Systematically make Use of Firm- and Deal-Specific Factors when Initially Capitalizing the Real Gains from Mergers and
Acquisitions?
Nicholas F. Carline, Scott C. Linn and Pradeep K. Yadav1
Abstract
This study empirically examines the impact of firm-specific and deal-specific factors on the change in industry-adjusted operating performance around corporate mergers and acquisitions. The factors investigated are offer size, bidder leverage, the size of bidder's cash resources, whether the bidder's and target's businesses are in the same industrial category, the method of payment selected for the merger, whether the merger was friendly or hostile, different aspects of the bidder’s ownership structure, and different aspects of the bidder’s governance arrangements. Most of these factors are being examined for the first time in this context. The empirical analysis is based on UK firms merging between 1985 and 1994, and hence the paper also reports on real gains in corporate mergers for a sample of mergers outside the U.S. Our results indicate that the performance of merged firms improves significantly following their combination. However, the extent of improvement depends significantly on the method of payment selected for the merger, and whether the merger was friendly or hostile. The change in performance is also related to director and officer ownership as well as the concentration of ownership in the hands of outside blockholders.
JEL classification: G35; C51
Keywords: Mergers; Operating Performance
1Nicholas Carline is at the Faculty of Business and Economics, Monash University, Clayton VIC 3800, Australia, tel.: 61-3-990- 52404, e-mail nicholas.carline@buseco.monash.edu.au). Scott Linn is at Michael F. Price College of Business, University of Oklahoma, Norman OK 73019, USA, tel.: 405-325-3444, e-mail slinn@ou.edu. Pradeep Yadav is at the Department of Accounting and Finance, Management School, Lancaster University, Lancaster LA1 4YX, UK, tel.: 44-1524-594378, e-mail p.yadav@lancaster.ac.uk. The authors thank the participants of the 2004 Annual Meetings of the European Finance Association and the Financial Management Association for helpful comments, specially the discussants Thomas Hardy and Adel Bino. The authors are grateful to Eduardo Lopez for research assistance, and also gratefully acknowledge the financial support of INQUIRE
Can the Stock Market Systematically make Use of Firm- and Deal-Specific Factors when Initially Capitalizing the Real Gains from Mergers and
Acquisitions?
Abstract
This study empirically examines the impact of firm-specific and deal-specific factors on the change in industry-adjusted operating performance around corporate mergers and acquisitions. The factors investigated are offer size, bidder leverage, the size of bidder's cash resources, whether the bidder's and target's businesses are in the same industrial category, the method of payment selected for the merger, whether the merger was friendly or hostile, different aspects of the bidder’s ownership structure, and different aspects of the bidder’s governance arrangements. Most of these factors are being examined for the first time in this context. The empirical analysis is based on UK firms merging between 1985 and 1994, and hence the paper also reports on real gains in corporate mergers for a sample of mergers outside the U.S. Our results indicate that the performance of merged firms improves significantly following their combination. However, the extent of improvement depends significantly on the method of payment selected for the merger, and whether the merger was friendly or hostile. The change in performance is also related to director and officer ownership as well as the concentration of ownership in the hands of outside blockholders.
JEL classification: G35; C51
Keywords: Mergers; Operating Performance
Can the Stock Market Systematically make Use of Firm- and Deal-Specific Factors when Initially Capitalizing the Real Gains from Mergers and
Acquisitions?
1. Introduction
Expected synergies are regarded as a primary reason for why mergers and takeovers occur.1 The most important way in which these synergies can manifest themselves is in terms of improvements in operating efficiency. Hence, a merger in which such efficiencies were expected would be associated with an improvement in the operating performance of the combined firm, relative to the operating performance of the two component firms before the merger. In this paper, we investigate the nuances of this hypothesis by empirically investigating the impact of firm-specific and deal-specific factors on the change in industry-adjusted operating performance around corporate mergers and acquisitions. We are particularly interested in whether the stock ownership of bidding firm directors and officers is associated with operating performance changes.
We connect real and financial market effects of mergers by asking the joint questions: a) Does managerial ownership influence the real productivity of a merger?, b) Do real productivity changes influence the financial market’s revaluation of the bidder/target pair?, and c) What are the determinants of managerial ownership in merger situations?
The factors we examine are offer size, bidder leverage, the size of the bidder's cash resources, whether the bidder's and target's businesses are in the same industrial category, the method of payment selected for the merger, whether the merger was friendly or hostile, different aspects of the bidder’s ownership structure, and different aspects of the bidder’s governance arrangements. Most of these factors are being examined for the first time in the context of operating performance changes following mergers, in particular the factors relating to the level of hostility, bidder ownership structure and board governance arrangements.
Furthermore, the empirical analysis is based on a sample of domestic UK mergers occurring during the period 1985 through 1994 for which relevant data were available before and after the merger. Hence the paper is also
outside the U.S.
There is extensive evidence both from the UK as well as the US on the stock price reactions to merger and tender offer announcements. Excellent surveys of the UK evidence include Franks and Harris (1993) and Hughes (1993), and of the US evidence, Jensen and Ruback (1983) and Jarrell, Brickley and Netter (1988).2 There is also an extensive literature on long-run post-merger equity abnormal returns both for the US and for the UK.3 Numerous studies have in addition examined merger-related changes in specific operational and structural characteristics of the firms involved. For example, Martin and McConnell (1991) examine management changes; Ravenscraft and Scherer (1988) and Herman and Lowenstein (1988) analyze earnings performance after takeovers; Ravenscraft and Scherer (1987) and Kaplan and Weisbach (1992) study divestiture activity; and Clark and Ofek (1994) investigate mergers involving "distressed" target companies to infer whether bidders are able to successfully restructure targets.4
However, the change in operating performance following corporate mergers has been directly examined on the basis of operating cash flows in relatively few studies. Healy, Palepu and Ruback (1992) find evidence of a general improvement in the operating performance of 50 US industrial mergers that occurred during the period January 1979 through June 1984. Using a similar approach, Cornett and Tehranian (1992) report improved operating performance for a sample of 30 mergers in the banking industry; more recently, Linn and Switzer (2001) use a relatively larger sample of 411 US mergers to document a general improvement in post- merger operating performance, though their main focus is on the method of payment used in the merger. Heron and Lie (2002) also document operating performance improvements for U.S. mergers. In contrast Ghosh (2001) finds no improvement for a sample of US mergers while Higson and Elliot (1994) in a study of UK mergers also report no general improvement in operating performance for their sample.5
Evidence on the relation between managerial ownership and the revaluation of the firms involved in mergers is also mixed. For instance, Lewellen, Loderer and Rosenfeld (1985) find that managerial ownership has a positive impact on bidder shareholder wealth. No such finding was reported by Sudarsanam, Holl and Salami (1996) in a study of UK mergers. These authors also find no support for the hypothesis developed in
Stulz (1988) that the relation between managerial ownership and merger announcement period returns is non- linear. Loderer and Martin (1997) find weak support for both a linear and non-linear association between managerial ownership and gains to bidder shareholders around acquisition announcements. However, they show these results are sensitive to model specification.6 To our knowledge ours is the first study to empirically examine the relation between ownership and changes in operating performance following mergers.
Our study builds on the existing literature in several ways. First, we investigate the real gains in corporate mergers for a sample of mergers (extending over a relatively long period) outside the US and the total revaluation of the target/bidder pairs in our sample. The second part of the paper examines the relation between operating performance changes, the market’s revaluation of the bidder and target firms and stock ownership by the managers of the bidding firm.
Our results provide evidence in favor of the hypothesis that mergers in the UK during our sample period were associated with improvements in operating efficiency and that the total abnormal revaluation of our bidder/target pairs are both positive and significantly different from zero. The results further suggest operating performance improvement depends significantly on the method of payment chosen for the merger, whether the merger was friendly or hostile and most importantly is positively related to managerial ownership.
In contrast, the change in performance is also shown to be inversely related to the number of directors who sit on the acquiror’s board.
Section 2 critiques relevant hypotheses regarding the potential determinants of changes in operating performance following a merger. Section 3 describes the sample and sources of the data examined. The empirical methods and results are presented in section 4. We first document the change in operating performance associated with the mergers in our sample. We then present results on the total market revaluations of the bidder/target pairs. Finally, we turn to the influence of managerial ownership on operating performance and the connection between operating performance and the financial market revaluations.
Section 5 presents our conclusions.
2. Hypotheses Regarding Merger Outcomes
One view of mergers and takeovers is that they are motivated primarily by expected synergies or operating efficiencies (Weston, Chung and Siu, 1998, Ch. 5). These synergies or efficiencies imply that the merger should arguably lead to an improvement in the operating performance of the combined firm, relative to the operating performance of the two component firms before the merger. Hence, following (Healy, Palepu and Ruback (1992) and others the hypothesis that expected synergies motivate mergers is at the core of the analysis.
Several firm-specific and deal-specific factors can potentially impact on the gains from mergers. The literature investigating attributes of mergers other than operating performance can provide guidance on the factors that could potentially be relevant in this regard. For example, Maloney, McCormick and Mitchell (1993) have shown that bidder abnormal returns are related to pre-announcement bidder leverage consistent with the arguments originally put forward by Jensen (1986).7
The size of the offer is potentially an indicator of economies of scale. A variable related to the size of the offer has been shown to be significantly related to abnormal returns inter-alia by among others Travlos (1987), Jarrell and Poulson (1989), Eckbo, Giammarino and Heinkel (1990), and Peterson and Peterson (1991).
Industry relatedness has also been offered as a partial explanation for abnormal gains in mergers. In this context, Healy, Palepu and Ruback (1992) report significant improvements in performance for mergers involving a high business overlap.
Empirical evidence consistently indicates that, at the time the offer is first announced, the share prices of both the target and bidder respond more positively to a cash takeover offer than they do to a stock offer.8 However, there have been mixed results on the relationship between long-run post-acquisition stock returns and the method of payment offered. Linn and Switzer (2001) do however present evidence that the operating performance of US mergers tends to be larger for cases in which cash was the principal form of payment.9 Their results are consistent with the theories developed by Fishman (1989) and Berkovitch and Narayanan.
(1990). Fishman (1989) argues that bidders use cash to deter competing bids when they have favorable private information indicating a high value for the target, potentially due to synergies. Berkovitch and Narayanan (1990) argue that a large cash offer increases the likelihood that the target will accept the initial bid and eliminates any delay during which other firms might offer competing bids. Important to their argument is the fact that the share of synergistic gains captured by the bidding firm increases with the fraction of the offer represented by cash. Thus, bidders with very favorable private information about future excess operating returns would tend to use larger amounts of cash in their offers, both to deter competition and to ensure that they capture a large share of the synergistic gains. In contrast, Herron and Lie (2002) using a sample of U.S.
takeovers from a later time period find no relation between operating performance changes and the fraction of the transaction paid with cash.
One view of hostile bidding environments is that they are likely to have an adverse impact on ex-post operating performance, since the disagreement and hostility between the top management teams of the two merging firms, present in such cases, could potentially lead to a loss of critical staff, or to unwise dismissals, or to other actions that harm productivity. The idea that hostile offers are deleterious is the counterpart to the view that friendly takeovers lead to good relations and the realization of positive synergies (Morck, Shleifer and Vishny, 1988, 1989). On the other hand, Schwert (2000) in a study of stock returns has recently argued that hostile offers are economically indistinguishable from friendly offers.
Harford (1999) shows inter-alia that the cash resources of the bidder can potentially influence the gains from mergers. In this context, it has been argued that the managers of bidder firms with excess cash resources can potentially be prone to spend "unwisely", and enter into deals that are not as well thought through and hence not likely to do as well later. This in essence is a specific case of the argument made in Jensen (1986) that firms with excess cash will tend to waste those funds on negative net present value investments.
There is a large volume of literature addressing the issue of whether or not stock ownership plays an important part in aligning the interests of managers and shareholders. (Murphy, 2000) These studies have
taken many forms, from determining whether officer ownership is associated with better firm performance, to establishing whether ownership incentives have any influence on a range of managerial decisions. However, there is surprisingly little evidence relating managerial financial incentives to merger/takeover operating performance. The investigations that have been conducted in this area examine abnormal share price returns, not real operating performance gains, and also reach differing conclusions. Loderer and Martin (1997) find weak support for both a linear and non-linear (Stulz, 1988) association between the stock ownership of bidding firm managers and gains to bidder shareholders around acquisition announcements. Managerial ownership incentives and the abnormal returns to mergers remains an unresolved empirical issue, and there is little known empirically about the relation between ownership and changes in operating performance following mergers.
Within any group of officers and directors a distribution of ownership shares can be identified as well as the sum of all the holdings of the group. Suppose we fix the total number of shares held by a group of officers and directors and consider the distribution of shares across group members. Two polar extremes are the cases in which a) one member owns all the shares held by the group, and b) all of the group members hold an equal number of shares. The inequality of the ownership distribution as reflected by a comparison of case a relative to case b suggests what we will call an ‘inequality of ownership’ effect. The greater the inequality of ownership the more the shares are concentrated in the hands of a few directors or officers.
Several outcomes of the ‘inequality of ownership’ effect are possible. First, greater inequality implies that that many members of the group hold low levels of ownership and thus have low incentive to monitor the behavior of the officers. This may lead to greater abuse of power and the wasting of assets, especially if those who hold this power gain utility from overseeing larger companies. Thus for a given level of total holdings by the group, those firms with greater inequality of shareholdings within the group of officers and directors may be associated with poorer merger outcomes. Conversely, if officers and directors pursue a goal of value maximization, greater inequality can imply that decision-making authority is concentrated in the hands of those who have high incentive to allocate resources wisely. Thus for a given level of total holdings by the group,
those firms with greater inequality of shareholdings within the group of officers and directors may be associated with better merger outcomes. The dominant effect is of course an empirical question.
Monitoring by large shareholders has been suggested as another mechanism contributing to the alignment of managers’ and shareholders’ interest (Shleifer and Vishny, 1986; Holderness and Sheehan, 1988; Stulz, Walkling and Moon, 1990). Based on the available evidence, large shareholders do not appear to be influential in merger decisions (Loderer and Martin, 1997), and may actually be detrimental (Sudarsanan, Holl and Salami, 1996) by encouraging managers to engage in wealth-decreasing combinations. Likewise, whether or not the degree of concentration amongst large shareholders has any impact on this non-existent or negative relationship has yet to be determined.
Other corporate control mechanisms studied in the literature relate to board governance structures, in particular, whether the CEO is also the board chairman (Brickley, Coles and Jarrell, 1997), and the proportion of independent outside directors on the board and board size (Yermack, 1996). Byrd and Hickman (1992) find evidence that bidders engage in wealth-increasing mergers when their boards are dominated by independent outside directors. Whether or not board governance structures influence the real gains from mergers, in the form of changes in industry adjusted operating performance has not been examined. Yermack presents evidence indicating value is decreasing in board size.
3. The Sample
The initial sample for this study consists of all bidder and target pairs involved in mergers of domestic UK companies during the period 1985 through 1994. The initial sample of UK mergers was obtained from the files of the London office of Securities Data Company (SDC). Accounting and market value data are obtained from Datastream. Included cases are required to have complete accounting data available from Datastream for at least three of the five years before the combination and three of the five years after. Data pertaining to ownership and governance structure were collected from company reports obtained from Companies House.10 Characteristics of the events and the deals themselves were collected from the files of the SDC and public
news sources. The final sample includes 81 mergers for which we were able to obtain pre- and post- merger performance data for the bidder and target from Datastream along with a complete set of measurements for the independent variables used in the analyses.
4. Empirical Results
4.1 The Analysis Of Operating Performance 4.1.1 Preface
An operating performance measure must be capable of revealing any productivity or efficiency changes that are a consequence of the combination. As Healy, Palepu and Ruback (1992) have noted, the change in net income after taxes is inadequate in this regard for several reasons. First, net income (net of interest and taxes) as a measure of performance may be affected by both the accounting method used for the acquisition and by the choice of financing. For example, when acquisitions are accounted for by the purchase method, the combined entity will report lower earnings than if the pooling method of accounting is used. The purchase method requires the target's assets and liabilities to be recorded at their current market value. The result is an increase in the amount of depreciation expense and a decrease in reported earnings. Goodwill may be written off immediately in the UK for reporting purposes, but is not a tax-deductible expense. Both have the effect of reducing reported net income. Second, post-acquisition net income may also be affected if the bidder issued debt or sold marketable securities to raise the funds for a cash offer. If the bidder raised cash through an increase in debt, interest expense will increase; if, however, selling marketable securities is used to raise cash, future interest income will decrease. Either situation will reduce reported net income.
We measure operating performance in any year as income before taxes and extraordinary items, plus depreciation and goodwill, plus net interest income. Note in particular that we exclude extraordinary items from the calculation, as they would clearly bias the result since they are typically nonrecurring. The definition of operating performance used in this study is unaffected by depreciation, goodwill, or the type of financing used to fund the acquisition. Changes in the measure examined should therefore be an accurate indicator of
productivity/efficiency effects that result from a combination.
4.1.2 The Benchmark For Operating Performance
Changes in operating performance resulting from an acquisition are evaluated by comparing the pre- acquisition control firm-adjusted performance of a portfolio, consisting of the bidding and target firms, to the actual post-acquisition control firm-adjusted performance of the combined entity. The pre-acquisition performance of the portfolio is conceptually an indicator of how the two separate firms would have performed if they had remained independent after adjusting for industry effects. The simple change in adjusted performance may not be a totally accurate assessment of improvement, however, if post-combination performance is correlated with pre-combination performance. We measure abnormal performance first using the simple change and then after taking this potential correlation into account.
The pre-acquisition cash flow return for year t is the sum of the cash flows of the bidder and target firms for combination i deflated by the sum of their asset values:
ASSET ASSET +
+ CF CF
= CF
i T, i
B,
i T, i
B,
i (1)
where cash flows for the individual firms (CFB,i and CFT,i) are measured as pre-tax earnings before depreciation, goodwill, interest expense, and interest income from short-term investments, and B and T denote
“bidder” and “target” respectively11. These data are obtained from Datastream. The variable ASSET is computed as of the beginning of each sample year, during the pre-acquisition period, and is equal to the market value of equity calculated using share price and the number of outstanding shares, plus the book values of net debt and preferred stock.
A separate control portfolio is constructed for each bidder and each target. For instance, the industry control portfolio for a particular bidder consists of those firms with the same SIC code as the bidder. The industry portfolios are denoted with the subscripts B-I and T-I for the bidder and target industries respectively.
The bidder and target are excluded from the control portfolios. The cash flow performance of these portfolios
is the benchmark against which actual performance is compared. Because the number of comparable firms for an industry varies across the sample cases, and to avoid the influence of outliers, median values are used instead of sample averages.
The industry cash flow return for combination i in year t is computed as a weighted average of the cash flow returns for the bidder and target industry portfolios, where the weights are the relative asset sizes of
the bidder (ASSETB,i) and the target (ASSETT,i):
. ASSET CF ASSET + ASSET
ASSET
+ ASSET CF ASSET + ASSET
ASSET
= CF
i I, - T
i I, - T i
T, i
B, i T, i
I, - B
i I, - B i
T, i
B, i B, i
I, ⎟⎟
⎠
⎞
⎜⎜
⎝
⎛
⎟⎟
⎠
⎞
⎜⎜
⎝
⎛ (2)
The cash flow return for the bidder's (or target's) industry is the median operating cash flow for the respective portfolio deflated by the median asset value. The ASSET weights adjust for the relative contributions (in terms of size) of the bidder and target firms to the combined entity.
The pre-acquisition benchmark, representing the performance in year t of the bidder-target portfolio prior to the combination indexed i, is the difference between CFi (equation (1)) and CFI,i (equation (2)):
. CF - CF
=
IACF pre,i i I,i (3)
This benchmark represents the industry-adjusted performance that would be expected for the period following the actual combination, assuming that the two firms did not merge. Post-acquisition performance in year t is measured as the actual cash flow return for the combined firm in that year, adjusted for industry performance during the same period. Industry performance is computed as in equation (2) using data from the post- combination period except that the ASSET weights are the relative asset sizes of the bidder and target firms one year prior to the acquisition. Post-acquisition industry-adjusted cash flow performance is labeled
IACFpost,i, again suppressing the time subscript.
4.1.3 A Comparison Of Pre-Combination And Post-Combination Performance
The median cash flow return for the five-year period preceding a combination serves as our forecast
of how the bidder and target together would have performed had they not combined. We label this quantity where combinations are indexed by i. The corresponding median for the five years
following the combination is labeled . We compute the difference between the five-year median pre-acquisition performance and the five-year median post-acquisition performance for each combination and label this difference
i ,
OPCFRETPRE
i ,
OPCFRETPOST
OPCFRETi
∆ .
Panel A Table 1 reports the operating performance results for the combinations in the sample.12 The medians as well as the means of across combinations are reported for the pre- amalgamation and post-amalgamation periods. The panel also reports the mean and median change.
(POST),i
OPCFRETPRE
13 The third column of Panel A reports the percentage of the sample cases having positive values for
and (POST ,i
OPCFRETPRE ) ∆OPCFRETi. We test whether pre and post combination grand mean and medians are significantly different from zero using conventional methods. The results show that the pre amalgamation grand mean and median are not significantly different from zero. In contrast the post amalgamation mean and median are significantly different from zero at the .01 level. Finally, tests of whether the grand median (grand mean) change in performance is significantly different from zero soundly rejects the null hypothesis.
The combinations in the sample do not outperform their industries before the acquisition. In each of the years –5 through –1 we also tested whether the mean (median) industry-adjusted cash flow return across cases is equal to zero.14 We cannot reject the null at the .01 level for any year. However, after the acquisition there is a marked difference between the performance of the sample cases and that of the industry benchmarks. Industry-adjusted cash flows show a significant overall improvement in the post-acquisition period, as is evident by the median difference of 6.39% (mean: 10.67%) for the overall sample (Table 1, Panel A). We reject the null that the mean (median) is equal to zero at the .01 level. These results provide strong support for the hypothesis that the mergers in our sample are associated with improvements in operating performance, consistent with the results presented by Healy, Palepu and Ruback (1992), Linn and Switzer
(2001) and Heron and Lie (2002) for mergers between domestic US corporations. Higson and Elliot (1994) present results for a sample of UK mergers that show operating performance in general did not improve, but that there was evidence of improvement for the 50 largest takeovers in their sample. Powell and Stark (2001) likewise present results suggesting that the operating gains in UK mergers are not unequivocally positive in their sample. The Higson and Elliot results may however be influenced by the empirical method employed as is suggested by the results in Powell and Stark. Ghosh (2001) and earlier in a general context Barber and Lyon (1996) have addressed the measurement issue. We turn to the implications of their conclusions for our results in the next section.
In summary, the results presented in Panel A of Table 1 indicate that operating cash flow returns for our sample of UK mergers are larger after the combination than the cash flow returns that would have been expected if the two firms had not combined.
4.1.4 A Further Look At The Basic Results
Ghosh (2001) in a study of US mergers has recently suggested that in cross-sectional regression models intended to explore the determinants of changes in operating performance following mergers the dependent variable should equal the actual change in performance, what we heretofore defined as ∆OPCFRETi . Several authors have conversely inferred performance changes from the estimated intercept in the regression of post industry-adjusted performance on pre industry-adjusted performance (Healey, Palepu and Ruback, 1992, Higson and Elliott, 1994); Linn and Switzer, 2001). Ghosh provides guidance on when the change model and the intercept model will produce biased results. The essence of the issue is an errors-in-variables problem. Ghosh shows that under a reasonable set of assumptions the change in cash flow performance will provide an unbiased estimate of performance changes. Specifically when the performance of the sample firms is not significantly different from their industry counterparts during the preacquisition period, the change model will provide unbiased estimates of improvement.15 Ghosh’s suggestions are similar to the general prescriptions offered by Barber and Lyon (1996) on the measurement of
operating performance changes following corporate events. We tested the null hypothesis that the yearly industry-adjusted performance values for years –5 through –1 are equal to zero, and could not reject the null. We conclude that the change model should therefore provide a reasonably unbiased estimate of the change in operating performance and hence employ the change in operating cash flow return as our measure of operating improvement.16 Panel B of Table 1 presents evidence also in support of using the change measure. Two regression models are reported in Panel B. In the first model we regress on and an intercept. Both the intercept and the slope estimates are positive and significantly different from zero. However the slope coefficient is not significantly different from one (t = 0.54). In the second model we regress the change variable
i ,
OPCFRETPOST OPCFRETPRE,i
OPCFRETi
∆ on and an intercept. The slope coefficient in this case is not significantly different from zero. As we have already indicated, the mean and median changes (Table 1, Panel A) are significantly different from zero at the .01 level. We conclude from these results that the firms in our sample experienced significant improvements in operating performance following these merger events.
i ,
OPCFRETPRE
17
4.2. Variables Used in Cross-Sectional Tests of the Economic Hypotheses The hypotheses outlined in Section 2 suggest relations between the
change in operating cash flow return and specific factors related to the deal and to the presence of potential synergies or efficiencies and to governance related factors. Table 3 lists the explanatory variables we employ in the analysis, how they are measured and the source of the data used in their construction. Two broad categories are defined: Deal specific and synergy variables, and, Agency variables. Table 4 presents descriptive statistics for each of the variables and Table 5 presents the correlations between the variables.
4.2.1 Deal Specific Factors
We test the influence of several factors that characterize the deal or the immediate environment at the time of the deal, all of which proxy for various elements of the hypotheses discussed in Section 2. These
STOCK One if the amalgamation was effected via a stock swap offer, zero otherwise HOSTILE One if acquiree officers and/or directors were initially opposed to amalgamating
with their acquiror, zero otherwise
CONTEST One if acquiror faced competition from a would-be acquiror in securing their amalgamation, zero otherwise
RELSIZE Total value accepted for acquiree’s equity as a percentage of acquiror’s market value 5 days before their merger or acquisition announcement date
Table 6 reports the results of univariate regressions involving these factors.
The factors STOCK and HOSTILE both have estimated coefficients that are significantly negative. The result for the coefficient on STOCK is consistent with the result reported by Linn and Switzer (2001) for a sample of US mergers and by Ghosh (2001) who also studies US mergers. The result itself is broadly consistent with the theories developed in Fishman (1989) and Berkovitch and Narayanan. (1990) in which bidders essentially bid cash when positive operating gains are expected. The negative coefficient for the HOSTILE dummy is consistent with our earlier conjecture that hostile offers may have a disruptive organizational effect that leads to inefficiencies. We find the estimated coefficient on the dummy variable CONTEST is not significantly different from zero.
Table 6 also reports on the effects of the size of the offer relative to the size of the bidder. There are at least two possible influences of the size of the deal on subsequent operating efficiencies. First, large offers may lead to economies that produce synergistic gains. Second, large offers may lead to situations in which a large organization must be folded into the bidder’s organization. A span of control issue may thus arise in which coordination is difficult and in the extreme inefficiencies arise. We transform RELSIZE by taking its natural log. We cannot reject the null hypothesis that there is no relation between the change in operating performance and LnRELSIZE.
4.2.2 Factors Related To Potential Synergistic or Efficiency Effects
We explore whether there are mean effects due to factors that are related to the relative characteristics of the bidder and target at the time of the offer which may proxy for synergistic or efficiency effects. These characteristics are designed to proxy for the relative strengths or weaknesses of the bidder versus the target. A set of dummy variables are defined:
FOCUS One if acquiror and acquiree had equivalent primary industry codes at the time of
their amalgamation, zero otherwise
RELQRATIO Difference between acquiror’s and acquiree’s QRATIO if acquiror had matched or outperformed and acquiree had under-performed the median firm in their primary industry at the fiscal year end before amalgamation, zero otherwise
RELLEV Difference between acquiror’s (aquiree’s) and acquiree’s (acquiror’s) LEV if acquiror was at or above (below) and acquiree was below (at or above) the level for the median firm in their primary industry at the fiscal year end before amalgamation, zero otherwise
RELCASHLIQ Difference between acquiror’s (acquiree’s) and acquiree’s (acquiror’s) CASHLIQ if acquiror was below (at or above) and acquiree was at or above (below) the level for the median firm in their primary industry at the fiscal year end before amalgamation, zero otherwise
Table 6 reports the results of tests for whether mean effects due to the above factors are present.
The coefficient on the variable FOCUS is positive as would be expected if combinations of firms operating in related industries lead to synergies. This result is consistent with the hypothesis that the mergers in the sample experienced improvements in operating performance due to increased efficiencies or synergies.
While the point estimate of the coefficient has the correct sign, we cannot however reject the null hypothesis that it is equal to zero at conventional significance levels.
The coefficient on the variable RELQRATIO however would appear to have the wrong sign. If bidders/acquirors have historically engaged in value increasing investments relative to their peers while targets have not, the expectation would be that acquisition of such a target would lead to operational changes that would improve its performance and hence the performance of the overall company would improve. A negative point estimate is inconsistent with this hypothesis. Nevertheless as with the factor FOCUS we cannot reject the null hypothesis that the coefficient is equal to zero.
Numerous authors beginning with Jensen (1986) suggest that firms with excess cash will be prone to waste those funds on poor investments. The factor RELCASHLIQ captures the case where the acquiror is not characterized by a situation of excess cash (relative to its peers) while the target does. We would expect from these arguments that the coefficient on this factor would be positive as the acquiror would be expected to make value increasing decisions while the target would represent a prime candidate for the eradication of a poor decision making environment. We cannot conclude that the estimated coefficient on this factor is significantly different from zero, and further its sign is contrary to the hypothesis. Likewise the estimated coefficient on the
variable measuring the relative leverage of the combining firms is not significantly different from zero.
We conclude from these results that mean effects due to relative strengths or weaknesses of the bidder and target do not appear to be present. This of course suggests that other forces must be at work. We turn next to explanations that are related to the governance structure of the acquiror at the time of the offer.
4.2.3 Factors Related To The Governance Structure And Characteristics Of The Acquiror
We examine specific governance characteristics of the acquiror and whether they are related to changes in performance that accompany the merger. Specifically the variables examined include:
QRATIO Valuation ratio [SIZE divided by book value of assets] of acquiror minus that of the median firm in their primary industry at the fiscal year end before amalgamation CASHLIQ Cash liquidity [book value of cash and equivalents as a percentage of SIZE] of
acquiror at the fiscal year end before their amalgamation if QRATIO is negative, zero otherwise
LEV Leverage [book value of long- and short-term debt as a percentage of SIZE] of acquiror at the fiscal year end before their amalgamation
BOARDOWN Percentage of acquiror outstanding equity shares accounted for by the beneficial interests of its officers and/or directors at the fiscal year end before the firm’s amalgamation
DISPBOARDOWN Thiel index of dispersion for the beneficial interests of acquiror officers and/or directors at the fiscal year end before the firm’s amalgamation
BLOCKVOTES Herfindahl index of concentration for acquiror equity votes controlled by non officer and/or director related block-holders with a stake of at least five percent at the fiscal year end before the firm’s amalgamation
BLOCKVOTESDUM One if BLOCKVOTES is at least 25, zero otherwise
CEOCHAIR One if the highest paid acquiror officer had been Chairman for at least two years before the firm’s amalgamation, zero otherwise
BOARDSIZE Number of acquiror directors at the fiscal year end before the firm’s amalgamation OUTDIR One if the amalgamation was effected in 1984 and increasing in units of one for
each subsequent year up to 1994
SIZE Market value of assets [market value of equity plus book value of preferred stock and long- and short-term debt] of acquiror at the fiscal year end before their amalgamation
REGULATED One if acquiror had a media or telecommunication services primary industry code at the time of their amalgamation, zero otherwise
While most of our measures are transparent, the variable DISPBOARDOWN needs clarification. The Theil T index, Theil (1967), is a scale free measure of inequality. Following Kosnik (1990), Thiel’s index of dispersion is deemed to the best direct scale-invariant measure of dispersion when a variable, such as managerial ownership, has a diminishing marginal effect.18 In our case we employ this variable as a measure of the inequality of ownership across the officers and directors of the bidder. The variables OUTDIR and REGULATED are included as controls. The Cadbury Report established specific voluntary guidelines for
governance structures in UK companies that have been widely adopted, along with recommendations in subsequent Reports. OUTDIR accounts for the structural break due to the Cadbury Report.
We find that only one of the variables examined has a statistically significant estimated coefficient in the univariate regressions. The variable CASHLIQ measures excess cash liquidity for acquiror’s that have below normal Q ratios. Thus, this set of firms represent potentially poor performers who have excess cash.
The estimated coefficient on CASHLIQ is negative suggesting that poor performing firms with excess cash may make merger decisions that are poor choices in terms of operating performance of the merger.
4.2.4 Multivariate Analysis
The univariate results presented in Table 6 while suggestive, are potentially limited if there are multiple factors simultaneously influencing operating performance. Table 7 presents the estimated coefficients for three expanded regression models. Column (1) presents the results for a model that includes only Deal specific and synergy variables. Column (2) presents results for a model including only Agency variables, and column (3) reports results for a model including all variables.
The results reported in column (1) indicate that the estimated coefficients for the variables STOCK and HOSTILE are negative and significant at conventional levels. We cannot reject that the coefficient on CONTEST is insignificantly different from zero.
We expand on the span of control issue by introducing a dummy variable RELSIZEDUM that takes the value 1 when the size of the deal is 25% or greater of the size of the bidder. We also interact this variable with the continuous measure of the relative size of the deal, imposing the maintained hypothesis that large deals have potential effects and that these effects are increasing in the relative size of the deal above some threshold. We find that the coefficient on this interaction variable is negative and marginally significant. The conclusion is that if there are benefits as well as costs that are correlated with the relative size of the deal, the net effect in our sample is negative. The remaining variables reported in column (1) do not have coefficients that are significantly different from zero.
Column (2) reports the results for a model examining the influence of governance characteristics of the acquiror on subsequent operating performance. The change in operating cash flow performance is larger the larger are the beneficial stock ownership interests of the officers and directors (BOARDOWN). However, when we weight these interests by a measure of the dispersion of ownership within this group we find that the change in ownership is inversely related to the weighted variable. The latter result suggests that while overall ownership is beneficial, when any single director or officer’s stake is small (when the dispersion index is large) the benefits of inside ownership are smaller. We assess the influence of outside blockholders with the variable BLOCKVOTES which measures the concentration of the interests of holders of 5% or more of the shares. The estimated coefficient on this variable is positive and significant. Performance is inversely related to the size of a company’s board (LnBOARDSIZE) consistent with results presented by Yermack (1996). Our results tend to support this result.
Column (3) presents the estimated coefficients for a model including both categories of variables. The conclusions drawn from the estimates reported in column (3) are largely the same as those drawn from columns (1) and (2). The only new result is that the estimated coefficient on the variable RELLEV is now significantly different from zero at conventional levels.
We conclude from these results that characteristics of the deals themselves as well as the governance structure of the acquiror play a role in determining the change in operating performance for the mergers in our sample. In particular the results suggest that both inside as well as outside ownership have a positive influence.
5. Conclusions
This study examines the change in industry adjusted operating performance of 81 UK firms that merged between 1985 and 1994. The results indicate that the performance of the merged firms improves significantly following their combination. Cross-sectional tests of the determinants of these gains and their relation to received theory suggest that both deal specific as well as bidder specific governance factors are
associated with the change in cash flow operating performance. Specifically we find that stock offers and hostile offers are associated with smaller changes than are cash or nonhostile offers. We also conclude that larger offers tend to be associated with lower gains. With respect to bidder characteristics we find evidence that ownership of directors and officers is positively related to operating performance change but that this is mitigated when the ownership interests of any single director or officer are small. Further concentration of ownership in the hands of a few outsiders has a positive influence. Finally, there is also evidence that performance changes are worse when bidders have large boards of directors.
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Table 1
Descriptive statistics for operating cash-flow returns around amalgamations (Panel A), and regressions of operating cash-flow returns resulting from amalgamations on pre-amalgamation returns (Panel B), for a sample of UK mergers and acquisitions effected during the period 1985-94.
Panel A: Descriptive statistics for operating cash-flow returns around amalgamations
Mean Median Proportion positive
Pre-amalgamation period -0.94 -0.90 0.42
Post-amalgamation period 9.72 4.36 0.77
Change resulting from amalgamation 10.67 6.39 0.81
Panel B: Regressions of operating cash-flow returns resulting from mergers and acquisitions on pre-amalgamation returns
OPCFRETPOST,i = 10.89 + 1.24 OPCFRETPRE,i R-squared = 14.03 (5.22) (2.83)
OPCFRETCHANGE,i = 10.89 + 0.24 OPCFRETPRE,i R-squared = 0.61 (5.22) (0.55)
Operating cash-flow returns are defined as earnings before depreciation, interest expense, taxation, and income on short-term investments, as a percentage of market value of assets at the relevant fiscal year end. Amalgamating firms’ operating cash-flow returns are industry adjusted by subtracting the median return for other firms in the same primary industry. In the pre-amalgamation period, the performance measure for the pseudo- combined firms is a weighted average of acquiror and acquiree returns, where the weights are relative asset values. In the post-amalgamation period, the performance measure for the combined firms’ industry is a weighted average of acquiror and acquiree industry median returns, where the weights are again relative asset values.
Amalgamating pairs of firms, represented in the sample, have at least three common years of operating performance history during both the five years preceding and following their amalgamations. Changes in operating cash-flow returns (OPCFRETCHANGE,i for combined firm i) are defined as the difference between the post- and pre-amalgamation median annual operating cash-flow returns (OPCFRETPOST,i for combined firm i and OPCFRETPRE,i for pseudo-combined firm i). Datastream is sourced to compute operating cash-flow returns. The sample size and number of observations in both Panels is 81. Panel A values are statistically significant exceeding the 0.01 level, except those for the pre-amalgamation period which are not significant at conventional levels. Panel B values in parentheses are t-statistics from White standard errors.
Table 2
Descriptive statistics for amalgamating firm asset revaluations around amalgamation announcements (Panel A), and regression of changes in operating cash-flow returns resulting from amalgamations on pseudo-combined firm asset revaluations around amalgamation announcements (Panel B), for a sample of UK mergers and acquisitions effected during the period 1985-94.
Descriptive statistics for amalgamating firm asset revaluations around merger and acquisition announcements
Mean Median Proportion positive
Acquirors -0.004 -0.008 0.41
Acquirees 0.169 0.128 0.91
Pseudo-combined firms 0.033 0.023 0.63
Amalgamating firms’ asset revaluations are defined as abnormal equity returns weighted by market value of equity to assets ratio at the fiscal year end before their amalgamations. Abnormal equity returns are continuously compounded market model adjusted changes in equity values from 5 days (acquirors) or 30 days (acquirees) preceding merger or acquisition announcement dates to 5 days following the amalgamations becoming effective. Acquirees are given an earlier announcement date if their acquirors faced competition from a would-be acquiror in securing the amalgamation. Market model parameters are estimated from 500 to 101 days before the relevant announcement dates, using FTSE All Share total returns. Asset revaluations for the pseudo-combined firms (ASSETREVi for pseudo-combined firm i) are defined as the weighted average of acquiror and acquiree returns, where the weights are relative asset values. Datastream is sourced to compute asset revaluations. The sample size and number of observations for all descriptive statistics is 81. All values are statistically significant exceeding the 0.05 level, except those for acquirors which are not significant at conventional levels.
