An empirical analysis of tender offers and proxy contests

Determinants of the choice of the hostile takeover mechanism: an empirical analysis of tender offers and proxy contests

Uma V. Sridharan

Tender offers and proxy fights determine who possesses the right to manage corporate resources. In a tender offer, the bidder makes a direct offer to the firm’s shareholders to purchase their shares and consequently to capture their voting rights. In a proxy contest, insurgents conduct a campaign to persuade shareholders how to vote on contested issues and board seats. The effects on stockholder wealth associated with tender offers and proxy fights are well-documented and differ significantly.(1) Jensen and Ruback (1983) report a 30% abnormal stock price gain with a successful corporate takeover by tender offer but only an 8% increase with a successful takeover by proxy contest. For unsuccessful attempts, they report a 4% abnormal price loss for tender offers and an 8% gain for proxy contests. Given these different wealth outcomes for target firm shareholders, it seems important to understand the factors that influence the choice between a tender offer or proxy contest.

The spate of corporate charter amendments and anti-takeover legislation enacted since the mid-1980s may change the takeover environment (see Karpoff and Malatesta (1989)). As a consequence, the legal and economic conditions in the early 1990s may appear to favor proxy contests over hostile tender offers as a means to ensure that managers maximize firm value. However, DeAngelo and DeAngelo (1989) and Mulherin and Poulsen (1993) suggest that there is a growing trend towards using both tender offers and proxy contests as complementary mechanisms for taking control of a firm. There also appears to be some preference in the nineties for choosing negotiation over war. (For example, in October 1991, the California Public Employee Retirement System “put the brakes on its five-year campaign of using shareholder proxy resolutions to try and gain a voice in corporate affairs.”(2) and instead decided to negotiate for changes.) Yet, one can reasonably expect that both proxy contests and tender offers will continue to exist.(3) Thus, it remains important to understand the choice of takeover method and to investigate the target firm characteristics that might influence the form of a control contest.

The literature on corporate capital structure, ownership structure, and takeovers suggests two sets of potential factors that might significantly influence the decision to pursue a hostile tender offer or a proxy contest. They are:

1) target firm ownership structure as reflected in ownership and capital structure data

2) target firm performance as reflected in accounting and market return data

This literature, which motivated our analysis of the proxy-tender choice along these lines, is discussed next.

I. Research Motivation and Literature Review

The potential relationship between a target firm’s ownership structure and the choice of a takeover mechanism is not a new idea. For example, Manne (1965) suggests that tender offers are more likely than proxy fights when a relatively large proportion of voting rights are held in large blocks not held by managers. In Manne’s seminal analysis, proxy fights are selected more often in management-controlled firms where the rival wishes to control the distribution of managerial compensation. Other researchers have also acknowledged and documented the importance of ownership structure in corporate decision making and behavior.(4)

Ownership structure may reflect important target firm differences. For example, Williamson (1967) hypothesizes that managers in management-controlled firms attempt to control and manipulate information so as to keep current shareholders satisfied. In this vein, Salamon and Smith (1979) show that managers in management-control led firms may misrepresent firm performance information contained in annual reports. More generally, Jensen and Meckling (1976) argue that managers in management-controlled firms tend to divert resources away from shareholders and to themselves.

Ownership structure is clearly an important factor in different phases of a control contest. The managerial response to a takeover attempt is related to the manager’s share ownership (see Morck, Schleifer, and Vishny (1988a) and Walkling and Long (1984)). Also, the distribution of voting rights in a target firm affects the price and probability of success in a tender offer (see Mikkelson and Partch (1989) and Stulz (1988)). Thus, given these findings, the potential effect of corporate ownership structure on the form of a control challenge merits investigation.

The capital structure decisions of the target firm affect its ownership structure and may reflect the managers’ desire to retain control of the firm.(5) A firm’s management can alter the fraction of voting rights it controls through capital structure changes. One possible motivation to take such action is the threat of a takeover attempt. Harris and Raviv (1988) suggest that a target firm’s capital structure may influence the form of the control contest it faces. In their model, incumbent management exchanges debt for equity as a defensive response to the takeover threat. Within the framework of this model, however, leverage increases are not identical for tender offers and proxy fights. Amihud, Lev, and Travlos (1990) also show that capital structure may be used as a defensive mechanism. Raad and Ryan (1995) and Sridharan (1990) show that capital structure, in combination with ownership structure and firm size, can help explain opposition to, and the outcome of, a tender offer. Corporate insiders prefer debt financing over new issuances of stock because new stock dilutes their holdings and increases the risk of losing control. Capital structure changes usually translate into ownership structure changes. Hence, we directly include some capital structure variables in our analysis to test the ownership hypothesis.

Firm performance as measured by accounting data may also influence the decision to pursue either a hostile tender offer or a proxy fight. Duvall and Austin (1965) suggest that poor firm performance can be a motivating factor in the decision to undertake a proxy contest. They find that stockholders are more likely to give their support to insurgents if earnings are poor.

In a proxy fight, target firm shareholders do not receive compensation in cash or equity for transferring their votes to the rival. Instead, they are promised improved prospects. If the rival argues that the target firm management is inefficient, then perhaps the only way this claim can be persuasively supported is through publicly available accounting numbers. In this case, a proxy fight may be undertaken rather than a tender offer.

If the motive for the takeover is not inefficient management but some type of operating synergy, then a tender offer may be more likely. In a tender offer, target firm shareholders are directly and immediately compensated for transferring their votes. If the accounting numbers cannot demonstrate poor performance, direct compensation may be the only means by which the rival can effectively convey the benefits of the corporate combination to the target firm shareholders. Thus, observable firm performance may signal the takeover motive and dictate in part the form of the takeover.

While previous theoretical research models the impact of capital structure and ownership structure on the outcome of a takeover bid,(6) scant theoretical work exists that explicitly models the choice of takeover mechanism (Harris and Raviv (1988) is an exception). This absence is surprising. Clearly, a corporate raider can try to take over a firm through the use of a tender offer or a proxy fight. Given the relative paucity of proxy fights, prior research merely suggests that proxy fights are more costly than tender offers or that the benefits of tender offers are greater than those of proxy fights (Shleifer and Vishny (1986)). However, no systematic attempt has been made within a theoretical model to link the choice of a tender offer versus a proxy fight to capital structure, ownership structure, or firm performance in a theoretical framework. This paper is not intended to fill this theoretical gap. It does, however, offer an empirical exploratory analysis regarding the choice of a tender offer versus proxy fight. Thus, the purpose of the paper can be viewed as more descriptive than as the formal hypothesis testing of a well-defined theory. Nonetheless, the information gleaned from this analysis may very well assist in the development of formal theories about the choice of the hostile takeover mechanism.

Analysis of previous research leads us to investigate empirically two sets of factors that might influence the choice of the hostile takeover mechanism: 1) ownership structure and 2) firm performance. The organization of this paper is as follows. Section II presents the design of the sample and the sources of the data. Section III contains definitions of the ownership structure and firm performance variables and presents descriptive statistics for these variables in targets of proxy fights and tender offers. In Section IV, a logistic regression model is employed to model the choice of a hostile tender offer. The last section of the paper offers interpretations and conclusions.

II. Sample Design and Data Sources

The initial data sample contains all target firms that received tender offers for control or experienced proxy contests for board seats from 1978 to 1985. Tender offer data for the period 1978-84 derive from a database compiled by Martin and McConnell (1991); data for the year 1985 come from the Tenderbase (1985) database. The names of firms that experience proxy contests are compiled from prior research papers on proxy contests (Castanias and Johnson (1988) and Pound (1988)) and from a survey of the Wall Street Journal Index (1978-85). The announcement date for a control contest is the date it is first reported in The Wall Street Journal. Relevant information for all contests is collected and verified with citations from the Wall Street Journal Index and The Wall Street Journal.

The sample includes only proxy contests for board seats and control-oriented tender offers. The sample includes both successful and unsuccessful tender offers and successful and unsuccessful proxy contests. In a narrow perspective, a proxy contest for control may be interpreted only as one in which a rival seeks a majority membership on the board. But from a wider perspective, any board seat gained may be construed as obtaining some measure of control. From a practical standpoint, since limiting the selection of proxy contests only to proxy contests for majority control of the board would further attenuate the relatively small sample of proxy contests available, we decided to include all proxy contests for board seats in the sample. In conformity with previous research on proxy contests,(7) a proxy contest for control in this study is broadly defined as one in which the rival seeks election of board members.

The definition of a control-oriented tender offer is less precise, and varying criteria have been used in prior research (see, for example, Bradley (1980), Bradley, Desai, and Kim (1983), Bradley, Desai, and Kim (1988), and Dodd and Ruback (1977)). In this study, as in Martin and McConnell (1991), a control-oriented tender offer is one in which the bidder holds less than 50% of the target shares prior to the contest.

In the 1978-85 period, 338 control contests initially are identified, 273 tender offers and 65 proxy contests. Additional data requirements are imposed on the sample to facilitate the analysis. First, the target firm is required to be unique to the tender offer or proxy contest. This reduced the sample by 14 firms. Second, balance sheet and income statement information for the announcement year and a period of two years prior to the event are available on the COMPUSTAT Annual and Annual Research tapes. These financial variables are averaged over the announcement year and the two prior years. Third, information on ownership structure and the distribution of voting rights needs to be available from proxy statements filed with the SEC just prior to the announcement of the control contest. These three data requirements eliminate an additional 124 events; 151 tender offers and 38 proxy fights fulfill these data requirements.

Since our research focuses on the choice of hostile takeover mechanism, the sample of tender offers is further pruned. Following Morck, Schliefer, and Vishny (1988b), takeover attempts by tender offer are classified as hostile or friendly based on target firm management’s initial reaction. Initial rejection by the target’s board is evidence of hostility. Data on management’s reaction to the tender offer is collected from the Wall Street Journal Index and Predicasts F & S Index. Based on this data, 79 tender offers are classified as hostile. The analysis is limited to hostile tender offers and proxy contests because, by definition, they are both hostile mechanisms used to gain control. Friendly tender offers are not included in our sample. The dynamics of friendly tender offers may be quite different from hostile tender offers, and thus, they are excluded.

The total number of hostile control contests analyzed in this paper is 117 – 79 tender offers and 38 proxy fights. Table 1 presents the number of tender offers and proxy fights in our sample by year.(8) The data are checked to observe if potential bias is introduced due to the restrictions imposed by data availability. In the initial sample and the final sample, the number of tender offers generally increased from 1978 to 1985. The exception is in 1980 when tender activity declined relative to the previous year. In the final sample, the number of proxy contests peaks in the early 1980s, then declines, and starts to increase again in 1985. A similar pattern occurs in the initial sample of proxy contests. Thus there does not appear to be a significant sample selection bias introduced by the data requirements.

III. Ownership Structure and Firm Performance Data

In this section, ownership structure, capital structure, and firm performance data are contrasted between target firms involved in tender offers and those involved in proxy fights.

The ownership profile of the target firm may affect the rival’s takeover mechanism choice. Several variables are used to measure directly the target firm’s ownership profile. The first measure, BLOCKOUT, represents the fraction of voting rights held in concentration by persons who do not hold management positions within the company. Management-controlled firms would have smaller values on this measure. BLOCKOUT is calculated by summing all voting rights held in blocks of 5% or more (not including such voting rights held by insiders) and expressing the sum as a fraction of the total available voting rights.

The second ownership variable, DIRECTOUT, measures the voting rights of outside directors who are not firm managers. If this value is small, then the firm is more likely to be management-controlled. DIRECTOUT is computed as the percentage of voting rights owned by all directors and officers of the company minus the percentage of voting rights owned by directors who also hold a management position within the firm. DIRECTOUT includes voting rights contained in unexercised options (due to expire in 60 days) and voting rights that belong to family members and close associates of directors and officers.(9)

The number of corporate insiders that serve as directors on the board represents the third measure of ownership. The variable, INSIDER, is calculated as the ratio of the number of insiders to the total number of directors on the board. An insider is a director who also holds a management position within the firm. A large value for INSIDER would suggest a management-controlled firm.

These three ownership variables (BLOCKOUT, DIRECTOUT, and INSIDER) attempt to measure directly the extent to which a target firm can be characterized as management-controlled. With these data, one can empirically determine whether and how the target firm’s ownership structure matters in the rival’s selection of the hostile takeover method.

The target firm’s capital structure, via redistribution of shares, may influence the form of the control contest. Incumbent management can directly affect the supply of shares available for tender by making capital structure changes. By increasing the amount of debt and reducing the amount of equity, the supply of shares available for tender is reduced. If the supply of shares available for tender is greater in low leverage (or smaller leverage increase) firms, then the likelihood of a successful tender offer may be greater and hence it may be the selected method of takeover. On the other hand, highly leveraged (or larger leverage increase) firms may present themselves with fewer shares available for tender. Under this scenario, a proxy contest may be the chosen takeover mechanism. Thus, the variables used to measure the target firm’s ownership profile should capture the effects of capital structure as well.

Table 1. Number of Proxy Contests and Hostile Tender Offers by Year,



The LEVERAGE coefficient is negative; the p-value suggests the coefficient is significantly different from zero at the 0.10 level. Hence, the higher the leverage, the more likely the contest will take the form of a proxy fight.

The coefficient for adjusted return on assets (ADJROA) is positive and significantly different from zero at the 0.01 level. Hence, the more profitable the target firm, the more likely the hostile takeover will be a tender offer. The coefficient for cumulative excess return (CAR) is also positive although just marginally significant. Nonetheless, stock market performance confirms the story told by accounting returns.

The third specification of the logit model drops the annual dummy variables. The coefficients and inferences are not dramatically altered. This suggests that the results are not time-period dependent.

The estimates from the logistic regression corroborate the inferences suggested from the analysis of means in Table 2. That is, relative to proxy fights, hostile tender offers are associated with lower leverage, better firm performance, and larger outside control. Similar results are obtained using ROA figures unadjusted for the market-wide ROA in each year.(13)

The results would enhance confidence if the logit estimates could predict the form of the takeover out of sample. The out-of-sample tests are conducted using the proxy contest and tender offer data from 1985. A chi-squared goodness-of-fit test is used to assess how well the estimated logit model fits the validation sample. To assess the estimated model, the expected number of tender offer targets in the validation sample is computed by summing up the probability of a tender offer as predicted by the logit model for all firms in the validation sample. The expected number of proxy contest targets is then computed by subtracting the expected number of tender offer targets from the total number of target firms in the sample.(14)

For the estimated logit model, the value of the [[Chi].sup.2] statistic is 0.3639 in the 1985 validation sample. The value of a [[Chi].sup.2] random variable with 1 degree of freedom is 2.70 at the 0.10 significance level. The low value of the [[Chi].sup.2] test statistic indicates that the logit model performs well in predicting tender offers versus proxy fights in the out-of-sample period. In addition to predicting the proportions of proxy contests and tender offers correctly, the logit model also helps to identify specifically the firms in the validation sample more likely to face tender offers and those more likely to face proxy contests. The model estimates a low tender offer probability for proxy contest targets and a higher tender offer probability for the tender offer targets. The evidence indicates that the estimated logit model possesses good predictive power and that its predictions are especially valuable in identifying which targets are likely to face a particular form of control contest.(15)

V. Interpretations and Conclusions

This research investigates the empirical determinants of two alternative forms of hostile control contests: proxy fights and tender offers. The evidence suggests that the target’s financial performance and ownership profile influence the choice of takeover mechanism. Hostile tender offers differ from proxy contests along both dimensions.

A proxy fight is more likely to ensue in cases where target firm performance is low, as measured by return on assets and stock market returns. While inefficient management is often cited as a reason for a takeover, our findings suggest that the nature of the inefficiency influences the takeover mechanism. If publicly available accounting and market return information indicate poor performance, then the target firm’s shareholders are more easily persuaded to vote with the rival in a proxy fight because managerial inefficiency is obvious. Perhaps this explains why DeAngelo (1988), in a study of 86 proxy contests, finds that incumbent managers “exercise their accounting discretion to paint a favorable picture of their own performance to voting shareholders.” If the alleged inefficiency, however, is due to overlooked new and profitable investment opportunities, a tender offer may be more likely. In this case, direct compensation may be the only credible mechanism to convey the cost of these missed opportunities to target firm shareholders. In short, the evidence from differential firm performance suggests that managerial “sins of commission” are punishable by proxy fight, whereas “sins of omission” are punishable by tender offer.

The ownership profile of a target also influences the choice of takeover mechanism. Firms that tend to be management-controlled are more likely to experience a proxy contest than a tender offer. The reason for this may relate to Stulz’s (1988) observation that as the voting rights of management increase, the probability of a successful tender offer declines. The reason may also be related to the claim that management-controlled firms tend to misrepresent information in annual reports (see Salamon and Smith (1979)). In this case, potential rivals may tend to avoid the tender offer mechanism, because target shareholders may be compensated before the new owners receive a complete, unbiased appraisal of the firm. The agency cost perquisites as described by Jensen and Meckling (1976) may also influence the choice of takeover mechanism. In a management-controlled firm, a tender offer potentially would compensate managers for the value of their shares as well as for the value of the perquisites. Hence tender offers may be more expensive in management-controlled firms than they would be otherwise.

Tender offer targets tend to be less leveraged than targets of proxy contests. The evidence supports the argument that the lower the leverage, the greater is the supply of shares available for purchase, and hence the more likely a tender offer will be chosen over a proxy fight. This is an additional piece of evidence that suggests ownership structure matters.

No claim is made that all the relevant determinants in the choice of the hostile takeover mechanism are analyzed here. Indeed, our study cannot directly address the empirical impact of changes in the regulatory environment on the choice of the hostile takeover mechanism subsequent to 1985. However, at the very least, the evidence presented in this paper suggests that firm performance and the ownership profile of the target firm do affect the decision to pursue either a hostile tender offer or a proxy contest for control. Perhaps future theoretical models can incorporate these stylized facts and systematic relations into a unified framework taking into account the changes in the regulatory environment as well.

We are grateful to Kenneth Martin for providing us with the tender offer data. We thank Sanjai Bhagat, Jocelyn Evans, Wayne Marr, David Mayers, Harold Mulherin, Sarah Peck, Mike Spivey, Terry Warfield, participants at the 1992 annual meeting of the American Finance Association, and especially three anonymous referees for their helpful comments and suggestions on earlier drafts of this paper. Partial financial support was provided by the Financial Markets Institute at the University of Iowa. Naturally, all remaining errors belong to us.

1 For example, see Bhagat, Brickley, and Lowenstein (1987), Bradley (1980), Bradley, Desai, and Kim (1983), Bradley, Desai, and Kim (1988), DeAngelo and DeAngelo (1989), Dodd and Ruback (1977), Dodd and Warner (1983), Ikenberry and Lakonishok (1991), and Jensen and Ruback (1983).

2 James A. White, “Giant California Pension Funds Softens Approach to Influencing Corporations,” The Wall Street Journal, October 7, 1991, page 9, columns 1-2.

3 While comparing the number of schedule 14B filings with the number of schedule 14D filings in Mulherin and Poulsen (1991), it may appear that the number of proxy contests is growing relative to the number of tender offers. However, when one compares the number of actual proxy contests that materialized (Mulherin and Poulsen (1993)) with the number of schedule 14D filings, there is no distinct pattern of proxy contests increasing relative to tender offers. In fact, over that past decade, it appears that the relative proportion of tender offers to proxy contests fluctuates randomly from year to year.

4 For example, see Brickley, Lease, and Smith (1988), Demsetz (1983), Demsetz and Lehn (1985), Holderness and Sheehan (1988), Jensen (1986), Jensen and Meckling (1976), Malatesta and Walkling (1988), Mikkelson and Partch (1989), Monsen and Downs (1965), Morck, Schliefer, and Vishny (1988a), Salamon and Smith (1979), and Stulz (1988).

5 For example, see Friend and Lang (1988), Harris and Raviv (1988), Amihud, Lev, and Travlos (1990), Stulz (1988), and Stulz (1990).

6 For example, see Grossman and Hart (1980), Harris and Raviv (1988), Israel (1991, 1992), Shleifer and Vishny (1986), and Stulz (1988).

7 See DeAngelo (1988) and Dodd and Warner (1983).

8 In the initial sample, for the years 1978 through 1985, the frequency of tender offer targets is 24, 20, 12, 25, 38, 25, 49, and 80, respectively; the frequency of proxy contest targets is 1, 2, 7, 12, 15, 8, 8, and 12, respectively. Tender offer figures include both friendly and hostile targets. Proxy contest targets include all contests for board seats. Across 1978-85, the final sample as a percentage of the initial sample is approximately equal for tender offer targets and proxy contest targets. We did not observe any serious bias introduced by sample selection procedures.

9 Empirical results are not dependent on this definition. Our results do not change significantly if the voting rights of family members and close associates of directors and officers are excluded.

10 Similar inferences are obtained using the Mann-Whitney-Wilcoxon rank sum test, which does not assume normality of the distributions.

11 In general, smaller firms are more often the targets of takeover attempts (for example, see Mikkelson and Partch (1989)).

12 The authors will gladly supply these correlations upon request.

13 The authors will gladly provide these results upon request.

14 The [[Chi].sup.2] test statistic is given by

[[Chi].sup.2] = [summation of] [([O.sub.j] – [E.sub.j]).sup.2]/[E.sub.j] where j = 1 to 2


[O.sub.j] = Observed number of targets of type j in the sample.

[E.sub.j] = Expected number of targets of type j in the sample.

j = 1 for tender offer and 2 for proxy contest.

The [[Chi].sup.2] value follows a chi-squared distribution with one degree of freedom. Failure to reject the null hypothesis would furnish evidence that the model is useful in predicting the form of control contest.

15 The logit equations estimated during the 1978-84 time period are used to predict proxy and tender targets for the sample of 91 firms during 1985. Based on Palepu’s (1976) approach of using derived cut-off probabilities, the predictive accuracy of the model is found to be approximately 83%.


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Uma V. Sridharan is Assistant Professor of Finance at Clemson University, Clemson, SC. Marc R. Reinganum is Phillips Professor of Finance at University of Iowa, Iowa City, IA.

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