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J0URNAL OF FINANCIAL AND QUANTITATIVE ANALYSIS VOL. 27, NO 4, DECEMBER 1992

The Role of Asset Structure, Ownership Structure, and Takeover Defenses in Determining Acquisition Likelihood

Brent W. Ambrose and William L. Megginson*

Abstract

This paper extends the Palepu (1986) acquisition likelihood model by incorporating mea? sures of insider and institutional shareholdings, by examining the deterrent effect of various takeover defenses, and by considering the effect of varying proportions of fixed (tangible) assets in a firm's total asset structure. We find that the probability of receiving a takeover bid is positively related to tangible assets, and negatively related to firm size and to the net change in institutional holdings. Blank-check preferred stock authorizations are the only common takeover defense significantly (negatively) correlated with acquisition likelihood.

I. Introduction

Theoretical and empirical research has focused on the importance of a firm's ownership structure on its financial performance, investment policies, and compet? itive viability.1 Myers (1977), Scott (1977), Myers and Majluf (1984), and Stulz and Johnson (1985), among others, have also stressed the impact of asset structure on a firm's financial policies. Our study extends this research by examining how several variables influence the probability that a firm will receive a takeover bid, using data from 1981-1986. In addition to the financial variables employed by Palepu (1986), we examine ownership and asset structure variables such as in? sider and institutional shareholdings, the importance of tangible assets in a firm's production process, and the presence of formal takeover defenses.

* School of Business Administration, the University of Wisconsin-Milwaukee, P.O. Box 742, Mil- waukee, WI 53201, and Terry College of Business, the University of Georgia, Athens, GA 30602, respectively. The authors are grateful to Bill Beranek, David Blackwell, Mary Dehner, Mark Griffiths, Jim Kau, Jim Musumeci, Jeff Netter, Annette Poulson, Joe Sinkey, JFQA Managing Editor Jonathan KarpofT, and JFQA referee Ralph Walkling for their helpful comments and recommendations. Partial financial support for this project was provided by the University of Georgia Research Foundation, and the authors gratefully acknowledge the data collection assistance provided by Drew Winters and, especially, Erik Van Houwelingen. 1 Beginning with the seminal paper by Jensen and Meckling (1976), and later works by Fama (1980) and Fama and Jensen (1983), the literature in this field has been voluminous. Recent works include Walkling and Long (1984), Demsetz and Lehn (1985), Fama and Jensen (1985), Lang, Stulz, and Walkling (1989), and Stulz (1988).

575


576 Journal of Financial and Quantitative Analysis

Several recent studies have examined how insider shareholdings influence the probability that a firm becomes a takeover target, and that the bid ultimately suc- ceeds. Both Mikkelson and Partch (1989) and Song and Walkling (1990) show that targets have significantly lower insider shareholdings than nontargets, but that the probability of offer success is directly related to officer and director holdings, while other authors (e.g., Agrawal and Mandelker (1987) and Lewellen, Loderer, and Rosenfeld (1985)) document that insider shareholdings help overcome agency con- flicts between managers and stockholders during corporate control events. Hold- erness and Sheehan (1988) obtain similar, positive results concerning the role of majority shareholders.

In addition to insider shareholdings, we examine the effect of institutional shareholdings on the probability of becoming a target, about which prior research contains several indirect but conflicting results. Shleifer and Vishny (1986) predict that large blockholders will help monitor managers more effectively, and they also model when a takeover attempt is more likely to occur than a proxy fight or internal management shake-up. Jarrell and Poulsen (1987) show that firms that adopt the most value-reducing forms of antitakeover charter amendments (ATC As) also have lower institutional shareholdings than do other firms, while Brickley, Lease, and Smith (1988) show that institutional investors who do not have business dealings with corporate management are more likely to vote against ATCA proposals than are other shareholders. Pound (1988), on the other hand, finds that institutional investors act as management's allies in proxy contests, while Stulz, Walkling, and Song (1990) show the target firm's gain in a successful takeover is inversely related to institutional shareholdings (and directly related to insider holdings). Finally, Agrawal and Mandelker (1990) find shareholder wealth effects surrounding ATCA proposals to be positively related to institutional shareholdings, suggesting that these investors provide a valuable monitoring service for other shareholders.

We also study whether takeover defenses actually deter takeover bids. While several authors examine the wealth effects of shareholder-approved takeover de? fenses, only Pound (1987) tests whether supermajority and classified board de? fenses actually work as predicted. Unfortunately, Pound's study covers the pe? riod 1974-1984 and, thus, is unable to examine whether the poison pill defenses described by Malatesta and Walkling (1988) and Ryngaert (1988) are effective takeover deterrents, since these defenses were not generally adopted until after the Delaware Supreme Court upheld Household International's poison pill plan in November 1985.

Finally, this paper studies the influence of a firm's asset structure on the like? lihood that it will become a takeover target; in essence, testing what an acquiring firm is actually seeking to buy in a target. First, we employ a market-to-book value measure to determine whether bidding firms are primarily seeking to purchase growth options or assets in place. Second, we examine whether a mismatch between a firm's growth prospects and liquidity position increases the likelihood that it will be acquired by a bidder, which can alleviate those constraints. Finally, we test whether the fraction of a company's total assets accounted for by fixed (tangible) assets rather than intangible assets and working capital influences the probability that the firm will be acquired.


Ambrose and Megginson 577

II. Data

The data employed in this study consist of a random sample of firms from nonregulated industries that are listed on the New York Stock Exchange (NYSE) or the American Stock Exchange (ASE), and have data available on the CRSP and COMPUSTAT tapes as of January 1,1981. Our sample selection criteria are more general than the mining and manufacturing firms used by Palepu (1986), although we also delete public utilities and firms in the financial services industry since the presence of regulation affects the probability of becoming a takeover target in ways that change over time and are difficult to measure. A total of 1897 companies meets these selection criteria.

We randomly select one-fourth of the total firms (475 companies) from this population of available firms for potential inclusion in the sample. Of these 475 companies, 135 were successfully acquired (28.4 percent) and delisted from the CRSP tapes by the end of 1986. Using the Wall Street Journal Index, we identify an additional 34 firms as targets of unsuccessful takeover bids. A takeover bid is defined as an announced attempt by one firm to accumulate or acquire majority voting power (50.1 percent or more of the outstanding voting shares) over another firm. We define the date this offer is first announced as the "bid date." Our final sample includes 169 target firms, 267 nontargets, and 39 liquidated or otherwise delisted firms that are not takeover targets. We delete this last group of firms because their inclusion would artificially force us to assign these weak firms to the early quarters of our temporally matched database, thus introducing bias into the sample.

We employ a temporal matching scheme to assign unique information dates to all of our surviving sample companies. For targets, we gather relevant, publicly available information from the time period when the bidder decides to launch a takeover attempt. We therefore assign as our information date the latest quarter- end that is at least 30 days before the bid date. We then match equal fractions of nontarget firms to the same information date so that direct comparison between the two groups can be made without adjustment for any secular trends in financial or ownership structure. Except for this temporal matching algorithm, our sample selection technique is similar to that employed by Mikkelson and Partch (1989) and our basic purpose is the same?to examine how firm-specific variables impact the probability that a given firm will become the target of a takeover attempt during a given time interval, in our case, during the period January 1981 to December 1986.

Panel A of Table 1 summarizes the distribution of targets and nontargets over the sample period, and Panel B details the one-digit SIC codes represented by both groups. We compute Cochran-Mantel-Haenszel (CMH) statistics to test the null hypothesis that no association exists between a firm's one-digit SIC industry group and whether it receives a takeover bid. The CMH statistics of 1.836 for nonzero correlation and 6.836 for general association do not reject the null hypothesis of zero correlation between industry group and acquisition likelihood. Thus, no significant industry clustering of takeover targets exists in this sample.

Once each company is assigned an information date, we collect the same machine-readable financial data from the CRSP and COMPUSTAT files that Palepu


578 Joumal of Financial and Quantitative Analysis

aThese target firms were listed on the New York or American Stock Exchanges as of January 1, 1981 although they had received bids prior to 1981. bMajor Industry Groups determined by first digit of the firm's SIC code.

(1984) employs. We also compute a measure of a firm's tangible assets (property, plant, and equipment) as a fraction of its total assets. This variable may be consid? ered either a proxy for the predicted importance of asset structure in determining debt-capacity, as described by Scott (1977) and Stulz and Johnson (1985), or sim- ply a measure of whether the firm is relatively rich in real estate and production capacity.2 These financial variables are presented and defined in Table 2?

We then manually collect the institutional shareholdings data described in Table 2 from the appropriate quarterly editions ofSpectrum 3: Institutional Stock- holdings Survey. These variables allow us to measure the impact of both the absolute level of and the change in institutional shareholdings on the likelihood that a firm becomes an acquisition target.

2Empirical support for the Scott model is provided in Bradley, Jarrell, and Kim (1984), but Titman and Wessels (1988) find a collateralizeable assets variable to be an insignificant factor in determining corporate capital structures. See Ambrose (1990) for more information concerning takeover targets during this time period.

3The one variable defined and employed by Palepu that we do not compute is the industry disturbance variable (IDUMMY). Given the frequency of takeovers during our sample period, this variable would have a realization of one for virtually every industrial grouping in every time period. Further- more, examination of the target and nontarget subsamples grouped by two-digit or three-digit SIC codes yields no evidence that takeovers within an industry are concentrated in time, as would be suggested by the "industry disturbance" hypothesis.


Ambrose and M

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We next collect the officer and director (insider) shareholding data from the appropriate annual proxy statements filed by each of our sample companies. We expect that the likelihood of receiving a takeover bid is inversely related to the level of insider shareholdings for two reasons. First, managers who own large equity stakes in their firms will manage that firm more in the interest of outside share? holders than would nonshareholder insiders (see Jensen and Meckling (1976)). This should make the firm less vulnerable to takeover, since an acquirer would be less able to recoup his investment in the acquisition by improving target firm per? formance. Second, large insider shareholdings also serve to entrench target firm managers by increasing their ability to oppose outside bids (see Stulz (1988)). This makes the firm a target only for bidders with the ability to offer bid premiums large enough to overcome insider resistance.

Finally, we draw from several sources to determine whether each of our sam? ple firms had formal takeover defenses in place as of their information dates. The defenses we examine are those described in Investor Responsibility Research Cen- ter (IRRC) ((1984), (1985), and (1986)), and include poison pill security rights purchase plans as well as various shareholder-approved antitakeover charter amendments (ATCA). We are able to determine definitively if a firm has a poison pill defense in place by consulting Ryngaert (1988), since he provides a comprehen- sive listing of firms with pills in place throughout our study period. Determining whether a firm has an ATCA in place is much more challenging. We consult the three IRRC publications cited above to determine if our firms are listed and, if so, to find out which defenses they have adopted and on which date. We also consult Jarrell and Poulsen (1987), (1988) to see which of our companies intersect with their listing of firms with shark repellents in place. The final public source we con? sult is Megginson, Fischer, and Blackwell (1988), who had access to a listing of all NYSE-listed firms that issued preferred stock during the 1980-1986 period, from which they determined which firms had "blank-check" preferred stock authorized.

While the procedure described above works quite well for those of our firms that are cited in one or more of the studies, well over half of our sample firms are not examined (or at least not cited) in any study. This creates a serious problem, since we cannot tell whether these firms do or do not have defenses in place. To overcome this problem, we examine the proxy statements from 1980 through the information date for all of our sample firms. By studying the first several pages of each annual proxy statement, we are able to determine if the firm proposed a takeover defense to their shareholders. If a firm is not cited in one of the published studies and this search of the company's annual proxy statements yields no evidence of defense adoption, we record that this firm does not have an ATCA in its charter as of its information date.

While this manual data collection technique is still not a perfect test of whether a given firm does or does not have an ATCA in place, we feel that it does provide a usable data item for several reasons. By examining the voting rights of shareholders and the classes of shares entitled to vote, we can definitely determine whether a firm has a dual class capitalization (see Partch (1987) and Jarrell and Poulsen (1988)). A similar examination of directors' nominations conclusively reveals whether a firm has authorized a classified board of directors. Therefore, the only remaining uncertainty concerns whether a firm has a fair price or supermajority provision in



its charter or whether it has blank-check preferred stock authorized. Since Jarrell and Poulsen (1987) document that most of their supermajority provisions, and virtually all of their fair price provisions, were adopted during the 1980s, we feel that the remaining error in our takeover defense variable is tolerably small.

III. Univariate Comparison of Targets and Nontargets Table 3 presents the means and medians of the financial, asset, and ownership

structure variables of the target and nontarget firm subsamples. The chi-square test statistic of 28.76, which is significant at the 0.001 level, indicates that we can reject the hypothesis that the targets and nontargets are from the same distribution. We, therefore, employ the ^-statistic using unequal variances to test for differences in the sample means.

The only variables with significantly different means for targets and nontar? gets are size (SIZE), the variable proxying for tangible assets as a fraction of total assets (REALPROP), and the net percentage change in institutional shareholdings (NETCH) during the quarter before the information date. Targets are significantly smaller than nontargets and yet have a significantly greater amount of tangible assets as a fraction of total assets than do nontargets. Targets also have a signifi? cantly smaller net increase in institutional shareholdings in the quarter before the takeover bid. Our finding that targets are significantly smaller than nontargets in the 1980s (a mean of $788 million versus $1,573 million) is similar to Palepu's findings for the 1970s, and also with the size results presented in Song and Walk? ling (1990), Mikkelson and Partch (1989), and Mitchell and Lehn (1990). Our result that institutions are not large buyers before takeover attempts contradicts the commonly held view that rising institutional shareholdings increase a firm's takeover vulnerability.

The fact that only one of our three asset structure variables is significant suggests that the primary motivation of acquiring firms is neither to purchase firms rich in growth options, since the market-to-book (MTB) ratios between targets and nontargets do not differ significantly, nor is it to acquire firms with a growth/resource mismatch, since the GRDUMMY variable is not different for bidders and targets. Instead, acquirers seem to bid for tangible-asset-rich target firms, as evidenced by the significantly higher REALPROP measure for target firms.

That targets have a greater fraction of fixed assets in their total asset structure is consistent with several possible explanations. First, this could be a proxy for greater debt-capacity of target firms, based on the logic of Scott (1977) and Stulz and Johnson (1985). A bidder that acquired a firm rich in collateralizeable assets could conceivably use the target's own assets as security for debt financing of the takeover offer, thereby effectively lowering the direct cost to the acquiring firm. While this rationale is consistent with the popular view of how the typical acquisition bid is financed, its usefulness as an explanation is seriously weakened by the fact that targets already have (insignificantly) higher mean and median leverage ratios than do nontarget firms. This suggests that targets and nontargets have similar debt capacity.



TABLE 3 Mean and Median Values of the Financial and Ownership Structure Variables for the Temporally-Matched

Subsamples of Target and NonTarget Firms, with a Test for Significant Differences in Variable Mean Values

aVariables for target subsample are calculated using between 101 and 169 observations. bVanables for nontarget subsample are calculated using between 177 and 267 observations. cThe f-statistics are computed to test the null hypothesis that the mean values for the target and non? target subsamples are equal under the assumption of unequal variances. dln order to save space, only the combined takeover defense variable (ATCA) will be presented in the following tables. Listed below are the individual takeover defense variable mean values for the target and nontarget samples.

* Indicates significance at the 0.05 level. **Indicates significance at the 0 10 level.

Our finding that bidders look for asset-rich targets is also consistent with the "operating synergy" rationale for nonconglomerate mergers presented in Chapter 8 of Weston, Chung, and Hoag (1990). According to this theory, those industries where economies of scale in production are important determinants of success will witness numerous capacity-expanding mergers as firms compete to quickly achieve dominant market shares. This suggests targets are acquired primarily to increase production capacity.4

4This interpretation is strengthened by the findings reported by Ambrose, van Houwelingen, and Megginson (1991). They use this same REALPROP variable in their study of acquisition likelihood for S&P 500 firms during the period September 1984-December 1987. They find that REALPROP is significantly negatively related to acquisition likelihood. This is exactly the opposite of the result reported here, but it is consistent with the idea that firms bidding for relatively small firms, as in this



Another possible explanation for targets having a significantly greater REALPROP measure is that it is a proxy for asset-rich firms in declining industries. Declining industries represent fewer growth opportunities. An asset-rich firm with few growth opportunities would attract substantial takeover interest as a method of restructuring the firm to gain a competitive advantage relative to other firms in the industry.

Finally, the REALPROP variable may also represent the fact that fixed assets are easier to value than growth opportunities. Growth opportunities rely heavily on the human capital of current managers. Firms with significant future growth opportunities are poor takeover candidates since outside bidders do not have a comparative advantage in managing the growth options. However, the most opti? mal use of fixed assets is open to interpretation. Thus, firms with a high proportion of fixed assets represent opportunities for outside bidders with expectations and information different from management's to shift current asset utilization.

In our sample, there is no significant difference between targets and nontargets in the percentage of insider shareholdings (OFFPCT). This contrasts with the results presented in Mikkelson and Partch (1989) and Song and Walkling (1990), both of whom find target firms have lower insider shareholdings.

Table 3 also reveals no significant difference in the frequency with which targets and nontargets employ takeover defenses. While 46.5 percent of targets have some type of shareholder-approved ATC A in place on their information dates, 51.6 percent of nontargets have such defenses in place on their matching dates. Neither category of firms employs poison pills with any regularity (1.1 percent of nontargets versus 0.6 percent of targets).5

IV. Methodology and Empirical Results

We use the same logistic probability model employed by Palepu ((1986), p. 15) to examine the likelihood that a given firm will be the target of an acquisition attempt sometime during the period 1981 to 1986. The regression model specified is

(1) pdJ) = l/[l+*-^,-')], where /?(/,1) is the probability that firm i is the target of a takeover bid during period t (t = 1981-1986); x(i, t) = a vector of measured attributes for firm / at time t\ (3 = the unknown parameter vector.

The estimates of the parameters of this model yield the acquisition probabil- ities for a given firm. The vectors of measured attributes used in each regression are some subset of the list of empirical variables described in Table 2. We begin with those same variables employed in Model 2 by Palepu (thus corresponding to a

study, are seeking to expand capacity, whereas firms seeking to acquire very large (S&P 500) companies are effectively deterred by the prospect of acquiring a relatively huge increment of productive capacity. The fact that the median S&P 500 target has almost $2 billion in total assets, versus $173 million for our median target, supports the capacity-expansion interpretation of our REALPROP results. 5 Additional results indicate that targets during the 1984-1986 period were significantly larger and had a significantly greater concentration of institutional investors than did targets during 1981-1983. Also, LBO targets have significantly higher concentrations of insider ownership than do other target firms.



simple update of his best model), and end with our most extensive functional form, which incorporates the standard financial variables as well as all of our ownership structure and takeover defense variables, plus our variable measuring fixed asset utilization. Our sample of targets contains both leveraged buyouts and third-party acquisitions. We present the results for the full sample. When LBOs are excluded, the results are not affected substantially.

In the interests of brevity, we only present the final models including financial and ownership structure variables. Tables replicating the Palepu models are available from the authors upon request. None of the variables in the simple Palepu update were significant, and the overall model had negligible explanatory power and was not significant.

Table 4 presents the results of the logit regression models. Model 1 in Table 4 presents the results of adding the tangible asset and ownership structure variables to the Palepu model. Model 2 tests for the presence of any antitakeover charter amendments and/or poison pill on the likelihood of becoming an acquisition target. ATCA is a dummy variable denoting the presence of any shareholder-approved takeover defense, while PP is a dummy variable denoting the presence of a poi? son pill defense. To further test the impact of takeover defenses on acquisition probability, Model 3 breaks out the ATCA variable into variables corresponding to the individual takeover defenses in the prediction model. The defenses examined include classified boards (CB), fair price requirements (FP), voting rights requirements (VR), supermajority requirements (SM), blank-check preferred stock authorizations (BCP), and dual class share structures (DC).

Several important results are presented in Table 4. First, it is clear that only the final model (Model 3, with individually specified takeover defenses) is statis? tically significant, with a chi-square value of 33.22 (p-value = 0.016), and only it has substantial explanatory power, with a likelihood ratio index (analagous to an R2 measure) of 0.078. Nonetheless, REALPROP and NETCHG are signifi? cant at the 10-percent level or higher in all three models and no other financial, asset, or ownership structure variable (except specific defenses in Model 3) is ever significant.

The REALPROP variable is significantly positive (at the 5-percent level) in all three models, indicating (as with the univariate tests) that an increasing fraction of fixed assets in a firm's total asset structure is significantly associated with the chance that the firm becomes an acquisition target. Since the institutional variables are highly correlated, only two of these variables (NETCHG and IIPCT), along with percentage insider shareholdings (OFFPCT), are used in the model. The variables indicating the percent of shares held by institutions and insiders (IIPCT and OFFPCT) are not significant.

When a dummy variable proxying for the presence of any takeover defense (ATCA) is included in Model 2, neither the variable nor the full model is significant. However, when the defenses are detailed individually in Model 3, both voting rights (VR) and blank-check preferred stock (BCP) are significant (at the 5-percent level). The results show voting rights defenses?which are generally considered to be very weak takeover deterrents?actually increase the probability of the firm becoming a takeover target. The use of blank-check preferred stock authorizations reduces the probability of the firm becoming an acquisition target. The high level



TABLE 4 Estimated Coefficient Values and Chi-Square Statistics from Logit Acquisition Likelihood Estimations

Using the Palepu (1986) Financial Variables, Plus the Ownership Structure Variables and the REALPROP Asset Measure Described in Table 2 (Model 1), Plus Dummy Variables Indicating the Presence of Poison Pill (PP) Defenses and Other Takeover Defenses Classified as a Group (ATCA) (Model 2) and as Individual Antitakeover Amendments (Model 3)

*indicates significance at the 0.05 level. **lndicates significance at the 0.10 level aAII variables are as defined in Table 2, although AER is denominated in nominal return (rather than percent return) per day bThe expected signs of the variable coefficients are as defined in Palepu (1986), except for REALPROP, which is derived from Scott (1977) and is described in the text cThe log likelihood ratio mdex provides an indication of the model's explanatory power and is similar to the R2 statistic used in regression models. The index is defined as (1 ?log likelihood at convergence/log likelihood at zero).

of significance of the BCP coefficient (chi-square = 9.38) is somewhat puzzling since the direct importance of BCP authorizations as a takeover defense is not clear. Generally, these shares are presumed to be the building blocks of poison pill defenses, but the PP variable here is not significant.

The significantly (at the 10 percent or better) negative coefficient for NETCHG indicates that the likelihood of a firm becoming an acquisition target decreases when institutional investors increase their fractional shareholdings in the quarter before the information date, and acquisition likelihood increases when institutions slow their purchases (or sell shares they already own). Thus, it seems that it is the change in institutional shareholdings, rather than the absolute level of such holdings, that influences a firm's vulnerability to a takeover attempt.

To examine whether longer-term changes in institutional shareholdings affect takeover bid probability, we develop net change measures of institutional share? holdings for a period spanning five full quarters for 294 of our sample companies,



and net change measures for a nine-month period (three quarters) for 304 com? panies. Neither the five-quarter nor the three-quarter net change variables have significant coefficients when included in the models.

To gain a better understanding of institutional investors' actions during the takeover period, Table 5 reports the institutional shareholdings over the two-quarter period around the information date. We collected data on the institutional share? holdings at the information date (T = 0), the quarter after the information date (T = +1), as well as the net percentage change in shareholdings during the quarter preceding the information date (T = ? 1 to T = 0) and during the quarter subse? quent to the information date (T = 0 to T = +1). Panel A presents the results for all targets. Since eight target firms did not have any institutional investors, Panel B reports the results for firms with nonzero institutional shareholding. The results show that institutions hold approximately 25 percent of the total firm shares at the information date, and this fraction declines after the announcement of the takeover bid.

We also tracked the shareholdings of the top five institutional investors during this period. We calculated the holdings of the top five institutional investors as of the quarter before the information date (T = ?1). We then followed the changes in shareholdings for these investors over the period (T = ? 1 to T = +1). As reported in Table 5, the top five institutional investors account for over half of the total institutional shareholdings (approximately 14 percent of the total shares outstanding) at the information date (T = 0). The results indicate that the negative change in institutional shareholdings is being driven by the top five investors selling off their investment. This result indicates that, after the announcement of an acquisition attempt, institutional investors begin selling?presumably either to arbitragers or to the bidding firm itself.

V. Summary

In this study, we examine the influence that various financial, asset, and own? ership structure variables have on the likelihood that a firm receives a takeover bid during the period 1981-1986. In addition to the financial and asset structure variables used by Palepu (1986), we study the effect on acquisition likelihood of insider and institutional shareholdings, various shareholder-approved takeover defenses and unilaterally-adopted poison pill defenses, as well as the relative frac? tion of tangible assets in a firm's total asset structure. We also perform univariate comparisons between target and nontarget firms.

We find that the explanatory power of the Palepu logit model is much reduced during our study period. The only logit model that is significant at conventional levels, and that explains a nontrivial fraction of the total variability in takeover attempts, is the one that includes all the financial, asset, and ownership structure variables, plus dummy variables indicating the presence of individual takeover defenses?as opposed to an aggregate dummy variable indicating if any defenses are present. In this model, the presence of a voting rights defense is positively related to bid probability, while the presence of blank-check preferred stock authorizations is negatively related to the probability that a firm will be the target of a takeover attempt during the period 1981-1986. Our results also indicate that



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the existence of a poison pill defense is not associated with the probability of a takeover bid.

While the absolute levels of insider and institutional shareholdings have no significant influence on the probability of receiving a takeover bid, the net change in institutional shareholdings in the quarter before the takeover bid is significantly negatively related to bid probability, as is a variable measuring the fraction of fixed versus other assets in the firm's total asset structure. Asset size is not significant in the logit models, although univariate comparisons do reveal that targets are significantly smaller than nontarget firms.

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