Who benefits in an insider negotiated block trade?
Prior studies suggest that shareholder value is improved when new active blockholders bring special expertise to a firm (Holderness and Sheehan, 1985; Barclay and Holderness, 1991 ; Bethel, Liebeskind, and Opler, 1998; Kang and Kim, 2008; Klein and Zur, 2009; Wruck and Wu, 2009). This evidence of shareholder gain exists whether the block is newly accumulated or purchased from an existing blockholder. What appears important is that the new blockholder assumes an active role and applies special expertise in the management of the target firm. The combination of special expertise and blockholder activism leading to shared value improvements is referred to as the active-investor paradigm (Barclay and Holderness, 1991). We provide new evidence regarding this paradigm by examining a sample of insider negotiated block trades that take place from 1979 to 1999.
Our sample block trades all involve the firm's largest assembled block and have an insider on at least one side of the trade. We classify the trades as outsiders purchasing from insiders and insiders purchasing from outsiders, or other insiders, to focus more sharply on trades where value gains from new blockholder activity are likely to occur. For example, trades more closely fit the description of new expertise and managerial talent being brought to the firm when the new blockholder is an outsider. (1) In addition, since we are looking for evidence of shareholder gain associated with blockholder activism and special expertise, we focus on block trades where the firm is not taken over within the following year.
We present four sets of evidence designed to assess the existence of shareholder gains, block-holder activities that could generate gains, or anticipations of gains by the market. We start by examining abnormal stock returns around the time of the negotiated block trades. This evidence, contrary to the evidence cited above, suggests that any permanent value gains from blockholder activities are captured privately by the new blockholders, not shared with other stockholders. We find no support for the existence of permanent positive changes in share value where the firm is not taken over within one year of the block trade. Given the potential problems arising from survivorship, we complement these results with a number of tests.
We begin by examining executive turnover. Holderness and Sheehan (1985), Barclay and Holderness (1991), Bethel et al. (1998), and Kang and Kim (2008) all interpret high turnover as resulting from blockholder monitoring. In our analysis, we distinguish between turnover reported with the announcement of the block trade or due to the departure of the block seller (called block trade or contract turnover) and the remaining turnover (called postblock turnover). Since turnover can be initiated by the block seller as well as the buyer, evidence is required to interpret high turnover as predominately a monitoring or disciplinary outcome.
Managerial turnover in our sample, as in other block trade studies, is extensive, but the abnormal turnover that occurs does not largely result from monitoring activity by the new blockholders. We find no reliable evidence supporting a negative correlation between the probability of turnover and prior performance for block trade turnover. The probability of turnover is negatively correlated with prior performance only when turnover is classified as postblock and the block buyer is an outsider, which is a minor portion of the turnover we report. Thus, the disciplinary/monitoring motive is important for turnover that occurs after a new outsider blockholder is on board, but not for the significant portion of turnover that is negotiated as part of the block sale. High block trade turnover occurs primarily because the block seller is a top three executive (chief executive officer [CEO], president, or chairman of the board), not for disciplinary reasons.
Next, we examine operating changes and accounting performance around the time of the block sale to provide evidence of blockholder influence in firms' activities that could generate value improvements. Unlike Bethel et al. (1998) or Weisbach (1995), we find no evidence of important operating changes and only weak evidence of accounting profitability improvements in our sample firms following the block sale. Accounting profitability improvements occur in firms with top executive turnover when insiders buy, but this represents a small fraction of the sample. Thus, there is only minor evidence of changes in corporate activities that could generate value improvements or that could be attributed to the special expertise of a new active blockholder.
Finally, we study the pricing of the negotiated block trade announcements. We estimate cross-sectional regressions to explain the announcement abnormal returns and include variables that can support the hypothesis that the market anticipates benefits from blockholders playing an active role in management. This analysis provides little evidence that the market attaches positive stock value in anticipation of the new active blockholders' managerial talents or expertise. Variables that proxy for expected blockholder activism (turnover is part of the block sale contract; the block buyer is an outsider, an individual, or takes a management or board position), situations where such activism or special expertise should be most beneficial for outside shareholders (the firm has a low Tobin's Q or high undistributed cash flow), or the blockholder has special expertise (the blockholder is a corporate purchaser from a related industry) present no evidence of being priced in the announcements. Factors that are priced are the premium paid by the new blockholder, prior net of market stock price performance, and the log of equity capitalization. However, these factors can be unrelated to expected blockholder activity and we argue they instead suggest that the market assesses a higher probability of takeover at the block sale announcement.
Taken together, our results suggest that transfer of ownership to blockholders with special expertise do not lead to permanent value improvements. Furthermore, there are no permanent stock value improvements as executive turnover is primarily nondisciplinary and there are few operating changes or accounting profitability improvements initiated. Finally, at the block trade announcement, the market fully anticipates the nature of these control changes that the probability of a takeover has increased and that permanent benefits are forthcoming only if the firm is taken over.
The rest of the paper is organized as follows. Section I describes the data, while Section II presents the event study results. Section III contains the analysis of top executive turnover and turnover determinants. Section IV contains the analyses of operating changes and accounting profitability. Section V contains the cross-sectional analysis of the announcement abnormal returns. Finally, Section VI provides a summary and our conclusions.
I. Description of Insider Block Trade Sample
A large sample of private trading by insiders is collected from two sources: 1) the Securities and Exchange Commission (SEC) file, Ownership Reporting System--Official Summary of Security Transactions and Holdings, from 1979 to 1990, and 2) the Securities Data Corporation (SDC) Mergers and Acquisitions database, from 1991 to 1999. (2) The sample is checked against the Wall Street Journal (WSJ) and "Factiva" to identify announcement dates. This results in an initial sample of 393 negotiated block trade announcements from 1979 to 1999. Since we want to concentrate on transactions that change control, we eliminate 148 trades that are not of the firm's largest assembled block. (3) Twenty-three observations with insufficient stock return data (13) or involving private placements of new equity (6) and targeted share repurchases (4) also are eliminated, leaving a sample of 222 block trades.
We focus the majority of our analysis on firms that are not taken over within one year of the block trade to more easily observe the results of value enhancing activities of the purchasing blockholder. There are 63 events where the firm is taken over within one year, leaving 159 block trades in the main sample. The 159 announcements are made by 156 firms. Three firms make two announcements. (4) Also, 64 announcements are from firms listed on the NYSE and AMEX, and 95 are on the NASDAQ. Purchasers comprise 54 individuals and 105 nonindividuals, and sellers comprise 103 individuals and 56 nonindividuals. Nonindividuals include domestic and foreign corporations, financial institutions, and charitable and voting trusts. In one case, an acquiring company is wholly owned by one individual. We classify this block purchaser as an individual.
As previously mentioned, for some parts of our study, the sample is categorized into two groups: 1) outsiders purchasing from insiders (118) and 2) insiders purchasing from outsiders (9) or other insiders (32). Our definition of an insider includes individuals who are directors or officers of the firm and corporations having a representative on the board of directors or as an officer. The SEC definition of insider also includes nonaffiliated parties who own 10% or more of the firm's outstanding shares. We count these parties as insiders when the other side of the trade is nonaffiliated (13); otherwise, we designate them as outsiders (9). (5)
Table I summarizes the distribution of the sample by year. No serious time trend in private block trades by insiders is detected, although there is some clustering from 1985 to 1989, 1996, and 1997. Sample characteristics for the 159 block trades in the main sample are presented in Table II. The mean (median) transaction is for 30% (28%) of the total shares outstanding with a 1999 consumer price index adjusted value of $37 million ($11 million). The per share mean and median block premiums paid in this study are 17% and 13% above the market price 10 trading days before the announcement. (6) These premiums are 6% and 3% measured relative to the closing market price on the day of the block trade announcement. The mean and median total dollar premiums paid for the blocks as a fraction of equity capitalization at the closing price on the day of the block trade announcement are 2% and 1% (p-values <0.05). The premiums paid relative to the closing market prices are evidence that these transactions are either associated with the transfer of private benefits of control or that buyers, on average, overpay. (7) Finally, mean and median firm sizes are $120 million and $27 million in terms of equity capitalization (1999 dollars).
The above sample characteristics are not unlike those in Barclay and Holderness (1989, 1991), except our firms are smaller and our block sizes are larger. These differences are likely brought by the restriction that our sample includes only transactions involving the largest assembled block.8 Also, their sample period is 1978-1982, whereas ours is 1979-1999. While there is some overlap, 89% of our sample is from after 1982. Therefore, most of our sample contains new evidence from a more recent period.
II. Stock Returns around Block Trade Announcements
We use standard and long run event study methods to document abnormal stock returns around block trade announcements.
A. Standard Event Study
Daily stock returns are obtained from the Center for Research in Security Prices (CRSP) daily returns file. We regress firms' continuously compounded rates of return on the CRSP equally weighted return index to obtain market model parameter estimates. (9) The estimation period uses trading days -720 through -241 (approximately two years). Daily prediction errors are then calculated for trading days -240 through +240 and cumulative abnormal returns (CARs) are formed by summing and then averaging the daily prediction errors over various windows. The announcement date (Day 0) is the day of the first WSJ announcement of the private trade or, if the first announcement appears as a news wire story, the day following the story appearance.
Figure 1 presents CAR plots of our total sample (222 events) and two subsamples: 1) 63 events where the firm is taken over within the year following the block trade and 2) 159 events where the firm is not taken over during the year following the block trade. Note that the CAR plot for the sample of firms not taken over exhibits continual downward drift and turns negative around Day 150. This differs from Barclay and Holderness (1991), where they report "When a block trades and the firm is not fully acquired, CARs average 5.6%...." Thus, their plot levels off at about Day 40 implying that it indicates permanent gains for outside shareholders. (10) Further, they conclude that the special skills and expertise of the new blockholders are important for the incremental valuation since ownership concentration does not change and the firms are not taken over.
Table III focuses our standard event study on the insider/outsider trade classifications. The table contains mean and median CARs for various event windows, z-statistics, and the percent of the CARs that are positive for the total sample of 159 firms that remain independent and three insider-category subsamples. The z-statistics are calculated using standardized prediction errors and the percent positive is tested using the Wilcoxon signed-rank test. The total sample average abnormal return for the two-day announcement period is a significant 5.50% (z-value = 11.81). About 67% of the announcement period abnormal returns are positive and the Wilcoxon signed-rank test is significant at the 1% level. The CARs that include the 10 and 20 days immediately preceding the announcement (11 - and 21-day windows) are 10.53% (z-value = 10.31) and 11.56% (z-value = 8.02), respectively. This suggests a significant information leakage prior to the WSJ announcement. The CAR for the 41-day window, 11.76% (z-value = 6.00), is not much different from that of the 21-day window.
[FIGURE 1 OMITTED]
The pretrade period (Days -240 through -41), which is not tabulated, indicates a significant abnormal stock price performance of-9.94% (z-value = 5.72). The posttrade period (Days 1-240) reports a significant negative CAR of-20.74%. (11) This negative CAR is large enough to completely offset the wealth gain experienced during the announcement period. When abnormal returns are calculated over Days -40 through 240, we find no evidence of positive abnormal performance. The percent positive is less than 50%, but insignificant and the mean CAR is significantly negative. (12,13) Subsamples yield similar abnormal return patterns. When insiders sell shares to outsiders and when insiders trade with other insiders, the CARs are similar to those of the full sample. There is some evidence that the pattern is different when insiders buy shares from outsiders. No positive abnormal returns are found in any event window, but the sample size is small.
Barclay and Holderness (1991) report their sample firms tend to be marginal performers in poorly performing industries. Our sample firms, however, are poor performers relative to their industries and relative to the market. (14) Since our sample of 159 may not have the typical negotiated block trade mix of good and bad performers, we split the total sample into two halves based on net of market prior performance and repeat the calculations. These results for either the good or bad performing subsample are indistinguishable from the results reported for the whole sample. We also find results that are indistinguishable when we split the overall sample period into two subperiods, 1979-1989 (84 events) and 1990-1999 (75 events), and when we examine separately the NASDAQ firms (95 events) and the NYSE and AMEX listed firms (64 events).
To examine whether our results are dependent upon limiting our sample to trades of the largest assembled block, we calculate CARs for trades of blocks that are not the largest. Of these 148 trades, 98 are not taken over during the following 12 months and meet the same sample inclusion criteria as our sample of "largest blocks." The mean and median CARs for this sample are 5.31% and 3.15% (both insignificant) over Days -40 through 240. Finally, we replicate our analysis calculating CARs using net of market returns to assess the sensitivity of our results to an alternate method. These results are qualitatively the same as the ones we present. Thus, we find no evidence of any remaining positive stock price performance one year after the negotiated block trades using standard event study methods.
Our tests, and also those of Barclay and Holderness (1991), suffer from a survival bias. Our sample of 159 contains no firms that have been taken over within the first year after the block trade announcement. The returns on these firms are compared with the returns on the equally weighted CRSP index that contains the stock of some firms that are acquired. Since some of the firms in the index are acquired, and this usually occurs with a substantial premium, our CAR estimates are biased down. We control for this problem in the matching procedure of one of our long run event study methods, yet the problem can still remain.
B. Long Run Stock Performance
To aid in confirming our finding of no permanent positive stock price performance around block trade announcements, we provide results using long run event study methods. We employ two methods and we refer to them as the event-time and calendar-time methods. Both methods compute performance measures over 14- and 38-month windows. The 14-month window closely matches the Day -40 to 240 window used in our standard event study. The 38-month window extends the 14-month window two more years. Monthly stock returns are obtained from the CRSP monthly returns file.
1. Event-Time Method
The event-time method closely follows Barber and Lyon (1997). For each sample firm, we find a matching firm based on the closest market capitalization within the same book-to-market quintile for the year-end prior to the block trade announcement. The matching sample excludes firms taken over within one year of the sample firm's block trade announcement. (15) Buy-and-hold abnormal returns (BHARs) are calculated as the difference between the buy-and-hold return (BHR) of the sample firm and the buy-and-hold return of the matching firm over the same period:
[BHAR.sub.i] = [BHR.sub.i] - [BHR.sub.mat]. (1)
Buy-and-hold returns are computed by compounding returns from the month immediately prior to the block trade announcement month through one year (and three years) following the announcement month, unless the sample or matching firm delists earlier. (16) The mean buy-and-hold abnormal return (ABHAR) is computed as:
ABHAR = (1/N) [N.summation over (i=1)][BHAR.sub.i], (2)
where N is the number of firms.
To assess the statistical significance of mean abnormal returns, we employ the bootstrapping procedure suggested in Kothari and Warner (1997) and used by Hertzel et al. (2002). The bootstrapped p-value is the percentile of the sample firm mean return relative to 1,000 matching firm mean returns from random portfolios that are matched by quintiles of market capitalization and book-to-market ratio. (17)
2. Calendar-Time Method
The calendar-time method measures long run performance as in Fama (1998). For each calendar month, we form an equally weighted portfolio of the stocks of firms that are in the block trade announcement window (e.g., Month -1 to +12 relative to the announcement for the 14-month window). The time series of the monthly portfolio returns net of the risk-free return, [R.sub.pt] - [R.sub.ft], is regressed on the three Fama and French (1993) factors over the sample period:
[R.sub.pt] - [R.sub.ft] = [alpha] + [[beta].sub.m]([R.sub.mt] - [R.sub.ft]) + [[beta].sub.s]SMB + [[beta].sub.h]HML + [[epsilon].sub.t], (3)
where [R.sub.ft] is the Treasury bill rate, [R.sub.m] - [R.sub.f] is the excess return on the value-weighted CRSP market portfolio (the market factor), small minus big (SMB) is the size factor, and high minus low (HML) is the book-to-market factor. (18) The intercept term, [alpha], estimates the abnormal return per month, and the implied abnormal returns over the holding periods are computed as [(1 + [alpha]).sup.n] - 1, where n = 14 or 38 for the 14- or 38-month window, respectively. We require a minimum of five observations to calculate calendar month returns. (19)
Table IV contains long run stock returns for the 14- and 38-month windows. Panel A reports that the mean buy-and-hold abnormal return for the 14-month window is an insignificant -2.06% (bootstrapped p-value = 0.636). The median abnormal return is 0.03%, with a p-value of 0.971 from a Wilcoxon signed-rank test. Our mean estimate is larger than the average CAR of-8.98% we report earlier for the Day -40 through 240 window, but still not positive. For the 38-month window, the mean abnormal return is weakly insignificant at-21.64% (bootstrapped p-value = 0.088) with a significantly negative median of-23.00% (p-value = 0.030).
Calendar-time abnormal returns can be found in Panel B of Table IV. For the 14-month window, the performance measure, [alpha], indicates an insignificant average monthly abnormal return of -0.32% (p-value = 0.482). This equates to an implied abnormal return over the 14-month period of-4.37%. For the 38-month window, the implied abnormal return is an insignificant -17.63% (p-value = 0.109). The calendar-time results are not much different from the event-time results.
We do two robustness checks for long run performance. First, we split time into two periods (1979-1989 and 1990-1999) and replicate Table IV for each subperiod. In either subperiod, there is no evidence of positive performance across either the 14- or 38-month windows. There is, as in Table IV, weak evidence of negative performance over the 38-month window, predominately in the earlier subperiod. We also replicate Table IV for the 118 insider negotiated block trades where insiders sell to outsiders. These tests are not qualitatively different from those in Table IV as they provide no evidence of permanent positive value gains for stockholders.
Thus, our rate of return results contrast with those of the extant literature regarding the control aspects of block trades. They especially contrast with Barclay and Holderness (1991) who find positive gains (average = 5.6%) still remain one year subsequent to the announcement for negotiated block trades that were not acquired within a year. Our rate of return evidence is more similar to that of Bradley, Desai, and Kim (1983) or DeAngelo and DeAngelo (1989), who analyze the postfailure price behavior of targets of unsuccessful tender offers and the value gains attributable to proxy fights, respectively. Value gains are fully dissipated in the year following failed takeover attempts or they are fully attributable to proxy contests that lead to the sale of the target. We obtain similar results for the negotiated block trades that we examine. If there is no acquisition, the announcement gain is fully dissipated in the year following the announcement.
Our rate of return evidence, as previously discussed, is subject to survivorship bias and must be interpreted with caution. The event-time method we use for computing long run stock performance controls for survivorship in the way it selects matching firms. Yet, this adjustment can be incomplete. There may be other survivorship problems peculiar to our sample selection that we are not controlling for. We now proceed to validate our interpretation of the rate of return evidence by examining for blockholder activities that could generate gains.
III. Executive Turnover Following Block Trades
Holderness and Sheehan (1985), Barclay and Holderness (1991), Bethel et al. (1998), and Kang and Kim (2008) all demonstrate high managerial turnover in the years following block trade announcements. This high turnover is interpreted as evidence that the new blockholders are monitoring and taking an active part in firm management. This activism, along with the new blockholders' hypothesized superior expertise, results in the permanent shareholder gains evidenced in their studies. In this section, we investigate turnover associated with the negotiated block trades of our sample.
A. Executive Turnover: Block Trade versus Postblock
We obtain our initial data for the analysis of executive turnover from the Standard & Poor's Register of Corporations, Officers and Directors (the Register). We then examine the WSJ, "Factiva," and proxy statements to verify the turnover (for correctness and completeness) and obtain the dates of the management changes.
1. Block Trade Turnover
We designate turnover as part of the block sale contract (block trade turnover) if the departing executive is the block seller or if the turnover is included in the announcement of the block trade. Otherwise, we designate the turnover as postblock. We conjecture that abnormal postblock turnover is more cleanly attributed to the monitoring efforts of the new blockholder since it is not part of the block contract. As such, it is less likely to reflect the normal succession demands of the block seller. This is, of course, arguable. For example, some of the postblock turnover we identify occurs in firms with block trade turnover. This may be due to the departure of the block seller (a mentor), rather than being a disciplinary outcome.
We draw a comparison turnover sample from the CRSP file of firms matched by announcement date, equity capitalization, and four-digit standard industrial classification (SIC) code (three-digit matching is used if we cannot match on four). (20) We do this because relying on comparisons with other turnover studies (as in Barclay and Holderness, 1991) or with turnover from an earlier period (as in Bethel et al., 1998) can be problematic. For instance, the median firm in our study has an equity capitalization of only $27 million, and most turnover studies focus on larger firms. Also, we expect that turnover can be time and industry dependent, and our comparison sample controls for these problems. However, we also benchmark with turnover from other studies and from an earlier period to allow for comparisons.
Table V contains our evidence on top executive turnover. We assign the turnover to Year 1, 2, or 3 by comparing the date of the management change with the block sale announcement date that starts at Year 1. The table contains the total turnover percentage for each year (in parentheses) and the number of executive changes that are classified as a block trade or postblock in each of the three major executive positions. (The reader should keep in mind that these three positions are not always filled by different individuals.) Additionally, for each position, we present the number of firms ([N.sub.p], where P = CEO, President, or Chair) that have survived to the end of the designated year and also list someone as holding that position. For example, 134 firms survive to the end of the first year and indicate they have a position titled CEO. In these 134 firms, the CEO position turned over 68 times in the first year after the block trade. We designate 48 of the turnovers as part of the block sale contract (i.e., block trade). We also report the number of times there is turnover in at least one of the three positions. The letter N (with no subscript) represents the total number of firms that survive to the end of the designated year relative to the block trade announcement. Note also that N is not 159 for the first year as seven firms in the sample went bankrupt within 12 months of the block trade announcement. (21)
3. Total Turnover
There is a high level of turnover in all three top executive positions during the first year after the block sale announcement. A total of 104 of 152 firms (68%) that survive the first year have turnover in at least one of the positions. This number of firms with turnover is highly significant. The control sample indicates that only 26 of 153 firms (17%) have turnover in these same positions over the same time period (p-value for the difference <0.001). (22) During the three years prior to the block trades, the average annual turnover in these positions is 21% (19% the year prior). Looking at other block trade studies, Bethel et al. (1998) find 22.3% CEO turnover during the two years following purchases by activist blockholders (compared with 78 of 152 or 51% from our study), while Barclay and Holderness (1991) note 33% turnover at the top position. Martin and McConnell (1991) report a 42% turnover rate for top executives beginning with the announcement of a takeover and ending 12 months after its successful resolution. Kaplan and Minton (2011) find 14.9% annual CEO turnover for Fortune 500 companies. Warner, Watts, and Wruck (1988) report 18.3% turnover in the top three executive positions for a random sample of NYSE and AMEX firms. This is similar to what we observe for firms in our control sample. We conclude from these comparisons that insider negotiated block trades involving the largest assembled block are major control change events.
4. Block Trade versus Postblock Turnover
The majority of turnover in Year 1 is part of the sale contract. A total of 75 of the 104 firms with turnover in at least one of the top three positions have management changes that either involve the block seller or are announced at the same time as the block sale. (23) Consequently, for these firms, the process resulting in top executive turnover begins before the block trade. Block trade turnover also is clearly statistically significant. Further, the block seller's departure is important. The turnover of 42 CEOs, 29 presidents, and 58 chairmen involve the departing blockholder.
The postblock turnover (occurring in 29 firms in Year 1) is less significant. Eighteen of these 29 turnovers occur in firms with no block trade turnover. When compared with the control sample, this quantity of turnover is not significant (p-value = 0.25). (24) The remaining 11 turnovers, occurring in firms with block trade turnover, include three cases that appear special to block trades. In these three cases, the block buyer initially replaces the block seller in one or more executive positions, and is then replaced in some of these positions by someone else within the year. Since the block buyer maintains possession of the block, these are not disciplinary turnovers that result from blockholder monitoring. The initial replacement by the block buyer is likely part of the transition process rather than a planned permanent solution. The eight remaining postblock turnovers in Year 1 occurring in firms with block trade turnover could nudge the total postblock turnover to significance and may be the result of monitoring, but they could also be related to the departure of the block seller in other ways. As previously mentioned, the block seller may be the executive's mentor.
Thus, we find only weak turnover evidence to potentially support the existence of blockholder monitoring activities occurring after the block purchase. However, high block trade turnover may also be attributed to blockholder monitoring; that is, monitoring that occurs prior to the block trade. There is some evidence consistent with this hypothesis. For example, the WSJ announcement of the sale of the SAI Group Inc. block indicates that the holder of the major block agreed to resign as chairman and CEO of the company "at the request of a major shareholder," who also bought the block. Yet, this kind of evidence is thin, and, more importantly, a number of these block trade departures are likely due to retirement. The average age of 80 top executives noted as block trade departures (78 of whom are block sellers) is 58. Since the median is 61, roughly half of these departing executives are close to retirement age (40, or 50%, are over 60). The average age of 69 top executive postbtock departures is significantly younger at 54 (with only 12, or 17%, over 60). (25) This result is comparable to findings of other studies in that voluntary turnover departing executives are significantly older than those in forced turnover (Denis and Denis, 1995). Thus, there are plausible alternative explanations to the inference that high block trade turnover is due to the monitoring activities of the new blockholder.
B. The Probability of Turnover
In this section, we examine multinomial logit regression estimates that provide evidence of blockholder monitoring, and allow us to distinguish between block trade and postblock turnover. Our regressions assess the determinants of the probability that a company has turnover, where its turnover is classified as either: l) postblock, 2) block trade, or 3) both postblock and block trade. Prior stock market performance and selected block buyer and seller characteristics are hypothesized to be determinants of the three turnover classifications.
1. Prior Stock Market Performance
Prior stock market performance should be a factor if the disciplinary motive is important. We measure stock market performance with the net of market stock return calculated over the year prior to the block trade (Event Days -280 through -41). (26) The market is measured with the CRSP equal-weighted return index.
2. Buyer and Seller Characteristics
We previously argued that negotiated block trades more closely fit the idea of new expertise being brought to the firm when an outsider buys it. Expertise is important for high quality monitoring. Similarly, a new blockholder taking a board position may be an indicator of monitoring since that is what board members are supposed to do (Kang and Kim, 2008). Finally, the importance of individuals as active blockholders has been emphasized by Holderness and Sheehan (1985), Denis and Serrano (1996), and Bethel et el. (1998), among others. We include dummy variables to represent these three factors, and we label them: 1) outsider buys, 2) new blockholder is an individual, and 3) board seat for new blockholder.
We further include an indicator variable equal to one if the block seller is a top three executive (CEO, president, or chairman of the board). We include seller is a top three executive to assist with the specification by controlling for possible seller-initiated turnover motivations unaccounted for by other variables.
3. Interaction Variables
Our arguments suggest a stronger negative correlation between prior performance and the probability of top executive turnover when the new blockholder is an outsider, takes a board seat, or is an individual. We include prior performance interaction variables to verify the monitoring (disciplinary) interpretation when the new blockholder is an outsider, takes a board seat, or is an individual.
Table VI contains the multinomial logit regression coefficient estimates for assessing the probability of turnover conditional on its classification. There are 34 firms with top executive turnover classified as postblock, 52 classified as block trade, 27 classified as both block trade and postblock, and 46 with no turnover (the base outcome).
The Panel A regression in Table VI indicates the probability of executive turnover is higher when the new blockholder is an individual or takes a board seat for either of our three turnover classifications. (27) There is only weak evidence for the significance of the block buyer being an outsider (the evidence is stronger when the turnover is postblock or postblock and block trade). More importantly, seller is a top three executive is significantly positive for the two turnover classifications that include block trade turnover, but not significant as a determinant of postblock turnover. This is not a marginal result either statistically or economically. The relative probability of the dependent variable being block trade turnover to the base outcome of no turnover is 211 for a one unit change in seller is a top three executive (i.e., going from zero to one). The relative probability for this variable for the postblock classification is indistinguishable from one. Another way to look at this is with the pseudo [R.sup.2]. Including seller is a top three executive yields a pseudo [R.sup.2] of 0.42, as reported in Table VI, while excluding it yields only 0.13 (not tabulated). The percentage difference in the pseudo [R.sup.2] between including and excluding the variable is 223%.
It is important to note that there is only very weak evidence, for any turnover classification, of a negative association between the probability of turnover and prior net of market stock performance (p-values are all > 0.18). Denis and Serrano (1996), Martin and McConnell (1991), Warner et al. (1988), Weisbach (1988), Huson, Malatesta, and Parrino (2004), and Kang and Kim (2008) all find evidence supporting a negative relationship between turnover and prior stock performance. These findings suggest the disciplinary motive overall is less important for turnover associated with insider negotiated block trades. The primary determinant for turnover classified as block trade is that the block seller is a top three executive.
Panel B of Table VI adds the interaction variable between outsider buys and prior performance (outsider buys*prior performance). The coefficient on this variable is significantly negative, but only for the postblock turnover classification. Further, the sum of this coefficient with the coefficient on prior stock performance, -1.94 (-3.08 + 1.14), is also significantly negative (Wald test p-value = 0.030).
In untabulated regressions, we include the other interaction variables with prior performance (board seat for new blockholder and new blockholder is an individual) in regressions similar to those in Table VI. These coefficient estimates are never significant, whether the variables are included in the regression coincident with each other or individually. Thus, the estimated correlation between prior performance and the probability of top executive turnover supports the monitoring hypothesis when the buyer of the block is an outsider, but only for the postblock turnover classification.
This evidence supports our conjecture that abnormal postblock turnover is more cleanly attributed to the monitoring efforts of the new blockholder. We find no reliable evidence to support the disciplinary motive for block trade turnover, but we do for postblock turnover when an outsider buys the block. The evidence from the postblock turnover category is most applicable for the active-investor paradigm. However, the result represents a relatively minor portion of the sample. The lack of monitoring evidence associated with block trade turnover is consistent with the evidence we find for shareholder permanent value gains. The block trade turnover events appear to be predominately initiated by the seller of the block (normal succession), and not the result of a value increasing monitoring effort by the new blockholder.
IV. Operating Changes and Profitability
In this section, we examine operating changes and profitability measures to further search for evidence of new blockholder special expertise and activism. If disciplinary reasons motivate the executive changes and the purpose of the changes is to institute corrective measures, we should see evidence of operating changes and profitability increases following the block sales if the new blockholders are more active or have more expertise than the old blockholders.
A. Operating Changes
Bethel et al. (1998) provide evidence to suggest that activist block purchasers target poorly performing diversified firms and their purchases "are followed by increases in divestitures and share repurchases and by declines in mergers and acquisitions." Weisbach (1995) provides evidence linking management turnover and divestitures. We examine different sources to find evidence of operational changes subsequent to the block sale for our sample of firms that are not taken over within one year of the insider negotiated block trades.
We examine the WSJ Index and articles in the WSJ for evidence of changes in operations during the four-year period surrounding the block trade. This four-year window requirement reduces our sample size from 159 to 132 firms. We count instances of divestitures and spinoffs, mergers and acquisitions, share repurchases, and layoffs and plant closings, among others. (28) This evidence is provided in Table VII where results are presented for the full sample by top executive turnover versus no top executive turnover, and by whether the block purchaser is an outsider or an insider for the top executive turnover firms.
We find no reliable evidence of shifts in operating policies around the time of the block trades. None of the before versus after comparisons is significant. For example, there is a slight increase in the number of divestitures or spinoffs in the two years following the negotiated block trades for firms with management turnover (from 9 to 15), but the p-value on the test of differences is only 0.20. (29) We also find no decline in the frequency of mergers and acquisitions. The only comparison of any statistical significance in the table indicates that the frequency of mergers and acquisitions during the two years prior is greater for firms without turnover than those with turnover. However, this tells us nothing about changes in operations. We also examine this data partitioned by whether the block purchaser is an outsider or not and with (reported in Table VII) and without turnover, with no additional illumination.
Since our firms are small, and perhaps not so newsworthy, we also examine the Standard & Poor's Register of Corporations, Directors, and Officers to obtain listings of the firms' reported SIC codes for evidence regarding firm divestitures. We compare the number of four-digit (and two-digit) SIC codes between the year prior to and the second year following the block sale. We do not tabulate these results, but we find only very weak evidence of changes in the number of reported SIC codes (either two- or four-digit) for firms with or without top executive turnover or whether the block buyer is an insider or an outsider. The firms in our sample are not widely diversified using the SIC code measures. The mean and median number of four-digit SIC codes for the sample are 2.2 and 2 the year prior to the block trade, respectively.
Thus, the operating change evidence we examine provides little support for the active-investor paradigm. This lack of operating change evidence contrasts with that reported by Bethel et al. (1998) and Weisbach (1995). This may be because the firms in our sample are smaller and less visible, or because the kinds of changes being initiated by the new blockholder are less visible and more difficult to document. Yet, we find no reliable evidence of operating changes.
Table VIII contains median industry-adjusted return on assets (ROA) and changes in industry-adjusted ROA. We present the median results since they appear less noisy than the mean results. Means are more likely affected by outliers that can be a problem using accounting data (Foster, 1986). Inferences are qualitatively similar in the mean results. Data is collected primarily from the Standard & Poor's Compustat files. We augment the Compustat files with hand-collected data from other sources that include Moody's, 10-Ks, and annual reports. ROA is defined as earnings before interest, taxes, depreciation, and amortization divided by total assets. Industry-adjusted ROA are net of the industry median. Firms' two-digit SIC codes are used to define industries. Year 0 in the table is the fiscal year in which the block trade took place. ROA's are calculated starting in Year 3 through the third year following the year of the block trade. Changes in ROA are calculated cumulatively starting with year 0.
First, we note that the sample sizes in the no top executive turnover and top executive turnover insider buys columns are smaller than the other categories, so a lack of power for these subsamples could potentially contribute to the inability to draw strong conclusions. We also note that this evidence suffers from survivorship bias (to an unknown extent) contributing to the inability to draw strong conclusions where the change evidence is positive. The sample attrition rates are 23% and 19% over Years 0 to 3 for the outsider and insider buy top executive turnover firms, respectively.
The results in Table VIII indicate that the top executive turnover firms generally perform significantly worse than (and the no top executive turnover firms are indistinguishable from) their industries. This holds for Years -1 through 3, although the Wilcoxon test only indicates that the performance is different for Years -1 through 2 (p-values < 0.05). The lowest performance for any year for the top executive turnover firms is Year 0, where the point estimate is -7.7% (p-value = 0.01). Further, there are no significant differences in performance between top executive turnover firms based on whether the new blockholder is an outsider or an insider, except in Year 3.
The industry-adjusted ROA changes in the bottom of Table VIII present weak evidence of performance improvement for the total sample over Years 0 to 3 (p-value = 0.108). This is primarily driven by the top executive turnover firms where insiders buy. In this subsample, profitability improves significantly over Years 0 to 2 and Years 0 to 3, consistent with the active-investor paradigm. However, the evidence represents only a small fraction of the sample.
Thus, the accounting profitability evidence indicates turnover firms are performing worse than their industries, and significantly worse than no turnover firms that are performing like their industries. ROA performance is not distinguished in any way in top executive turnover firms where outsiders are the block purchasers. This evidence provides support for the disciplinary motive for turnover in the sense that on an industry-adjusted basis, turnover firms perform worse than no turnover firms. There is only weak evidence in support of the active-investor paradigm as we find only marginal improvements in profitability subsequent to the block trade, and no evidence where outsiders buy.
V. The Determinants of Negotiated Block Sale Announcement Returns
Our event study examination of stock returns provides no evidence of permanent value improvements for outside shareholders. Initial gains around the announcements appear fully dissipated in the year following the block trade. Perhaps, at the block trade announcement, gains from blockholder activity and special expertise are initially anticipated by shareholders, but due to estimation problems or chance, they are not detected in our event study. In this section, we examine announcement abnormal returns with multivariate regressions to see if shareholders anticipate gains from blockholder activities or special expertise.
A. Explanatory Variables
Our explanatory variables measure blockholder activity and the potential for benefits that could be generated by blockholder activity or special expertise. These variables indicate where the market should recognize potential gains if the active-investor paradigm is important for the control changes associated with insider negotiated block trades.
1. Blockholder Activity
Arguably, active blockholders are those who take top executive or board positions, are individuals, or are outsiders. Therefore, we use five dummy variables to represent blockholder activity. They indicate: 1) block trade turnover, 2) whether the new blockholder is an individual, 3) an outsider, 4) takes a board seat, or 5) takes a management position.
The active-investor paradigm implies a positive association for these variables. If a new blockholder/manager typically brings specialized talent or is better able to cope with relevant problems, then the announced departure of the old blockholder/manager (or their representative) should be good news resulting in a higher announcement return. Alternatively, if perquisite consumption or special ownership benefits are more likely to accrue for the new blockholders who control management positions, serve on the board, are individuals, or are outsiders, we may observe the opposite. (30) Note that these hypotheses are not mutually exclusive.
2. Potential for Benefits
There are several proxies available for measuring the potential for benefits that might accrue to shareholders from a control change. We use the block premium paid per share (relative to the preannouncement price), prior stock price performance (net of market), a low Tobin's q indicator variable, undistributed cash flow, a related business indicator variable, the fraction of shares purchased in the block, and firm size as proxies for the potential for benefits.
The block buyer should pay a premium if there is competition for the block and obtainable benefits. The size of the premium, measured as the ratio of the block price per share to the closing price on Day -10 (minus 1.0) is an assessment of the size of the benefits. Net of market prior performance can indicate the size of the benefits if prior (poor) performance is a result of reversible operating problems. We also estimate Tobin's Q for our sample firms to proxy for these kinds of operating problems. Brav et al. (2008) find that activist hedge funds target low-Q firms more often. Our regressions use a dummy variable equal to one if the estimated Q ratio is less than one. (31)
There may also be improvements in shareholder value if new active blockholders enforce more efficient utilization of free cash flow (Jensen, 1986). Brav et al. (2008) and Klein and Zur (2009) report that cash payouts increase and cash balances decrease after firms are targeted by activist blockholders. We use undistributed cash flow as a proxy for free cash flow. We define undistributed cash flow as in Lehn and Poulsen (1989), and normalize it with the book value of total assets. (32)
Corporations in related lines of business can provide synergies that enhance shareholder value. Allen and Phillips (2000) note that announcement stock returns are higher when block purchasers have product market relationships with the target firms. Therefore, if the block purchaser is a corporation in a related line of business, we set a dummy variable equal to one. (33)
We conjecture that blockholders are more effective as active investors (thus generating more benefits) when the fraction of shares purchased in the block is large and firm size, as measured by the log of equity capitalization, is small. Larger blocks provide more alignment incentive for the new blockholder and smaller firms should be less bureaucratic and operating problems more easily resolved.
Our final benefit measuring variable is the interaction of prior performance and the outsider buys indicator variable. Our work demonstrates an association between the probability of top executive turnover and prior performance when an outsider buys the block. This suggests that we should find a stronger correlation between announcement abnormal returns and prior performance when the new blockholder is an outsider.
3. Private Benefits
The variables we use for measuring the potential for outside shareholder benefits can also be indicators of (or sources for) the extraction of private ownership benefits. For example, a high premium paid by the new blockholder could be for anticipated private benefits associated with block ownership. Tobin's Q may be low as the existing blockholder is extracting a share of the firm's cash flow privately, and not because of poor operating performance. Undistributed cash flow can also measure the size of the potential private benefits available for the new blockholder. Additionally, private benefits for a block purchasing corporation may be larger if the firms are in related lines of business. There may be more potential for below market transfer pricing arrangements. Thus, these variables may be assessing the potential for private benefits of control. If the new blockholders are more efficient at extracting private benefits than the old blockholders, then the predicted associations in our regressions may be diminished or reversed.
4. Takeover Probability Revision
An alternate hypothesis, that may explain positive announcement abnormal returns, is that they represent the valuation effects of the market's reassessments of takeover probabilities. Recall that 28% of the block trades in our initial sample of 222 are closely associated in time with takeovers. A revision in the probability of takeover can be captured by at least some of the variables in our regressions. For example, Palepu (1986) finds that prior performance is negatively associated with the probability of a takeover. Lang, Stulz, and Walkling (1989) argue that typical targets have Tobin's Q ratios below one. Also, the block price (or the premium) provides an estimate of the bid price shareholders can expect if a takeover follows the block trade.
B. Announcement Abnormal Return Results
If the active-investor paradigm is dominant, announcement abnormal returns should associate predictably with variables that proxy for blockholder activity and the potential for benefits. Table IX contains regression results that examine the announcement abnormal returns. Abnormal returns are estimated over the interval from Day -10 through Day 0 to capture the observed preannouncement drift.
The table finds that variables indicating blockholder activity (block trade turnover, new block-holder is an individual, outsider buys, board seat for new blockholder, and management position for new blockholder) provide no evidence of being positively associated with the announcement abnormal returns. The regressions indicate only three significant variables: 1) the block trade premium, 2) the firm's prior year net of market stock price performance, and 3) the log of equity capitalization. These variables are significant and stable in the various specifications we estimate. (34) The signs on the three significant coefficient estimates are consistent with the active-blockholder interpretation. They are also consistent with an alternative hypothesis that the block trade induces a revision in the probability of a takeover.
To further investigate this alternative hypothesis, we estimate another regression (untabulated) explaining announcement abnormal returns. It includes, as additional observations, 59 events that were originally excluded because the firm was taken over within one year of the block trade. (35) We estimate this regression with block trade premium, prior performance, log of equity capitalization, and slope and intercept dummy variables designating the added observations. The estimated correlations between announcement abnormal returns and prior performance, block trade premiums, or log of equity capitalization are undifferentiated in this regression between firms that are taken over and those that are not. The slope and intercept dummy variables are all insignificantly different from zero (p-values > 0.37), and the estimated correlations are like those we report in Table IX.
Thus, our analysis of the determinants of announcement abnormal returns provides no evidence of associations supporting the importance of blockholder activities, and the correlations that we find (with block trade premium, prior performance, and log of equity capitalization) are like those from a comparable sample where the firm is taken over within one year of the block trade. We interpret this evidence as supporting the revised probability of takeover hypothesis, which is consistent with the nonpositive evidence we find supporting permanent value gains for shareholders.
VI. Summary and Conclusions
In this paper, we examine stock performance, top executive turnover, operating and profitability changes, and the pricing determinants associated with insider negotiated block trade announcements where the firm is not taken over within one year of the block trade. The trades all involve the firms' largest assembled block and are drawn from 1979 to 1999. We examine this sample to investigate the active-investor paradigm where new blockholders with special expertise take an active role in management and create value for outside shareholders.
If managerial activities by the new blockholder provide incremental shareholder value, we should find corroborating evidence. However, overall, we find no reliable evidence of associated permanent stock price increases, operating changes, or improved net of industry accounting profitability. We find some evidence supporting improved net of industry accounting profitability where the block is purchased by an insider and there is top executive turnover, but the category represents only a small portion of the sample.
We also find little evidence from our analysis of the determinants of announcement abnormal returns that shareholders anticipate receiving any benefits from blockholder activities. Our results can be consistently interpreted as suggesting the initial gains in shareholder value at the block trade announcements are in anticipation of takeovers, not improvements in profitability. When a takeover is not forthcoming, the gain disappears.
We do find substantial top executive turnover associated with the negotiated block trades, which could naively be interpreted as evidence of new blockholder monitoring. The quantity of this turnover is significant. A total of 68% of sample firms have turnover in at least one of the top three executive positions (CEO, President, or Chairman) during the first year following the block trade announcement. Our analysis highlights turnover that is part of the block trade contract since a substantial portion of the turnover (72%) is either announced with the block trade or the departing executive is the block seller. The age distribution of the departing executives and the lack of a reliable association between the probability of turnover and prior stock market performance suggest that high turnover is not mainly driven by new blockholder monitoring, but instead is substantially demanded by the block sellers. The probability of turnover is negatively associated with prior stock performance when the block purchaser is an outsider and turnover is not part of the block sale contract. This is consistent with the active-investor paradigm, but represents a relatively small portion of the sample. Therefore, we can conclude that the disciplinary motive for turnover is relatively unimportant in our sample.
Consequently, our evidence overall does not support the active-investor paradigm, whereby new blockholders with special expertise and skills become active in management and generate improvements in shareholder value. Instead, our evidence suggests that the market anticipates that any benefits from blockholder activities are small or that they will be captured privately by the new blockholders.
These results differ, especially from those reported by Barclay and Holderness (1991). Our results may vary because the market for corporate control in the two sample periods is different. The 1980s were a period of significant innovation in the market for corporate control. Innovation occurred in the financing for takeovers (through the introduction of junk bonds) and in antitakeover methods (through the introduction of poison pills and new state antitakeover statutes). Thus, it is likely that certain organizational or operational changes effected through the negotiated block market in the 1970s were later handled more cheaply by other means (e.g., with leveraged buyouts). There are characteristics of the two samples that suggest this is a valid conjecture. For example, the firms in our sample are predominately suffering operating problems, but are not in declining industries to the same extent they are in the earlier sample. Additionally, Barclay and Holderness (1991) identify managerial resistance to block buyers in 34 of their total sample of 109 block trades. In a similar sample, we identify managerial resistance in only eight of 350 events (the z-value for the difference in proportions is 9.1). Thus, the more recently negotiated block market appears more aligned with normal succession and less aligned with providing discipline, consistent with our results.
We thank an anonymous referee, Jennifer Bethel, Larry Dann, Harry and Linda DeAngelo, Larry Harris, Mark Huson, and seminar participants at Arizona State University, the Ohio State University University of Nevada, Las Vegas. and University of Southern California for valuable comments and suggestions. Saeyoung Chang acknowledges financial support from Shustek/Vestin and CB Richard Ellis Summer Research Grants.
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(1) Huson, Malatesta, and Parrino (2004) examine CEO turnover and find that performance improvement is positively related to the appointment of an outsider CEO, rather than an insider.
(2) The SEC stopped releasing the Ownership Reporting System file to the public after 1990.
(3) Of the 148 trades eliminated, 98 pass the further screens we impose and would otherwise be included in our study. Of these trades, 53 are purchases and 27 are sales by the holder of the largest assembled block. The 53 purchases do not appear to be changes in control. Mean (median) holdings prior to the purchase are 32.5% (26.0%) and after are 43.8% (41.6%). Also, 26 of the 27 sales by the largest blockholder do not change the holder's identity, and, as such, do not appear to be changes in control either. Mean (median) holdings prior to the sale are 46.5% (46.2%) and after the sale 31.9% (27.6%). Therefore, a strong majority &these trades can be characterized as either consolidation or portfolio rebalancing trades. Only one trade (the remaining member of the 27) represents a change in the identity of the holder of the largest assembled block. In this case, a 10.7% blockholder sold a 7.4% block and an existing 9.3% block became the largest assembled block.
(4) Two of the firm's announcements are separated by approximately four and eight years, with no overlap for the three- year horizon we use for the turnover analysis. The third firm's announcements are separated by less than three years with one executive turnover during the overlap period. We count this turnover only once.
(5) We classify these 13 events as outsiders purchasing from insiders, which is the SEC classification. We classify nine events as insiders purchasing from outsiders, which is not the SEC classification. The SEC classifies these as insider to insider transactions. Thus, we have no outsider-to-outsider transactions. Also, it may be debatable that an otherwise nonaffiliated blockholder who has a seat on the board of directors is really an "'insider." Such misclassifications reduce the power of our tests.
(6) Block price information is available for 156 of our 159 events. In 150 sales, the transaction is straight cash. Four sales are paid with promissory notes and two with a combination of cash and a promissory note. We value the promissory notes at their face amount. Our announcement date convention uses WSJ announcement dates or the day after the reported date if the source is a news wire story.
(7) The premiums as a fraction of equity capitalization more directly relate to the magnitude of private benefits potentially available to the new blockholder (Barclay and Holderness, 1989).
(8) This is the important restriction in our sample selection process. Because the SEC classifies nonaffiliated parties who own 10% or more of the outstanding shares as insiders, our sample selection differs from that of Barclay and Holderness (1989, 1991) only in that we omit trades (that they would include) between nonaffiliated parties where the block trade size is between 5% and 10% of outstanding shares. Our requirement that the sample includes only transactions involving the largest assembled block makes these omissions minor. Only seven block trades in our sample are smaller than 10% of the shares outstanding.
(9) We also have used simple rather than continuously compounded rates of return. This choice makes no important difference in our study. See, for example, DeAngelo et al. (1996) who report important differences in their study.
(10) Barclay and Holderness (1991) do not say the 5.6% is significant and it is not in their Table II (over the period -40 to 240), but on page 866 and in the abstract, they treat the estimate as if it were reliably positive.
(11) This negative CAR is not evidence of an inefficient market since in arriving at our sample of 159, we exclude 63 events where the firm is taken over within one year of the block trade. However, there is downward drift (Days 1 through 240) in the total sample that includes these observations suggesting an inefficient market or a misspecification of the generating process in our CAR estimations. The mean and median CARs for the total (inclusive) sample are 12.18% and 5.06%, respectively, over Days 1 through 240. Both estimates are significant.
(12) As stated above, the choice between simple and continuously compounded returns makes no important difference in our study. For the total sample, the mean CAR is -8.06% calculated over Days -40 through 240 using simple returns.
(13) For the entire sample of all firms that includes the firms taken over (222 events), the mean and median CARs are 0.58% and 9.70% (both insignificant) over Days M0 through 240. Although the median looks big, with about 55% of abnormal returns positive, the Wilcoxon test yields a p-value of only 0.403.
(14) In the three years prior to the trade (Event Days -720 through -41), our sample firms have significant mean and median net of industry returns of-67.80% and -69.44%. We estimate these using equally weighted industry indices calculated for each event using all other firms with the same two-digit standard industrial classification (SIC) code from the CRSP files. Net of market mean and median returns estimated over the same period are -62.83% and-64.89%, respectively (also significant). These numbers compare with average returns of 8.4% and -41.5% measured net of industry and net of market, respectively, reported by Barclay and Holderness (1991) for the three years prior to their trades. The net of market number in their study is significantly negative.
(15) This is our control for the survival bias.
(16) Similar computation method is used in Levis (2011).
(17) The breakpoints for market capitalization and book-to-market ratio are obtained from Ken French (http://mba.tuck.dartmouth.edu/pages/faculty/ken, french/data_library.html).
(18) Data on the three factors are obtained from Ken French at http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html.
(19) Mitchell and Stafford (2000), Hertzel et al. (2002), and Byun and Rozeff (2003) require a minimum number of observations to calculate a monthly portfolio return. We also run the estimation without requiring a minimum and using weighted least squares, where we weight with the number of observations in the event portfolio. These alternative specifications (not tabulated) yield qualitatively similar results to those we present.
20) When matching on four-digit SIC codes, we require at least five firms in the industry. We select the firm with the closest equity capitalization and then check the WSJ to insure that the firm has not been taken over during the first year (as in the block trade sample). If the firm has been taken over, we select the firm next closest in size. If there are fewer than five firms in the four-digit industry code, we use the three-digit industry code. Firms that disappear after the first year (for whatever reason) are not replaced.
(21) We are able to use these seven block trade firms later in the multivariate portion of the study as we can definitely classify them as having top executive turnover. We exclude them here because the firms do not survive for a full year subsequent to the block trade.
(22) We use a binomial approximation to test the equality of proportions in the two samples.
(23) There is no block trade turnover in Year 2, and the postblock turnover is no different from turnover in the control sample. In Year 3, postblock turnover is significantly lower (p-value = 0.06) in the block sale sample for the president. The block trade turnover in Year 3 may seem odd, but the press announcements for Motor Club of America and Servico, Inc., report that employment for a specified number of years beyond the date of the sale (for the block seller) was part of the block sale contract.
(24) For this test, we reduce the sample size by the number of block trade turnovers.
(25) There are 72 postblock departing top executives. We are unable to find the ages of three of them.
(26) We also estimate regressions with performance measured over the year prior to the company's first turnover announcement date. These results are qualitatively the same as those we report.
(27) We have estimated these regressions (untabulated) using a two-stage estimation method where board seat for new blockholder is treated as endogenous (Maddala, 1983). We omit the outsider buys variable from the Table VI equivalent regressions for identification purposes. These estimations are qualitatively the same as those we report. Other explanatory variables listed in Table VI appear reasonably predetermined. Also, significance levels are not qualitatively different when we use robust standard error calculations (White, 1980).
(28) We also count (but do not report) frequencies of the following categories with similar results: restructuring/reorganization other than divestiture/spinoff, acquisition of a block of other firm's shares, disposition of a block of other firm's shares, received a contract, issued stock, issued debt, obtained a bank loan, new block investment in firm's shares, and adopt anti-takeover measure. These categories account for most nondividend/earnings announcements.
(29) We also look at the dollar magnitude of the pre- and postevent divestitures. Seven prior event divestitures (that have information available) have a median value of $19.0 million, whereas, twelve postevent divestitures have a median value of $11.2 million. The mean value ($188.5 million) is larger for the prior than for the postevent divestitures ($11.2 million). All difference tests are insignificant.
(30) This is suggested by Fama and Jensen (1983), DeAngelo and DeAngelo (1985), Demsetz and Lehn (1985), and Stulz (1988). Also, Villalonga and Amit (2010) find individual blockholders are more likely to appropriate private benefits of control. Evidence of a negative correlation between announcement return and individual block acquirer is shown by Kang and Kim (2008).
(31) We estimate the Tobin's Q ratio as the market value of common stock plus the estimated market value of debt and preferred stock divided by the replacement value of assets. We follow McConnell and Servaes (1990), who use a variation of the Lindenberg and Ross (1981) algorithm, in these calculations. The indicator variable representation for Tobin's Q ratio follows the work of Lang, Stulz, and Walking (1989) who find sharper results using this instrumental variable rather than the actual estimated value. Using an instrumental variable can help with measurement error and the resulting attenuated coefficient estimates.
(32) Undistributed cash flow is after-tax cash flow not distributed to security holders as either interest or dividend payments (Lehn and Poulsen, 1989).
(33) The actual classification of "related business" is from information contained in the announcement, from the business description in the Register (Standard & Poor's), and from examining proxy statements. We are unable to use the usual SIC code sources as our corporate purchasers are frequently foreign or privately owned.
(34) We have also estimated these regressions using weighted least squares. The qualitative results are unchanged with this procedure.
(35) There are 59 events here rather than 63 as reported earlier as the block price is unavailable for four events.
Saeyoung Chang and David Mayers *
* Saeyoung Chang is a Professor in the Department of Finance at the University of Nevada, Las Vegas in Las Vegas, NV. David Mayers is an Emeritus Professor in the School of Business Administration and the A. Gary Anderson Graduate School of Management at the University of California, Riverside in Riverside, CA.
Table I. Sample Distribution by Year This table presents distribution of 222 announcements of insider negotiated block trades of the largest assembled block over the period 1979-1999, by year. The sample of firms not taken over within one year consists of 159 announcements. The sample of firms taken over within one year consists of 63 announcements where the firm is taken over within one year of the block trade. Year Firms Not Firms Total Taken Over Taken Over within One within One Year Year 1979 3 1 4 1980 5 5 10 1981 6 3 9 1982 3 2 5 1983 7 4 11 1984 8 3 11 1985 12 4 16 1986 8 10 18 1987 6 6 12 1988 14 7 21 1989 12 0 12 1990 7 1 8 1991 7 1 8 1992 8 1 9 1993 8 0 8 1994 7 2 9 1995 6 3 9 1996 13 2 15 1997 10 3 13 1998 5 4 9 1999 4 1 5 Total 159 63 222 Table II. Descriptive Statistics This table reports descriptive statistics for 159 insider negotiated trades of the largest assembled block from 1979 to 1999. The sample excludes block trade events where the firm is taken over within one year of the block trade. Premium paid over market price before trade is computed based on the market price ten trading days before the announcement. Premium paid over market price after trade is computed based on the closing market price on the day of the block trade announcement. Book-to-market ratio is book value of equity for the fiscal year end divided by market value of equity for the calendar year end, before the block trade announcement. Total market value of common stock is the market capitalization ten trading days before the announcement. Mean Median Std Dev Fraction of outstanding shares 30.2% 28.0% 13.7% traded Dollar amount of transaction (in $37.4 $10.6 $206.6 millions of 1999 dollars) (a) Premium paid over market price 17.4% 12.9% 39.2% before trade (a) Premium paid over market price 6.2% 3.4% 32.3% after trade (a) Premium as a fraction of market 6.2% 2.7% 14.3% capitalization before trade (a) Premium as a fraction of market 2.4% 0.9% 11.9% capitalization after trade (a) Book-to-market ratio 0.91 0.76 0.80 Total market value of common $120 $27 $453 stock (in millions of 1999 dollars) Seller's shareholding before trade 31.6% 31.5% 13.8% Buyer's shareholding after trade 33.1% 33.0% 14.2% Minimum Maximum Fraction of outstanding shares 5.8% 79.3% traded Dollar amount of transaction (in $0.8 $2,570.0 millions of 1999 dollars) (a) Premium paid over market price -63.1% 191.3% before trade (a) Premium paid over market price -69.5% 131.1% after trade (a) Premium as a fraction of market -16.9% 69.3% capitalization before trade (a) Premium as a fraction of market -32.3% 65.4% capitalization after trade (a) Book-to-market ratio -3.10 3.71 Total market value of common $2 $5,366 stock (in millions of 1999 dollars) Seller's shareholding before trade 5.8% 79.3% Buyer's shareholding after trade 7.2% 79.3% (a) The number of observations is 156 as trade price is unavailable in three cases. All trades, but six are for straight cash. Two of these six are paid with a combination of cash and promissory notes. The remaining four trades are paid for with promissory notes that are valued at face value. Table III. Cumulative Abnormal Returns for 159 Announcements of Largest Block Traded This table reports mean and median cumulative abnormal returns (%) for the sample of 159 announcements of largest block traded from 1979 to 1999. The sample excludes block trade events where the firm is taken over within one year of the block trade. Abnormal returns are estimated using the market model method. The announcement date (Day 0) is the day of the first WSJ announcement of the private trade, or if the first announcement appears as a news wire story the day following the story appearance. Market model parameters are estimated over the period from Days -720 through -241. z-statistics are in parentheses and the % positive statistic is in brackets. The Wilcoxon signed-rank test is used for the % positive. Event Window Total Insider Sells Sample to Outsider (N = 159) (N = 118) Announcement Period: [-1, 0] Mean 5.50 ** 6.25 ** (11.81) (11.71) Median 2.20 ** 3.98 ** [67.3] [71.2] [-10, 0] Mean 10.53 ** 11.44 ** (10.31) (9.49) Median 7.57 ** 7.34 ** [69.8] [69.5] [-20, 0] Mean 11.56 ** 11.56 ** (8.02) (6.68) Median 8.41 ** 7.89 ** [75.5] [75.4] [-40, 0] Mean 11.76 ** 12.56 (6.00) (5.60) Median 9.61 ** 10.18 [69.2] [69.5] Postannouncement Period: [1, 40] Mean -1.51 -1.59 (-1.22) (-1.18) Median -4.28 -5.13 [40.3] [38.1] [1, 240] Mean -20.74 ** -20.08 ** (-6.58) (-5.72) Median -19.95 ** -17.17 * [37.7] [39.8] Announcement and Postannouncement Period [-40, 240] Mean -8.98 ** -7.51 ** (-3.64) (-3.00) Median -6.01 -4.48 [45.3] [45.8] Insider Event Window Insider Buys Trades from Outsider with Insider (N = 9) (N = 32) Announcement Period: [-1, 0] Mean -2.53 ** 5.00 ** (-3.02) (5.44) Median -1.68 0.82 * [33.3] [62.5] [-10, 0] Mean -5.38 * 11.64 ** (-2.11) (5.88) Median -9.31 10.40 ** [33.3] [81.3] [-20, 0] Mean 0.00 14.79 ** (-0.18) (5.16) Median -3.09 14.29 ** [44.4] [84.4] [-40, 0] Mean -3.78 13.18 ** (-0.85) (3.08) Median -0.69 11.20 ** [44.4] [75.0] Postannouncement Period: [1, 40] Mean -3.56 -0.63 (-0.97) (-0.07) Median -3.48 -3.13 [44.4] [40.9] [1, 240] Mean -14.15 -25.04 ** (-1.09) (-3.11) Median -32.95 -22.22 * [22.2] [34.4] Announcement and Postannouncement Period [-40, 240] Mean -17.93 -11.86 (-1.33) (-1.66) Median -31.03 -2.77 [22.2] [50.0] ** Significant at the 0.01 level. * Significant at the 0.05 level. Table IV. Long Run Stock Performance This table presents long run returns following 159 insider negotiated block trades from 1979 to 1999. The sample excludes block trade events where the firm is taken over within one year of the block trade. Panel A reports buy- and-hold abnormal returns for the 14-and 38-month periods around the block trade announcement. The 14-month window is from Month -1 through Month 12, where Month 0 is the announcement month. The 38-month window is from Month - 1 through Month 36. The abnormal return is computed by subtracting the buy-and-hold return on the matching firm from that of the sample firm. We find a matching firm based on the closest market capitalization within the same book- to-market quintile at year end prior to the announcement. The matching sample excludes firms taken over within one year of the sample firm's block trade announcement. The bootstrapped p-value is the percentile of the sample firm mean return relative to the 1,000 matching firm mean returns from random portfolios matched by the same quintiles of market capitalization and market-to-book ratio. The median is tested using the Wilcoxon signed-rank test. Panel B presents calendar-time abnormal returns computed from event portfolio regressions. Monthly excess portfolio return ([R.sub.p] -[R.sub.f]), where [R.sub.f] is the Treasury bill rate, is regressed on the three factors from Fama and French (1993). [R.sub.m] -[R.sub.f] is the excess return on the market, SMB is the size factor, and HML is the book-to- market factor. The intercept ([alpha]) represents the abnormal return per month, and the implied abnormal return is computed as [(1 + [alpha]).sup.n] -1 , where n = 14 and 38 for the 14-and 38-month window, respectively. The event portfolio requires a minimum of five observations. Panel A. Buy-and-Hold Abnormal Returns 14-month window [-1, 12] 38-month window [-1, 36] Raw Return Abnormal Raw Return Abnormal Return Return N 159 159 159 159 Mean 16.99% -2.06% 27.53% -21.64% (Median) (-2.86%) (0.03%) (-12.45%) (-23.00%) ** Bootstrapped 0.636 0.088 p-value Panel B. Calendar-time Abnormal Returns [R.sup.pt] - [R.sup.ft] = [alpha] + [[beta].sub.m] (R.sub.mt] - [R.sup.ft]) + [[beta].sub.s] SMB + [[beta].sub.s] HML + [[epsilon].sup.t] 14-month Window [-1, 12] 38-month Window [-1, 36] [alpha] Implied [alpha] Implied 14-mo. AR 38-mo. AR Full Sample -0.319 -4.37% -0.509 -17.63% (N= 159) (p-value) (0.482) (0.109) Adjusted 0.306 0.538 [R.sup.2] ** Significant at the 0.05 level. Table V. Top Executive Turnover Following Insider Negotiated Block Trades This table presents top executive turnover following the announcement of an insider negotiated block trade involving the largest assembled block from 1979 to 1999. Turnover is designated as block trade if the departing executive is the block seller or the turnover is included in the block sale announcement. Otherwise, it is designated as postblock. [N.sub.p] (where P = CEO, Pres, or Chair) varies for each executive position and represents the number of firms that both survive to the end of the designated year relative to the block trade announcement and also list having the position. N represents the total number of firms that survive to the end of the designated year relative to the block trade announcement. The differences between N and [N.sub.p] represent the number of surviving firms not listed as having a particular executive position. The control sample is constructed by matching the 159 block trade firms not taken over within one year on the basis of equity capitalization and four/ digit SIC codes (three/digit matching is used where four/digit matching is not possible). The tests below compare the total turnover percentages, total (%), and the proportion (postblock/ [N.sub.p]--block-trade)) in the block trade sample with the proportion, postblock/[N.sub.p], in the control sample. A binomial approximation is used to test the equality of proportions in the two samples. Block Trade Sample Year 1 Year 2 Year 3 CEO turnover: Total (%) (51) ** (8) (12) Block trade 48 0 1 Postblock 20 10 12 [N.sub.CEO] 134 118 109 Postblock/[N.sub.CEO] (%) (15) (8) (11) President turnover: Total (%) (39) ** (14) (8) * Block trade 35 0 2 Postblock 24 18 8 [N.sub.Pres] 150 132 120 Postblock/[N.sub.Pres] (%) (16) (14) (7) Chairman turnover: Total (%) (54) ** (8) (9) Block trade 62 0 1 Postblock 15 10 10 [N.sub.Chair] 143 129 117 postblock/[N.sub.Chair] (%) (10) (8) (9) Turnover in at least one of the (68) ** (17) (15) top three positions: Total (%) Block trade 75 0 2 Postblock 29 23 16 N 152 136 124 Postblock/N (%) (19) (17) (13) Reason for delisting: 0 5 3 Acquired 7 10 8 Bankrupt 0 1 1 Control Sample Year 1 Year 2 Year 3 CEO turnover: Total (%) Block trade Postblock 10 7 11 [N.sub.CEO] 108 99 94 Postblock/[N.sub.CEO] (%) (9) (7) (12) President turnover: Total (%) Block trade Postblock 22 14 18 [N.sub.Pres] 149 134 126 Postblock/[N.sub.Pres] (%) (15) (10) (14) Chairman turnover: Total (%) Block trade Postblock 10 13 10 [N.sub.Chair] 143 123 115 postblock/[N.sub.Chair] (%) (7) (11) (9) Turnover in at least one of the top three positions: Total (%) Block trade Postblock 26 22 22 N 153 139 130 Postblock/N (%) (17) (16) (17) Reason for delisting: 0 10 5 Acquired 4 4 4 Bankrupt 2 0 0 ** Significant at the 0.05 level. * Significant at the 0.10 level. Table VI. Multinomial Logistic Regression Results Explaining Top Executive Turnover Following Insider Negotiated Block Trades This table presents multinomial logistic regressions explaining top executive turnover for 159 firms with an announcement of an insider negotiated block trade involving the largest assembled block from 1979 to 1999. Turnover is designated as block trade if the departing executive is the block seller or the turnover is included in the block sale announcement. Otherwise, it is designated as postblock. The dependent variable is one if there is postblock turnover, two if there is block trade turnover, three if there is both postblock and block trade turnover, and zero if there is no turnover during the three-year period following the announcement. No turnover is the base outcome. There are 34 postblock turnover, 52 block trade turnover, 27 postblock and block trade turnover, and 46 no turnover firms. New blockholder is an individual is an indicator variable set equal to one if the block buyer is an individual. Outsider buys is an indicator variable set equal to one if the buyer is an outsider. Board seat for new blockholder is an indicator variable. Seller is a top-three executive is an indicator variable set equal to one if the block seller is CEO, president, or chairman of the board. Prior performance is the net of market stock return estimated with daily stock return data over the 12 months ending 2 months before the block sale announcement. p-values are in parentheses. Postblock Block Trade Postblock and Turnover Turnover Block Trade Turnover Panel A. (1) (2) (3) Intercept -3.71 -6.12 -8.27 (0.000) (0.000) (0.000) New blockholder 3.02 2.79 2.24 is an individual (0.001) (0.009) (0.053) Outsider buys 1.61 1.19 2.12 (0.069) (0.272) (0.103) Board seat for 2.17 3.06 3.13 new blockholder (0.003) (0.003) (0.007) Seller is a top- 0.08 5.35 6.19 three executive (0.943) (0.000) (0.000) Prior performance -0.82 -1.05 -1.05 (net of market) (0.192) (0.189) (0.239) [chi square]-statistic 182.8 (0.000) Pseudo [R.sup.2] 0.424 Panel B. (1) (2) (3) Intercept -3.84 -6.39 -9.39 (0.000) (0.000) (0.000) New blockholder 3.39 3.01 2.49 is an individual (0.001) (0.006) (0.037) Outsider buys 1.30 1.24 3.06 (0.147) (0.283) (0.069) Board seat for 2.28 3.15 3.27 new blockholder (0.002) (0.002) (0.006) Seller is a top- 0.20 5.50 6.31 three executive (0.858) (0.000) (0.000) Prior performance 1.14 -0.89 -2.79 (net of market) (0.325) (0.551) (0.150) Outsider buys * -3.08 -0.78 1.37 Prior performance (0.037) (0.667) (0.540) [chi square]- 189.5 statistic (0.000) Pseudo [R.sup.2] 0.440 Table VII. Changes in Operations Following Insider Negotiated Block Trades This table presents changes in operations after block trades. The frequencies of operational events are compared between the two- year periods before and after the block trade for firms with an announcement of an insider block trade involving the largest assembled block. Frequencies are based on reports in the WSJ. The sample decreases to 132 from 159 as firms are required to be listed in the WSJ Index during the four year period. t-test is used for the difference in proportions. Total Top No Top Sample Executive Exec. (N = 132) Turnover Turnover (N = 94) (N = 38) Divestiture/Spinoff Before 14 9 5 (10.6%) (9.6%) (13.2%) After 18 15 3 (13.6%) (16.0%) (7.9%) p-value (diff) 0.435 0.203 0.324 Merger/acquisition: Before 16 8 8 (12.1%) (8.5%)* (21.1%)* After 22 15 7 (16.7%) (16.0%) (18.4%) p-value (diff) 0.258 0.127 0.744 Share repurchase: Before 8 6 2 (6.1%) (6.4%) (5.3%) After 5 2 3 (3.8%) (2.1%) (7.9%) p-value (diff) 0.407 0.289 0.661 Layoff/plant closing: Before 7 3 4 (5.3%) (3.2%) (10.5%) After 3 2 1 (2.3%) (2.1%) (2.6%) p-value (diff.) 0.207 0.657 0.183 Top Executive Top Executive Turnover Turnover Buys Outsider Buys Insider (N = 77) (N = 17) Divestiture/Spinoff Before 9 0 (11.7%) (0.0%) After 13 2 (16.9%) (11.8%) p-value (diff) 0.375 0.164 Merger/acquisition: Before 6 2 (7.8%) (11.8%) After 12 3 (15.6%) (17.6%) p-value (diff) 0.135 0.668 Share repurchase: Before 6 0 (7.8%) (0.0%) After 2 0 (2.6%) (0.0%) p-value (diff) 0.159 1.000 Layoff/plant closing: Before 3 0 (3.9%) (0.0%) After 2 0 (2.6%) (0.0%) p-value (diff.) 0.658 1.000 * Significant at the 0.10 level. Table VIII. Changes in Operating Performance Following Insider Negotiated Block Trades This table reports the median industry-adjusted return on assets (ROA) and the median change in industry adjusted ROA for 159 firms with an announcement of an insider negotiated block trade involving the largest assembled block from 1979 to 1999. ROA is defined as earnings before interest, taxes, depreciation, and amortization divided by total assets (EBITD-total assets). Industry-adjusted ROA is net of the industry median. Firms' two-digit SIC codes are used to define industries. Year 0 is the fiscal year in which the block trade took place. The Wilcoxon signed-rank test is used for top-executive turnover versus no top-executive turnover or top-executive turnover outsider buys versus top-executive turnover insider buys. Sample sizes are under the ROAs and p-values are in parentheses. Total Top No Top Sample Executive Executive Turnover Turnover Year -3 -2.7% -2.1% -3.4% 136 98 38 (0.003) (0.016) (0.094) Year -2 -1.6% -1.4% -2.6% 149 106 43 (0.033) (0.111) (0.141) Year -1 -2.8% -5.9% ** 0.2% ** 159 113 46 (0.001) (0.001) (0.579) Year 0 -5.4% -7.7% *** -1.1 % *** 156 111 45 (0.001) (0.001) (0.307) Year 1 -5.3% -7.0% ** -2.0% ** 143 101 42 (0.001) (0.001) (0.201) Year 2 -3.1% -5.2% *** 0.9% *** 133 94 39 (0.001) (0.001) (0.235) Year 3 -2.0% -3.7% * -0.7% * 124 86 38 (0.003) (0.001) (0.727) Change (0,1) -0.4% -0.3% -0.8% 143 101 42 (0.308) (0.625) (0.234) Change (0,2) 1.0% 0.8% 1.5% 133 94 39 (0.357) (0.632) (0.311) Change (0,3) 1.5% 2.1% 0.5% 124 86 38 (0.108) (0.144) (0.685) Top Executive Top Executive Turnover Turnover Outsider Buys Insider Buys Year -3 -2.8% 1.6% 81 17 (0.009) (0.927) Year -2 -1.6% -0.7% 87 19 (0.139) (0.541) Year -1 -6.1% -5.9% 92 21 (0.001) (0.004) Year 0 -7.7% -7.7% 90 21 (0.001) (0.001) Year 1 -7.5% -1.2% 83 18 (0.001) (0.048) Year 2 -7.0% -0.4% 77 17 (0.001) (0.159) Year 3 -5.0% ** 1.3% ** 69 17 (0.001) (0.712) Change (0,1) -0.5% * 3.6% * 83 18 (0.261) (0.304) Change (0,2) -0.9% ** 5.0% ** 77 17 (0.669) (0.027) Change (0,3) 1.5% ** 13.5% ** 69 17 (0.642) (0.015) *Significant at the 0.10 level. **Significant at the 0.05 level. ***Significant at the 0. Table IX. OLS Regression Results Explaining Announcement Abnormal Returns for 156 Insider Negotiated Block Trades This table presents ordinary least squares regressions of the announcement abnormal return [-10, 0] for 156 insider negotiated block trades from 1979 to 1999. Block trade turnover is an indicator variable that is equal to one if the block seller is a departing executive or if executive turnover is included in the block sale announcement. New blockholder is an indicator variable that is equal to one if the block buyer is an individual. Outsider buys is an indicator variable that is equal to one if the buyer is an outsider. Board seat for new blockholder is an indicator variable. Management position taken by new blockholder is an indicator variable. Block premium per share is the ratio of the block price per share to the closing share price on Day -10 minus 1.0. Prior performance is the net of the market stock return estimated with daily stock return data over the 12 months ending 2 months prior to the block sale announcement. Low Tobin's Q is an indicator variable set equal to one if our Tobin's Q estimate is less than one. Undistributed cash flow is the posttax cash flow not distributed to security holders as either interest or dividends, scaled by the book value of assets. Related business is an indicator variable that is equal to one if the purchaser is a corporation and is in the same line of business. Prior performance*outsider buys is an interaction variable set equal to prior performance when an outsider buys and zero otherwise. Fraction purchased is the percentage of the outstanding equity purchased. Log of equity capitalization refers to the equity capitalization of the firm. The number of observations is 156 because block-premium per share is unavailable in three cases. Regression Number: (1) (2) Intercept 0.038 0.054 * (1.23) (2.04) Blockholder activity Block trade turnover (+) 0.003 (0.10) New blockholder is an individual (+) Outsider buys (+) 0.010 (0.27) Board seat for new blockholder (+) Management position for new blockholder (+) Size of benefits pool Block premium per share (+) 0.170 ** 0.183 ** (4.62) (4.45) Prior performance (net of market) (-) -0.126 * -0.099 ** (-1.96) (-3.07) Low Tobin's Q (+) -0.030 (-0.96) Undistributed cash flow (+) -0.151 (-1.55) Related business (+) 0.003 (0.11) Prior performance *outsider buys (-) 0.029 (0.39) Fraction purchased (+) Log of equity capitalization (-) F-statistic 8.28 ** 6.03 ** Adjusted [R.sup.2] 0.16 0.16 Regression Number: (3) (4) Intercept 0.526 * 0.543 * (2.24) (2.17) Blockholder activity Block trade turnover (+) 0.015 (0.38) New blockholder is an individual (+) 0.015 0.015 (0.45) (0.36) Outsider buys (+) 0.044 0.035 (1.04) (0.82) Board seat for new blockholder (+) -0.036 -0.029 (-0.82) (-0.67) Management position -0.040 -0.048 for new blockholder (+) (-1.08) (-1.05) Size of benefits pool Block premium per share (+) 0.149 ** 0.168 ** (3.94) (4.05) Prior performance (net of market) (-) -0.077 * -0.074 * (-2.27) (-2.13) Low Tobin's Q (+) -0.041 (-1.30) Undistributed cash flow (+) -0.113 (-1.12) Related business (+) -0.001 (-0.02) Prior performance *outsider buys (-) Fraction purchased (+) 0.124 0.130 (1.10) (1.14) Log of equity capitalization (-) -0.029 * -0.029 * (-2.34) (-2.24) F-statistic 5.62 ** 3.97 ** Adjusted [R.sup.2] 0.19 0.19 ** Significant at the 0.01 level. * Significant at the 0.05 level.
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|Author:||Chang, Saeyoung; Mayers, David|
|Date:||Sep 22, 2012|
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