Going-Private Restructuring and Earnings Expectations:
A Test of the Release of Favorable Information for Target Firms and Industry Rivals*
Jeremy Goh
Associate Professor of Finance
Singapore Management University
Michael Gombola**
Professor of Finance
Drexel University
Feng-Ying Liu
Professor of Finance
Rider University
De-Wai Chou
Assistant Professor of Finance
National Chung Cheng University
Printing Date: July 31, 2017
*A previous version of this paper received the award for “Outstanding Paper in Corporate
Finance” by the Eastern Finance Association at its 2002 annual meeting.
**Corresponding author: Michael Gombola, Department of Finance, Drexel University,
Philadelphia, PA 19104. Tel. (215) 895-1743. Fax (215) 895-2955.
E-mail:[email protected].
Going-Private Restructuring and Earnings Expectations:
A Test of the Release of Favorable Information for Target Firms and Industry Rivals
Abstract
This research documents that analysts significantly revise upward their forecasts of
earnings for targets of going-private bids subsequent to the announcement of going-private
restructuring. These upward forecast revisions are significantly related to the stock price reaction
to the announcement. Potential tax savings and the reduction of agency costs associated with
going private restructuring do not appear to explain these upward forecast revisions. Analysts
also significantly revise upward their forecasts of earnings for industry rivals of targets of goingprivate bids. Furthermore, these upward forecast revisions for rivals are significantly related to
the stock price reaction for rivals. Forecast revisions for rivals are not related to proxies for
agency costs or potential tax benefits of leverage. Overall, our results provide evidence
supporting the hypothesis that going-private announcements convey favorable information about
future earnings of targets of going-private bids as well as their industry rivals.
Key words: Going-private restructuring; Information transfer; Earnings expectations
Going-Private Restructuring and Earnings Expectations:
A Test of the Release of Favorable Information for Target Firms and Industry Rivals
1. Introduction
Previous empirical studies examining the announcement effects of going-private
restructuring on stock returns document a positive announcement period abnormal stock return.
(e.g., DeAngelo, DeAngelo and Rice (1984), Lehn and Poulsen (1989), Marais, Schipper and
Smith (1989) and Slovin, Sushka and Bendeck (1991)). This empirical finding is consistent with
several explanations or hypotheses. These explanations include: (i) revelation of favorable
private information about the future earnings and cash flows of the company to be taken private
(the information hypothesis); (ii) mitigation of agency problems of free cash flow to be realized
when the company is taken private (the free cash flow hypothesis); (iii) potential tax savings
associated with financing the transaction (the tax benefits hypothesis); and (iv) wealth
redistribution from bondholders to stockholders as the bondholders bear more risk of the private
company (the wealth transfer hypothesis). The observed positive abnormal stock returns could
result from any of these hypotheses or a combination of them.
In this study, we examine the information content of going-private transactions. We test
the hypothesis that announcements of going-private transactions convey favorable information to
the market about earnings prospects for targets of going-private bids. To test the hypothesis, we
use analysts’ forecasts of future earnings as a proxy for investor expectations, and examine
monthly revisions of analysts’ forecasts of future earnings around the going private
announcement. Examining analysts’ revisions of earnings forecasts can provide direct evidence
on the information hypothesis - that the wealth effect of going-private transactions results from
1
information about earnings prospects for companies to be taken private.
This hypothesis predicts an upward revision of earnings forecasts by analysts subsequent
to announcement of going-private restructuring. A positive correlation between the
announcement-period stock returns and earnings forecast revisions would provide further support
for the information hypothesis. A positive correlation, however, cannot completely rule out the
contribution of other explanations to the observed positive stock price return associated with a
going-private announcement. In further analyses, we control for the potential effect of mitigation
of agency problems, tax savings, and potential contaminating information.
We find significant and positive abnormal forecast revisions for current-year earnings of
target firms. We also find a significant positive relation between abnormal earnings forecast
revisions for target firms and the abnormal stock return around the announcement of goingprivate transactions. This relation remains even after controlling for the potential effects of free
cash flow and tax benefits of debt, as well as other contaminating information. Furthermore,
results show that neither the announcement period stock returns nor the earnings forecast
revisions subsequent to the announcement can be explained by the target’s free cash flow or its
potential tax benefits of debt. Our results provide strong support for the hypothesis that goingprivate announcements convey favorable information about earnings prospects of target firms.
Slovin, Shushka, and Bendeck (1991) argue that financial markets could perceive the
private information revealed in the announcement of going-private restructuring as industrywide, rather than firm-specific. They document a significant announcement-period abnormal
return of 1.32 percent for industry rival firms and conclude that the financial market perceives the
information conveyed in the announcement of going-private transactions as industry-wide. As
indicated by Slovin, Shushka and Bendeck (1991), their finding of intra-industry valuation effect
2
of a going-private announcement could result from any of three contributing factors: (1) private
information revealed about improved earnings and cash flows for industrial rivals (i.e., intraindustry information effects), (2) increased probability of takeover bids for rival firms in the
same industry (i.e., intra-industry takeover probability effects), and (3) the potential for
ameliorating the agency problems of free cash flow for other firms in the industry, in response to
a takeover bid (i.e., intra-industry agency problem effects). The observed positive stock price
reaction to a going-private buyout bid for industry rivals could be consistent with any of these
effects or a combination of them.
In this study, we test the hypothesis of intra-industry information effects by examining
revisions in analysts’ earnings forecasts for rivals of going-private bids. By testing earnings
forecast revisions of rival firms, we extend the study by Slovin, Shushka and Bendeck (1991) in
narrowing down the factors contributing to stock price effects on rival firms. Upward earnings
forecast revisions for rival firms would provide direct evidence supporting the intra-industry
information transfer explanation. An information transfer to rivals must originate with
information about target firms. Therefore, evidence in support of an intra-industry information
transfer effect would also provide support for the information hypothesis for target firms.
Upward earnings forecast revisions for rivals would not support the other two explanations of a
positive stock price reaction. An increased probability of takeover for industry rivals could
produce a positive price reaction for these firms, but should not produce an upward revision in
earnings forecasts for rivals, particularly for current-year earnings. The potential for industrywide reduction in agency problems of free cash flow could possibly be associated with eventual
improvements in earnings forecasts if management preemptively improves earnings performance
in response to increased takeover probability. Although eventual earnings improvements could be
3
observed, it is doubtful that analysts would immediately revise earnings forecasts upward due to
the possibility that management could potentially reduce agency problems and improve earnings
in an attempt to thwart a takeover.
Consistent with Slovin, Shushka and Bendeck (1991), we find significant, positive
abnormal returns for rival firms around the announcement of buyout bids. We also find rival
firms experience significant upward revisions in analyst forecasts of current-year earnings and
five-year earnings growth. In addition, we find a significantly positive relation between forecast
revisions (both current-year earnings and 5-year earnings growth) and abnormal returns for rival
firms. This relation remains significant even after controlling for other variables, including the
free cash flow of rivals, debt capacity of rivals, relative size of targets and rivals, and identity of
the acquirers, as well as potentially contaminating information. Overall, our results for rival firms
provide strong support for the hypothesis that going-private announcements convey industrywide favorable information about earnings prospects.
2. Hypotheses and Related Literature
2.1. Hypotheses for Shareholder Gains of Target Firms
2.1.1. Mitigation of Agency Problems
Jensen (1986) suggests that corporate restructuring, such as going private transactions,
can be motivated by value enhancement engendered by reduction of agency costs otherwise
prevalent in firms owned by atomistic shareholders. By taking a firm private, the new
concentrated ownership group imposes discipline resulting in reduced overinvestment, and
reduced management perquisites unrelated to job performance. When investors recognize the
prospect of increased efficiency in investment and management, the market reacts positively to
4
the going-private announcement.
In a test of this hypothesis, Lehn and Poulsen (1989) report a significant relation between
a firm's free cash flow and the takeover premium. They also find that free cash flow is a predictor
of the probability of a firm being taken private. A later study by Halpern, Kieschnick, and
Rotenberg (1999) examines a sample of firms with dysfunctionally low managerial ownership
prior to going private and finds no evidence of agency problems of free cash flow. To the
contrary, this group of firms exhibits lesser investing activity and lower free cash flow than a
matched sample of public firms or a matched sample of target firms in mergers.
Examining a sample of firms with high managerial ownership prior to going public,
Halpern, Kieschnick, and Rotenberg (1999) also find no evidence that mitigation of agency
problems is a major motivating factor in taking these firms private. Instead, managers increase
their proportionate holdings in the firm while at the same time they reduce their dollar holdings
in the firms taken private. By substituting external debt for their own equity, managers “cash out”
of the firm taken private and increase their ability to diversify personal portfolios.
2.1.2. Tax savings
Wealth gains observed in going-private transactions could result from tax advantages
associated with this form of corporate restructuring. As detailed by Kaplan (1989), and
Lowenstein (1985), these tax advantages include the deductibility of interest payments associated
with increased debt, increased deduction for depreciation, and the tax advantages of financing the
transaction with employee stock ownership plans. Kaplan (1989) finds that tax benefits are an
important source of the wealth gains for a sample of management buyouts. He concedes,
however, that companies could obtain many of the same tax benefits without going private.
5
Further analysis of tax consequences of going-private transactions by Weston, Siu, and
Johnson (2001) reveals potential tax disadvantages of going-private transactions. These
disadvantages include capital gains tax paid by selling shareholders and taxes paid by the firm on
gains from asset sales as well as higher income taxes paid by the firm if it can increase its
earnings through efficiencies. Consequently, they conclude that the overall tax consequences of
a going-private transaction could be indeterminate.
Unused tax advantages of debt financing do not appear to be unique to firms taken
private. Examining a sample of firms taken private, Halpern, Kieschnick, and Rotenberg (1999)
find no difference either in debt utilization or in tax expenditures between firms later taken
private and a matched sample of firms that remain publicly held. Consequently, they find no
evidence that would suggest that firms taken private are unique in their ability to enjoy the tax
consequences of the transaction.
2.1.3. Wealth transfer
Since going private transactions are often financed through large increases in debt, the
financing could have an ancillary effect of wealth transfer between bondholders and
stockholders. This wealth transfer could explain (at least in part) the wealth effect in going
private transactions. Lehn and Poulsen (1988) find that the effect of a going private restructuring
on the value of debt securities is not significant. Marais, Schipper and Smith (1989) also find an
insignificant price effect on nonconvertible debt. Asquith and Wizman (1990), however, report
losses to bondholders of firms that are taken private.
2.1.4. Undervaluation and information asymmetry
The undervaluation or information asymmetry explanation for the positive stock price
6
effect observed in going private transactions stems from differences between insiders (“informed
shareholders”) and outsiders (“uninformed shareholders”) in their expectations of future earnings
and the true value of the firm. By tendering a premium-price takeover bid, the buyout group, who
are typically either incumbent management or buyout specialists, reveal their private information.
Halpern, Kieschnick, and Rotenberg (1999) show that targets of going-private
transactions are underperformers in earnings and stock price performance. Due to the
underperformance, it is plausible that expectations for these companies have been revised
downwards, perhaps overly so. Overdone pessimism could result in underpricing. Insiders, who
have a better understanding of future prospects, can capitalize on temporary underpricing, by
taking the firm private. At a later date, when the true prospects for the firm are better apparent to
investors, the firm can be taken public again to the profit of the group that has not succumbed to
the pessimism. DeGeorge and Zeckhauser (1993) show that after being taken private, firms
outperform their counterparts both in terms of accounting returns and stock price performance.
Insider trading prior to going-private announcements can provide an indirect test of the
information hypothesis. Harlowe and Howe (1993) and Kaestner and Liu (1996) find that
insiders of firms taken private engage in significant abnormal buying prior to the going-private
announcement. Kaestner and Liu also show that the insider buying is not related to either
potential tax savings or free cash flow of the target firm. It could, however, be in anticipation of a
premium-price transaction. This study provides a more direct test of the information hypothesis
by testing earnings forecast revisions associated with a going-private announcement, since
earnings forecasts are a more direct measure of prospects of the firm to be taken private.
7
2.2.
Industry-Wide Information Effects
2.2.1. Favorable Private Information about Future Earnings Prospects of Rivals
Foster (1981) describes the information transfer from an announcing firm to other firms
within an industry. Similarly, Szewczyk (1992) demonstrates how announcement of a stock
offering can lead to price reactions for similar firms. Likewise, Asness and Smirlock (1991)
describe how REIT bankruptcies affect valuation of all firms in the industry. In all of these cases,
the announcing firm generates information that is not only firm-specific but also industry-wide.
Industry-wide revision of expectations could transpire in response to a going-private
announcement. If a going-private bid reveals private information about earnings prospects of a
target firm, this favorable information could transfer to other firms within the same industry. The
conjecture of industry-wide information effects is supported by evidence that multiple goingprivate transactions within the same industry are commonly observed, to the extent that
industries could be considered subject to “buyout waves” (Ambrose and Winters, 1992).
Just as earnings forecasts can provide a direct test of the information effect for target
firms, it can also provide a direct test of intra-industry information transfer for rival firms. This
intra-industry information transfer effect predicts a positive revision in earnings forecasts for
rival firms. It also predicts a positive relation between the positive stock price reaction shown by
Slovin Shushka and Bendeck (1991) for rival firms and their earnings forecast revisions.
2.2.2. Industry-Wide Reduction in Agency Problems of Free Cash Flow
A takeover aimed at reducing the agency problems of free cash flow for one firm within
the industry could provide information about industry-wide agency problems and their potential
for attenuation. The ultimate effect on stock prices is not clear, however. If investors were
8
previously unaware of agency problems within the target firm and the industry, then the
discovery of such agency problems could lead to a negative stock price reaction and industrywide downward revision in earnings forecasts.
If investors view a takeover bid in the industry as an indication of the potential for
reducing known industry-wide agency problems, then the shareholder wealth effect for rivals
could be positive. The positive price response could impound the future benefits of reduced
agency problems either through other takeovers within the industry or pre-emptive reduction in
agency costs in an effort to thwart future takeovers. In either case, the agency cost reduction
might not be immediate. Even though far off in the future, the prospect of industry-wide
reduction in agency costs could result in stock price improvements.
2.2.3. Increased Probability of Takeover for Rivals
An increased probability of future control bids within the industry could affect stock
prices industry-wide solely due to the premium price at which going-private transactions are
accomplished. For example, in the case of a twenty percent takeover premium, a ten percent
increase in the probability of takeover for rival firms would increase the expected value of
takeover premium by two percent of stock price and lead to a two percent price reaction for rival
firms. Such a price increase for rivals could be observed even if the target’s assets are liquidated
or put to use in another industry.
If the positive stock price reaction for rival firms shown by Slovin, Shushka, and Bendeck
(1991) is due solely to increased probability of takeover bids industry-wide, there should no
evidence of significant upwards earnings forecast revisions for rival firms. Likewise, there should
be little association between the stock price reaction and earnings forecast revisions for rivals. A
9
significant stock price reaction in the absence of significant upwards earnings forecast revisions
for current-year earnings would be consistent with the hypothesis that the price reaction is due to
increased probability of takeover for rivals or the hypothesis that the price reaction is due to
industry-wide reduction in agency problem of free cash flow.
3. Sample Selection and Characteristics of Buyout Target Firms and Industry Rivals
The sample of firms taken private was obtained by searching LEXIS/NEXIS, the Wall
Street Journal Index, Dow Jones News Retrieval Service, Mergerstat Review and the Securities
Data Corp. database for the years 1980-1996. The data represent an update of the sample for
years 1980 to 1987 used by Lehn and Poulsen (1989). To be included in the final sample, the
following screening criteria must be met:
1. The transaction must be confirmed in the Wall Street Journal. The publication date of
the announcement in the Wall Street Journal is used as the announcement day.
2. The announcing firm must have sufficient data in the CRSP database for the
calculation of abnormal stock return surrounding the announcement day.
3. The announcing firm must be followed by security analysts and have sufficient data in
the IBES earnings database to allow calculation of earnings forecast revisions.
4. The announcing firm is not in the utility, real estate, insurance and financial industries.
An initial sample of 353 announcements was verified as having an announcement
published in the Wall Street Journal. This initial sample was reduced to 323 announcements of
going private restructuring with available data in the CRSP database and estimates of currentyear earnings in the IBES database. Each announcement corresponds to a unique firm that is
subject to a going-private bid. Our final sample contains 323 announcements for 323 firms.
10
Table 1 reports the distribution of the sample by year and provides a year-by-year
comparison with the Lehn and Poulsen (1989) sample. It also provides a year-by-year
comparison of firm size for our sample and the Lehn and Poulsen sample. The number of firms
for each year of our sample is about half the number in the Lehn and Poulsen sample. This
smaller number of firms is combined with a larger firm size for our sample, which is about twice
the size of the firms in the Lehn and Poulsen (1989) sample. The larger firm size and smaller
number of firms per year of our sample is due primarily to the requirement that firms in our
sample must be included in the IBES database. Particularly for earlier years of our sample, data
for many smaller firms was not available in IBES.
Our sample is remarkably similar to the sample employed by Kaplan and Stein (1993),
who impose a minimum total transaction value of $100 million. With the similarity to the Kaplan
and Stein (1993) sample comes the implication of their primary finding, that the characteristics of
firms taken private changed significantly between the early years and later years of their sample.
Table 2 presents the distribution of Standard Industrial Classification (SIC) codes for the
sample of target firms. The presence of 55 separate two-digit SIC codes, with 16 of these
representing at least one percent of the sample, indicates a wide variety of industries. A
disproportionately large percentage of the sample is represented by wholesale and retail firms,
which comprise almost 22 percent of the sample.
To develop the sample of intra-industry rivals, we utilize the CRSP daily returns file to
identify all firms in the CRSP file that share the target’s four-digit SIC code. To be included in
the sample of intra-industry rivals, the following five criteria must be met:
1. The firm must remain publicly held throughout the sample period.
11
2. The firm must not be a foreign firm.
3. The firm must not have any major corporate events announced during a period from
three days prior to three days following the target company’s announcement. Major
corporate events include mergers, acquisitions, divestitures, stock repurchases, stock
offerings, and earnings announcements.
4. The firm must have sufficient data in the CRSP database for the calculation of
abnormal stock return surrounding the announcement day.
5. The firm must have sufficient data in the IBES earnings database to allow calculation
of earnings forecast revisions.
Application of these criteria produces a sample of 3,145 rival firms
4. Estimating Abnormal Returns and Abnormal Forecast Revisions
To estimate the stock price reaction to going private announcements, we use the event
study technique. We calculate abnormal returns using the market model, with the CRSP equally
weighted index as a proxy for the market return. We estimate the coefficients of the marketmodel by ordinary least squares regression using an estimation period that begins 345 trading
days before the announcement and ends 90 trading days before the announcement. To test the
statistical significance of abnormal returns, we use the t-test for the mean of the abnormal
returns.
We estimate revisions of earnings forecasts according to the Brous (1992) methodology
to calculate the abnormal forecast revision (AFR), which adjusts for serial correlation in earnings
forecasts and a tendency for successive downward revision of analysts' forecasts in unadjusted
12
forecast revisions (FRs).1
We define FR as the monthly change in the mean of earnings forecasts by analysts,
standardized by stock price per share:
(1)
FRi,t = (Fi,t - Fi,t-1)/Pi
Where FRi,t is the forecast revision of earnings for firm i from month t-1 to month t, Fi,t and Fi,t-1
are the mean values of analysts' earnings forecasts for firm i at months t and t-1, respectively, as
reported in the IBES database. Pi is the stock price for firm i at the end of the month prior to the
announcement of going private restructuring.2
O'Brien (1988) shows that forecast revisions as defined in Equation (1) might be subject
to an optimism bias. Optimistic forecasts at the beginning of the fiscal year are systematically
revised downward as the year progresses. Brous (1992) provides evidence of serial correlation in
earnings forecast revisions that might be due to the fact that not all analysts revise their forecasts
on a monthly basis. Consequently, information released during one month can be reflected in
changes in analysts' earnings forecasts during several subsequent months. Brous and Kini (1993)
report that approximately 20 percent of analysts revise their earnings forecasts each month. This
percentage implies that information will be fully reflected in analysts' forecast revisions during
the four- to five-month period following the announcement.
Since there is the potential for both optimism bias and serial correlation in the forecast
1
A detailed description of this methodology is available in the Appendix provided by Brous and Kini (1994).
2
Christie (1987) presents the theoretical and empirical benefits of normalizing by price per share rather than earnings
per share. Pound (1988) provides an example to demonstrate the merits of normalizing by price per share instead of
earnings per share. This example considers a firm with a stock price of $30 per share. An earnings change from $-0.01
to $0.03 per share would be represented as .04/30 and a change from $0.01 to $0.03 would be represented by .02/30.
Normalizing by price per share maintains the relative importance of these revisions. Normalizing by earnings might not.
13
revisions, we estimate the abnormal forecast revision in a manner consistent with Brous (1992)
to adjust for these two potential problems. Using data for all IBES firms, Brous and Kini (1993)
show evidence that their forecast adjustment process used to determine AFRs induces no new
bias for a random month.
We estimate the abnormal forecast revision for each firm as the difference between the
forecast revision, FR, and the expected forecast revision, E[FR]:
(2)
AFRi,t = FRi,t - E[FRi,t]
We estimate the expected forecast revision for firm i in month t, E[FRi,t], as:
n-1
(3)
E[FRi,t] = ki + (1/n)
e
i,t-c
c=1
The expected forecast revision equals the forecastable component (ki) plus the equally
weighted average of the n previous months' unexpected component. We estimate the forecastable
component, ki, for each company in our sample. We use all months of earnings forecasts in the
IBES database for the company except the 12-month period beginning six months prior to the
going private announcement and ending six months after the announcement. The unforecastable
component, ei,t-c, is equal to the difference between the ki and the actual monthly forecast
revision for firm i in month t-c.
Consistent with Brous (1992), the value of n in Equation (3) is taken as five, which is
equivalent to assuming that analysts' forecasts follow a fourth-order moving average process. A
fourth-order process is consistent with a four-month lag in analysts' revisions.
We estimate cumulative AFRs beginning with the announcement month (month 0),
14
which we define as the first month in which IBES data could partially reflect information
conveyed by the going private announcement. We calculate cumulative AFRs over two-month
(0,1) and four-month (0,3) periods. A four-month (0,3) cumulation period should capture all
revisions associated with an announcement.3
We test the statistical significance of AFRs and cumulative AFRs, using the parametric ttest for the mean of the AFRs and cumulative AFRs and the nonparametric Wilcoxon signedrank test for the median of the AFRs and cumulative AFRs.
5. Results
5.1. Abnormal stock returns for Target Firms and Industry Rivals
Table 3 reports average abnormal stock returns for target firms in Panel A and for
industry rivals in Panel B. The results provide strong evidence of positive and significant
abnormal returns for both target firms and industry rivals during the announcement period. For
targets, the (0,1) announcement interval has a cumulative 2-day return of 12.68 percent, which is
significant at the 0.01 level (t=51.98). Each of the two days within that interval is also significant
at the .01 level. Evidence of significant returns is also shown for the days prior to the
announcement. The abnormal return for the interval beginning 20 days prior to the announcement
and ending 1 day prior to the announcement is 8.63 percent, which is significant at the .01 level
(t=11.02). Combining this pre-announcement interval with the two-day announcement interval
produces a cumulative abnormal stock return of 21.31%. The size of this cumulative return is
similar to that shown in previous studies by DeAngelo, DeAngelo and Rice (1984) and Slovin,
3
The IBES database records analysts' earnings forecasts on the third Thursday of each month. If a forecast is made
after the third Thursday of the month, it is included in the forecasts for the following month. Announcements days are
therefore categorized into IBES months, rather than calendar months.
15
Sushka and Bendeck (1991).
The abnormal return for rivals over the (0,1) announcement interval is 0.33 percent,
which is statistically significant at the .01 level (t=3.01). The abnormal return for rivals for the
interval beginning 20 days prior to the announcement and ending one day prior to the
announcement is 1.57 percent, which is significant at the .01 level (t=4.48). The overall abnormal
return over the entire (-20, +1) event period is 1.91 percent, which is statistically significant at
the .01 level (t=5.18). This cumulative abnormal stock return is about one tenth of the cumulative
average abnormal stock return for target firms shown in Panel A.
Although on a per-firm basis, the reaction for rival is only one-tenth the reaction for
targets, the aggregate effect is almost the same. Based on market values, the aggregate value
effect for the entire sample of rival firms is about $50 billion, compared to an aggregate of $58
billion for the entire sample of target firms.4 The aggregate shareholder gain for rival firms is
about 86% of aggregate shareholder gain for target firms5.
The sample of rival firms also displays some evidence of positive abnormal returns after
the announcement. The cumulative abnormal return of 0.32% over the (+2,+5) postannouncement period is significant (t=1.99, not shown in Table 3), with much of the return due
to a return of 0.18% that is significant at the .05 level (t=2.24) in day +4 alone. None of the other
daily post-announcement returns is significant. A significant post-announcement return could
result either from a lag in the information effect or to some contaminating information for rivals.
4
The aggregate market value for the 323 target firms is $171,949 million, as shown in Table 1. The aggregate
market value of the 3145 rival firms is $2,679,540 million, or more than 10 times larger.
5 Slovin, Shushka and Bendeck (1991) find an aggregate value effect for their sample of rival firms that is about 83
percent of the aggregate value effect for their sample of target firms.
16
5.2. Abnormal Forecast Revisions of Earnings for Target Firms and Industry Rivals
Table 4 presents monthly and cumulative abnormal forecast revisions (AFRs) of currentyear earnings and five-year earnings growth around the announcement of going private
restructuring for target firms in Panel A and for rival firms in Panel B. The table includes results
for the announcement month and each of the three months before and after the announcement.
Panel A provides strong evidence of significant upward abnormal revisions in analysts'
forecasts of current-year earnings for target firms subsequent to going-private announcements.
The average AFR of current-year earnings for the announcement month (Month 0) is positive and
significant at the 0.01 level (t=3.17). For a firm with a price/earnings (P/E) multiple of 13.75,
which is the median P/E for the sample, the AFR of 0.0051 for the announcement month
corresponds to an increase of 7% (=0.0051*100*13.75) in forecasted earnings for that single
month. The cumulative AFR of current-year earnings for the 2-month (0,1) period is also positive
and significant at the 0.01 level (t=2.41). The cumulative AFR for the 4-month (0,3) period,
however, is positive, but not statistically significant (t=1.59).
For each of the three months immediately preceding the announcement, the AFR is not
significant. Month –3 has a positive, but insignificant AFR, and Months –2 and –1 have negative
and insignificant AFRs. Whereas stock price behavior shown in Table 3 provides evidence of
information leakage prior to the announcement, earnings forecast behavior does not. Either
analysts are not aware of an impending going-private transaction prior to its announcement or
they refrain from employing private information to update earnings forecasts until the
information is made public.
Once the impending going-private announcement is made public, however, analysts react
17
quickly with revisions of earnings forecasts. Virtually all of the four-month (0,3) AFR and the
two-month (0,1) AFR is provided by revisions during month 0. The AFR for Month 1 is positive,
but not significantly different from zero. The AFRs for Months 2 and 3 are also not significant.6
This concentration of the AFR in the month immediately after the announcement is unusual.
Typically, only about 20 percent of analyst forecasts are updated in any single month, according
to Brous and Kini (1993), which would result in announcement effects spread out over several
months. For going-private transactions, however, the transaction is often executed within a
month or two after the bid announcement. Analysts are unlikely to prepare forecast revisions for
companies that are no longer publicly traded. Consequently, earnings forecast revisions are
unlikely after the company has been taken private.
Panel A of Table 4 also contains monthly and cumulative AFRs of five-year earnings
growth rates for target firms around the announcement of going private restructuring. The results
in this table do not provide evidence of significant revisions of long-term earnings by analysts.
None of the months examined, from three months before to three months following the
announcement month, shows significant revisions, either positive or negative.
Finding significant revision of current-year earnings but not of five-year earnings growth
is common in other studies of information effects on earnings expectations [e.g. Brous (1992),
Gombola and Liu (1999)]. In the specific instance of going-private transaction, the question of
five-year earnings growth may become moot if the company is not expected to remain public
over the forecasting period. If analyst earnings forecasts are provided in response to investor
interest, then a lack of investor interest in earnings growth of companies becoming private could
6
We also extend the examination of AFRs to Months 4, 5, and 6. There is no evidence of significant forecast
revisions of either current-year earnings or five-year earnings growth for these months. Results for theses months are
not shown in Table 4 but are available from the authors.
18
limit the interest of analyst in providing such forecasts. Consequently, we would be reluctant to
conclude from the results shown in Table 4 that only current-year earnings forecasts and not fiveyear growth estimates are affected by information released in going-private announcements.
Panel B of Table 4 presents abnormal forecast revisions for industry rival firms for the
announcement month as well as three months before the announcement to three months after the
announcement. The current-year earnings AFR for the announcement month (Month 0) is
positive and significant at the 0.05 level (t=2.01). Likewise, the AFR for the following month
(Month 1) is also positive and significant at the 0.05 level (t=2.14). The following two months (2
and 3) also show positive AFRs, but the revision is not significant. The cumulative AFR of
current-year earnings for the 2-month (0,1) period is also positive and significant at the 0.01 level
(t=3.00), as is the AFR for the four-month (0,3) interval (t=3.21).7
Results shown in Table 4 for current-year AFRs of industry rival firms differ from those
for target firms in the time and the size response to the announcement. For target firms, analysts
appear to revise earnings forecasts immediately upon the announcement. For rival firms, the
response is not immediate. Instead, analysts might wait until a regular quarterly update before
revising earnings forecasts.
The abnormal forecast revisions for target firms are about ten times as large as those for
rival firms. For example, the two-month AFR for target firms is 0.007 as compared to a value of
0.0007 for rival firms. For a rival firm with a P/E of 14.91, which is the median P/E for the rival
sample, there is an increase of 1.04% (=0.0007*100*14.91) in forecasted earnings for the two-
7
We also extend the examination of AFRs to Months 4, 5, and 6. We find some evidence of upward forecast
revisions of current-year earnings for Month 5. There is no evidence of upward forecast revisions of five-year
earnings growth for any of these months. Results for theses months are not shown in Table 4 but are available from
the authors.
19
month (0,1) interval. For a target firm with a P/E of 13.75, which is the median P/E for the target
sample, there is an increase of 9.8% (=0.00716*100*13.75) in forecasted earnings for the twomonth (0,1) interval. The disparity in size of earnings forecast revisions, which differs by a factor
of ten between targets and rivals is consistent with the difference in size of the abnormal stock
returns between target firms and their industry rivals, which also differs by a factor of ten, as
shown in Table 3. Since the number of rival firms exceeds the number of targets by a factor of
ten, the aggregate change in earnings forecasts for rivals approaches the change for targets. .
Panel B of Table 4 also presents monthly and cumulative AFRs of five-year earnings
growth rates for rival firms. The AFR for the announcement month is significant at the 0.10 level
(t=1.76). The cumulative forecast revision for the two-month (0,1) interval including the
announcement month and the following month is positive and significant at the .01 level
(t=2.60). Evidence of significant upward revision in long-term earnings growth estimates for
rival firms is particularly notable since parallel results are not observed for target firms. One
explanation we can provide for this difference is that analysts no longer provide estimates of
long-term growth for firms to be taken private. For their industry rivals, however, the question of
long-term earnings growth is not moot, but is met by analysts.
5.3. Regression Analyses for Target Firms
Support for the hypothesis that going-private announcements convey favorable
information about future earnings of targets requires a positive association between earnings
forecast revisions and the stock price reaction to the announcement of a going-private
announcement. Tables 3 and 4 show a positive stock price reaction and upward revision of
earnings forecasts for target firms, but not the necessary relation between the two. In this section
we present results of regression analyses examining the relation between earnings forecast
20
revisions and stock price reaction to a going-private announcement for target firms while
controlling for contaminating effects on either variable.
The significant positive stock price reaction for target firms and the significant positive
earnings forecast revisions for target firms could both result from ancillary financing effects of a
going-private transaction. The debt employed to finance many going-private transactions could
simultaneously increase both the stock price and expected future earnings per share. For a
profitable firm, substitution of debt for equity could increase earnings per share even if operating
earnings do not improve.8 The increased leverage could also produce tax savings, as Kaplan
(1989) explains.
To untangle the relation between leverage, earnings, and share price, we examine the
leverage change for each going-private transaction and later include this measure as a control
variable in the regression analyses. Table 5 presents the leverage (measured by the ratio of debt
to assets) of firms taken private for each year from 3 years prior to the going-private
announcement to three years following the announcement. This year-by-year change in financial
leverage is presented in Panel A for all firms in the sample and in Panel B for the set of 65 firms
with available data for every year during the seven-year period.
The full sample shows a slight decrease in leverage for the years immediately prior to the
going-private announcement, followed by a moderate increase for the years following the
announcement. A similar pattern is shown by the smaller sample of 65 firms. In either case, the
leverage ratio increases from about 50% in the announcement year to about 65% for the third
year following the announcement. Most of this increase occurs during the year immediately
following the announcement. The changes are not significantly different from zero at any
8
The increase in EPS would not necessarily increase share price since a risk increase accompanies the earnings
21
standard level of significance for either sample.
Somewhat notable is the tendency of firms taken private to maintain higher levels of debt
years after the transaction. Although the reputation for leveraged transactions is that the new
owners attempt to unwind the leverage as quickly as possible, the process for firms in our sample
appears quite slow. One explanation for this behavior follows from the analysis of tax benefits of
debt by Graham (2000). Once debt is added in the going-private process, previously underleveraged firms could become comfortable at the new higher level of debt as they enjoy greater
tax advantages. Another explanation is that the firm, although intending to reduce debt after the
transaction is unable to reduce debt as quickly as desired. In either case, the increase in debt is
more than just transitory.
In addition to leverage changes, the firm’s free cash flow position could also affect the
results shown for stock price reaction and earnings forecast revisions for target firms. Firms with
severe agency problems of free cash flow could enjoy both an increase in share value and an
increase in earnings if the agency problems are reduced or eliminated by a new management team
once the firm is taken private. Greater free cash flow and greater agency problems would allow
greater opportunity to reduce these agency problems and increase earnings and share price. The
opportunity to reduce agency problems of free cash flow should be reflected immediately in the
stock price reaction to a going-private announcement. The stock price reaction is primarily due to
the premium paid in order to take the firm private. This premium paid should impound any
benefits of reduction in agency problems of free cash flow anticipated by the buyer group. The
reduction in agency problems may not be reflected in increased earnings until long after the firm
becomes private.
increase.
22
Examining the association between earnings forecast revisions and the stock price
reaction in a regression model is further complicated by measurement problems for these two
variables. First, the measurement period for stock return effect differs from the measurement
period for forecast revisions, with the latter extending over at least a month. Second, earnings
forecast revisions are much more susceptible to information contamination than are stock price
changes. The danger of information contamination for stock returns is limited to information
released during the short announcement period for measuring stock price effect. Because
earnings forecasts are not immediately updated, an information release may not be captured in
earnings forecast revisions until months after the announcement. Consequently, the observed
abnormal forecast revisions, such as shown in Table 4, could be contaminated by effects of
information released outside of the announcement period for measuring stock returns but within
the period for measuring earnings forecast revisions.
To control for the contaminating effect of prior information releases on earnings forecast
revisions, previous studies [e.g. Hertzel and Jain (1991) and Gombola and Liu (1999)] employ
cumulative abnormal stock returns outside of the abnormal return event period in examining the
association between earnings forecast revisions and market reaction. Information effects revealed
outside the abnormal return period that could contaminate the forecast revision are then captured
in these abnormal returns.
The information effect could also depend upon the identity of the acquirer. Slovin,
Shushka, and Bendeck (1991), while noting that this effect on prices is an empirical question,
demonstrate a significantly greater price reaction for targets acquired by groups including a
buyout specialist than for management-led buyout teams.
The resulting regression model then can be expressed as:
23
(4)
AFRi = b0 + b1ARi + b2CH_DEBTi + b3CFLOWi + b4PAARi + b5MBO + b6SIZE + ei
Where AFRi is the abnormal earnings forecast revision for target firm I for the two-month (0,1)
interval, ARi is the cumulative abnormal return for firm i during the 22 day, (-20, +1), interval,
CH_DEBTi is the change in leverage between three years prior to and three years following the
announcement for firm i, as shown in Table 5. CFLOWi is the ratio of cash flow to assets for the
year immediately prior to the going-private announcement for firm i. It is constructed according
to the definition of free cash flow employed by Lehn and Poulsen (1989) and Lang, Stulz and
Walkling (1991), using data from the annual Compustat files. PAARi is the pre-announcement
cumulative abnormal return for firm i during the (-91, -21) day interval. MBOi is a dummy
variable that takes a value of one if the buyout team for the ith target firm is management-led,
and zero otherwise. SIZEi is the natural logarithm of equity market value for the ith target firm,
the product of shares outstanding and closing price per share for the announcement month.
Table 6 contains the results of estimating Equation (4) using two alternative
specifications of the dependent variable. In the first specification, shown in Panel A, AFR shown
is for current-year earnings. In the second specification, shown in Panel B, AFR shown is for
five-year earnings growth. The results in Panel A show that the relation between AFR for
current-year earnings and announcement-period abnormal return (AR) is positive and significant
at the 0.01 level (t=2.72). This result is consistent with the prediction of the information
hypothesis.
The coefficient for the variable representing the change in debt (CH_DEBT) is not
statistically significant. Also, the coefficient is negative, which is opposite to the predictions of
the tax benefit hypothesis. The sign for the variable representing free cash flow (CFLOW) is also
negative, but is significant. The free cash flow hypothesis predicts a positive relation between
24
free cash flow and future earnings improvement, which is opposite to the observed sign.
The coefficient for pre-announcement abnormal stock return (PAAR) is significant and
negatively related to the AFR for current-year earnings. A possible explanation for the negative
sing is that greater market underperformance prior to the announcement is reversed by the
announcement. It is consistent with a reversal in investor expectations about the future prospects
of the firm to be taken private.
The coefficient for dummy variable representing the presence of a management-led
takeover (MBO) is negative and significant at the .05 level (t=-2.10). This result indicates that
upwards revisions of earnings forecasts are smaller for management buyouts that for buyouts by
outsiders. Analysts might be able to understand the intentions of outsiders in a going-private
transaction, whereas intentions of management-led groups could be less transparent. The
coefficient for firm size (SIZE) is also negative and significant(t=-2.34). The significance
underscores the need to incorporate this control variable in studies of earnings forecast revisions,
just as in event studies.
The results shown in Panel B of Table 6 show little relation between AFR for five-year
earnings growth and any of the independent variables. The relation between abnormal stock
return and AFR for five-year earnings growth is not statistically significant (t=-0.55). This lack of
statistical significance is not surprising in light of the insignificant revisions of five-year earnings
growth forecasts, shown in Table 4. Two possible explanations might underlie these findings.
First, the results could indicate that the favorable information conveyed at the going private
announcements concerns only transitory, but not permanent, changes in earnings. Secondly, the
lack of significant revisions in long-term earnings growth forecasts might stem from limited
incentive for analysts to generate such forecasts for firms that are about to become private.
25
An alternative examination of the relation between earnings forecasts revisions and the
stock price effect can be performed with the forecast revisions employed as an independent
variable to explain the stock price reaction as the dependent variable. The resulting regression
model becomes an examination of the relation between abnormal returns and earnings forecast
revisions, which tests the information hypothesis, while controlling for free cash flow and debt
change. These two variables serve as proxies for testing effects of the free cash flow hypothesis
and tax benefit hypothesis. This alternative regression model then can be expressed as:
(5)
ARi = b0 + b1AFRi + b2CH_DEBTi + b3CFLOWi + b4PAARi + b5MBOi + b6SIZEi + ei
Although all variables are as previously defined in Equation (4), interpretation of the independent
variables changes. The pre-announcement abnormal return, (PAAR) instead of serving as a
means to control for information contamination in the dependent variable, becomes a measure of
prior stock price “run-up”.9 The model is estimated alternately with AFR for current-year
earnings forecasts and then as AFR for five-year growth forecasts.
Table 7 contains the results of cross-sectional regressions expressed in Equation (5). The
results shown in Model 1, indicate that the relation between AFR for current-year earnings and
AR is positive and significant at the 0.01 level (t=2.72). This result confirms the finding in Table
6 of a positive relation between AFR and AR and is consistent with the information hypothesis.
The relation does not extend to five-year earnings growth forecasts shown in Model 2. Neither
the variable representing free cash flow (CFLOW) nor the variable representing the impact of
potential tax savings (CH_DEBT) significantly adds to the explanation of abnormal stock return.
Neither is significant in either model. The variable measuring pre-announcement price run-up
9
Similar measures of “run-up” have been employed in other studies of information effects, such as the examination
of the price effects of stock offering announcements by Comment and Jarrell (1991).
26
(PAAR) is significantly related to AR in Model 1, suggesting some information leakage prior to
the announcement.
The coefficient for the dummy representing presence of a management buyout (MBO) is
positive and significant at the .05 level (t=2.52) for Model 1 and significant at the .10 level
(t=1.75) for Model 2. These results are consistent with the findings of Slovin, Shushka and
Bendeck (1991) who also find that management-led buyouts are associated with higher abnormal
returns in response to going-private announcements.
The difference in sign for MBO between results in Table 6 and results in Table 7 should
not be disconcerting. A management-led buyout can be associated with higher abnormal stock
returns, but not necessarily higher earnings forecast revisions than a buyout by outsiders. The
abnormal stock return from a buyout announcement is primarily due to the premium offered by
the takeover group. A management-led group may be confident in offering a higher premium
over the previous market price for the same level of earnings, or earnings improvement.
Results for target firms shown in Tables 6 and 7 provide strong evidence of a significant
and positive relation between the earnings forecast revisions for current-year earnings for firms
subject to going-private bids and the stock price reaction to the announcement. This result is
consistent with the hypothesis that going-private announcements convey information about
earnings prospects for targets of going-private bids. There is very little evidence that changes in
debt or the free cash flow position of targets firms is related to either improvement in earnings
forecasts or increases in shareholder wealth associated with the going-private announcement.
5.4. Regression Analyses for Rival Firms
Testing for an intra-industry information transfer for rival firms requires examining the
27
association between earnings forecast revisions for rival firms and their stock price reaction to a
going-private bid within the same industry. A positive association between earnings forecast
revisions and the stock price reaction for industry rivals would provide support for the hypothesis
that going-private announcements contain industry-wide favorable information about future
earnings prospects. This section presents results of testing this association in a regression model.
Controlling for cash flow effects and change in leverage is necessary in examining the
relation between earnings forecast revisions and stock price reaction in a regression model for
rivals, just as for targets. To the extent that agency problems of free cash flow are industry-wide,
a going-private transaction could motivate managers of rival firms to improve earnings
performance in an effort to thwart potential future takeover bids. Managers could also try to
improve earnings through increasing leverage to take advantage of tax benefits and improve
earnings per share. Levering up the firm would also further protect against unwanted goingprivate bids by reducing the attractiveness as a takeover target. The lower the rival’s debt, the
greater is the opportunity to increase leverage and tax benefits.
Since the intra-industry information transfer from targets to industry rivals should be
greater for more prominent targets in the industry, we also include a measure of relative firm size
between target firms and rival firms in the regression models. According to the intra-industry
information transfer hypothesis, we should expect a greater effect on earnings for a target firm
larger than its corresponding rival.
The information transfer effect could also depend upon the identity of the acquirer.
Slovin, Shushka, and Bendeck (1991) and our results shown previously in Table 7 demonstrate a
significantly greater price reaction for targets acquired by management-led buyout teams than
outsiders. The effect of the identity of the acquirer on information transferred to rival firms is
28
uncertain. If management-led teams have access to superior information about industry prospects
than outsiders, a greater earnings forecast revision for rivals should be observed. Alternatively,
management-led going-private transactions could be based more on company-specific
information whereas investor-led transactions could be based on valuations within an industry
and less on company-specific characteristics. Consequently, the effect of this variable is an
empirical question.
Similar to targets, the pre-announcement stock return, or price “run-up” can be used to
control for announcements prior to the stock return announcement period. In addition, for rivals,
the post-announcement stock return can be used to control for events after the announcement
period that could be reflected in earnings forecast revisions but not in the announcement-period
return. In the case of targets, controlling for post-announcement events is unnecessary since the
company has been taken private quickly.
The resulting regression model is:
(6)
AFRi = b0+ b1ARi + b2CFLOWi + b3DEBTi + b4RELSIZEi + b5MBOi + b6PAARi +
b7PSARi + ei
where AFRi , ARi , CFLOWi, PAARi and MBOi are as defined previously for target firms, but
constructed for the sample of rival firms. DEBTi is the ratio of debt to assets for the ith rival
firm, taken from COMPUSTAT for the year immediately prior to the going-private
announcement, RELSIZEi is a dummy variable that takes a value of one if the target is larger
than the ith rival firm, and zero otherwise, and PSARi is the post-announcement abnormal return
for the ith rival firm during the +2, +90) day period.
Table 8 presents results of estimating the regression model expressed in Equation (6).
29
Model 1, constructed for AFRs for current-year earnings, shows evidence of a positive and
significant (t=3.98) relation between the AFR and the AR for industry rival firms. The highly
significant association between AFR and AR provides very strong support for the hypothesis that
the market reaction for rivals is due to favorable information about their earnings prospects.
Neither the proxy for free cash flow (CFLOW) nor the proxy for tax benefits of unused debt
capacity (DEBT) are statistically significant in this model. The measure of relative size
(RELSIZE) is positive and statistically significant at the 0.01 level (t=2.56). This result indicates
that larger size of targets is associated with a greater earnings forecast revision for rivals.
Information about larger firms should have greater industry-wide information effects.
The coefficient for the dummy variable for management-led buyouts (MBO) is not
significant at any conventional level. Also, neither the coefficient for pre-announcement
abnormal return (PAAR) nor post-announcement abnormal return (PSAR) is statistically
significant. The sign of the PAAR variable is opposite to one that would indicate information
contamination.
In Model 2, the relation between AFR for 5-year growth rates and AR for industry rival
firms is positive, but significant only at the 0.10 level. There is no evidence of a relation between
the AFR for 5-year growth rates and either the pre-announcement abnormal return (PAAR)or
post-announcement abnormal return (PSAR).
The regression model presented in Equation (6) allows considerable control for
confounding effects on earnings forecast revisions, but provides little inference about abnormal
returns since abnormal returns are used only as an independent variable. In order to allow
inference about abnormal returns, an alternative examination of the relation between abnormal
returns and earnings forecast revisions for rivals can be performed by employing earnings
30
forecast revisions as an independent variable and abnormal stock returns as the dependent
variable. With market reaction as the dependent variable, a regression model can be built that
incorporates alternative explanations for the stock price reaction for rival firms.
Slovin, Shushka and Bendeck (1991) point out that the positive stock price reaction for
rivals could result from: (1) buyout bids may reveal private information about the future cash
flows of target firms and their intra-industry rivals (2) buyout bids could produce an increase in
the probability that rival firms may become the target of future control bids and (3) buyout bids
could be an indicator of industry-wide agency problems subject to reduction either by current
management or by new management after a successful buyout bid.
Earnings forecasts can serve as a proxy for the future cash flows of inter-industry rivals,
the probability that rival firms could become targets of future control bids can be proxied by the
rival firm’s debt and cash flow position. Firms with less debt can support greater takeover
financing in a going-private transaction and are more likely to be future targets of going-private
bids. Firms with greater cash flow can also support greater takeover financing and are also more
likely to become future targets. In addition to serving as a proxy for probability of takeover, cash
flow serves as a direct measure of the agency problems of free cash flow. The greater the cash
flow of rivals, the greater are the potential benefits of their reduction.
Incorporating measures for the identity of the buyer (management vs. outsider) and preannouncement stock return, the regression model becomes:
(7)
ARi = b0 + b1AFRi + b2CFLOWi + b3DEBTi + b4MBOi + b5PAARi + ei
Where all of the variables are as defined for Equation (6). The regression model does not include
the variable for relative firm size of targets and rivals (RELSIZE). Relative firm size is
31
significantly related to AFRs for rivals, as shown in Table 8. The inclusion of this variable would
induce multicollinearity in the model.
Table 9 reports results of estimating the regression model expressed in Equation (7).
Model 1, which incorporates current-year earnings as an independent variable, shows a positive
relation that is significant at the 0.01 level (t=3.77) between AFR and abnormal return (AR) for
rival firms. This level of significance is very similar to that found when AFR for the current-year
earnings is employed as the dependent variable shown in Table 8, indicating robustness of the
association between AFR for current –year earnings and AR for rival firms. Also similar to table
8, neither the proxy for free cash flow (CFLOW) nor the proxy for tax benefits of unused debt
capacity (DEBT) is statistically significant in this model.
There is some weak evidence (significant at the 0.10 level) of greater intra-industry
information transfer for investor-led buyout bids than management-led bids. This result could be
due to management-led bids implying more company-specific information on the target firm’s
value whereas outsider-led bids imply industry-wide information. Pre-announcement abnormal
return (PAAR) is significantly related to the abnormal return for rivals.
The relation between AFR for 5-year growth rates and AR for industrial rivals, shown in
Model 2 in Table 9, is positive, but significant only at the 0.10 level. Also significant at the 0.10
level is the relation between the bidder’s identity (MBO) and AR in this model. Model 2 also
shows a highly significant relation between pre-announcement abnormal return (PAAR) and
announcement-period abnormal return (AR) for rivals.
Results shown in Table 9 provide support for the hypothesis that the positive market
reaction to going-private announcements observed for industry rivals is due to inter-industry
32
information transfer about future earnings prospects for target firms and their inter-industry
rivals. This hypothesis is the first of the three hypotheses presented by Slovin, Shushka and
Bendeck (1991) to explain the positive abnormal returns of rival firms to a going-private
announcement. There is no evidence that the rival’s abnormal return is related to its free cash
flow position or its leverage and therefore no support for the other two hypotheses.
6. Conclusions
This study provides direct evidence supporting the hypothesis that going-private
announcements convey favorable information about future earnings prospects not only for target
firms but also for industry rivals. It documents a significant upward revision in analysts' forecasts
of current-year earnings subsequent to an announcement of going private restructuring for target
firms and for industry rivals. It also documents a significantly positive relation between revisions
of analysts' forecasts of current-year earnings and the abnormal stock return associated with the
going private announcement for target firms and for industry rivals. This relation remains even
after controlling for leverage changes and free cash flow. There is also some evidence of upward
revisions in analyst forecasts of five-year earning growth for rival firms and some evidence of a
positive relation between these revisions and the abnormal stock return for industry rivals. There
is little evidence that the upward revisions of analysts' earnings forecasts or the positive stock
price reaction can be attributed to either free cash flow or potential tax benefits of increased
leverage for target firms. Likewise, neither the upward revision of analysts’ earnings forecasts
nor the positive stock price reaction is related to the cash flow or leverage position of rival firms.
33
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35
Table 1
Characteristics of the Going-Private Sample
The sample includes 323 going private announcements for the period from 1980 to 1996.
Equity values are computed as the product of common shares outstanding and the closing
price of common stock at the end of fiscal year immediately preceding the calendar year of
the announcement date.
Year
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
Lehn & Poulsen
(1989)
Mean
Number of Equity
firms
Value
($mil)
15
33.1
21
87.8
27
79.1
35
115.4
48
173.9
36
371.7
39
285.9
42
224.3
1980-1987 263
1988-1996
Full
sample
193.2
Our Sample
5
8
13
17
25
22
22
26
32
19
26
10
9
9
20
27
33
Mean
Equity
Value
($mil)
94.1
172.4
130.3
187.9
342.6
770.4
682.3
397.9
373.8
653.3
1277.9
262.9
110.6
215.9
340.5
1173.2
384.4
Median
Equity
Value
($mil)
110.5
117.9
88.1
115.8
321.5
339.7
196.7
164.7
183.1
273.1
154.8
57.7
47.4
68.8
101.4
118.8
108.4
Total
Standard Equity
Deviation Value
($mil)
56.8
470.4
179.0
1379.4
84.8
1693.3
236.2
3195.4
313.7
8565.4
1221.3
16949.8
1108.0
15011.2
558.5
10346.5
591.9
11960.1
971.7
12412.8
1277.8
33224.0
486.1
2629.1
139.5
995.4
215.9
1943.0
609.4
6810.8
4072.7
31677.6
719.2
12685.7
138
185
323
417.5
618.0
532.4
171.0
128.3
140.6
744.3
1866.7
1495.6
Number
of Firms
36
57611.5
114338.4
171949.9
Table 2
Distribution of the Standard Industrial Classification (SIC) code for the Going-Private
Sample
This table shows the distribution of the SIC code for the going-private sample. The presence of
fifty-five separate two-digits SIC codes, with sixteen of these representing at least 1% of the
sample (thirty-four going-private), indicates a wide selection of industries.
Industry
Food Products
Chemical products
Electronic Equipment
Scientific Instruments
Communications
Eating and Drinking Establishments
Health
Fabric and Clothes
Paper and Paper Products
Manufacturing
Computer Hardware and Software
Transportation
Wholesale and Retail
SIC Missing
All Others
Two-Digit SIC Code
20
28
36
38
48
58
80
22,23
24,25,26,27
30,31,32,33,34
35,73
37,39,40,42,45
50,51,52,53,54,56,57,59
13,15,16,17,21,47,55,70,75,
78,79,82,83,87,89,95,322
Total
Number of
Firms
19
16
13
11
11
11
11
15
17
33
33
27
70
2
35
323
37
Percentage
5.88
4.95
4.02
3.41
3.41
3.41
3.41
4.64
5.26
10.22
10.22
8.36
21.67
0.62
10.84
100.00
Table 3
Average Abnormal Stock Returns Surrounding Going-Private Announcements
for the Going-Private Sample
We estimate average abnormal returns based on the market model around the
announcement day (Day 0) of going private. The market model is estimated over the
(-345, -91) period. The going-private sample includes 323 going private
announcements for the period from 1980 to 1996.
Panel A: Target Firms
Panel B: Rival Firms
Day(s)
Abnormal Return (%) t-statistic
Abnormal Return (%) t-statistic
-20
0.28
1.68
0.11
1.35
-19
0.02
0.15
0.21***
2.73
-18
0.06
0.36
0.02
0.25
-17
0.13
0.8
0.05
0.68
-16
0.61***
3.61
-0.05
-0.64
-15
0.50***
2.99
-0.04
-0.51
-14
0.09
0.57
-0.01
-0.07
-13
0.13
0.76
0.21***
2.66
-12
0.30
1.77
0.04
0.49
-11
0.29
1.71
0.00
0.00
-10
0.11
0.63
0.21***
2.66
-9
0.24
1.42
0.15*
1.86
-8
0.18
1.06
0.26***
3.25
-7
0.35**
2.10
0.29***
3.67
-6
0.57***
3.41
0.01
0.16
-5
0.78***
4.66
0.10
1.22
-4
0.03
0.18
0.08
1.04
-3
0.31
1.88
0.13*
1.65
-2
0.81***
4.86
-0.01
-0.10
-1
2.84***
16.96
-0.18***
-2.30
0
9.94***
59.32
0.14*
1.79
1
2.74***
16.34
0.19***
2.46
2
0.21
1.28
0.10
1.23
3
-0.07
-0.39
0.00
0.06
4
-0.01
-0.05
0.18**
2.24
5
0.01
0.03
0.04
0.45
(0,1)
12.68***
51.98
0.33***
3.01
(-20, -1)
8.63***
11.02
1.57***
4.48
(-20, +1) 21.31***
35.07
1.91***
5.18
*Significant at the 0.1 level.
**Significant at the 0.05 level.
***Significant at the 0.01 level.
38
Table 4
Average Adjusted Forecast Revisions of Current-Year Earnings and Five-Tear Earnings Growth
Rates for Months Surrounding Going-Private Announcements for the Going-Private Sample
We define the forecast revision for Month t as the mean of analysts’ forecasts reported in the IBES database
in Month t less the mean of analysts’ forecasts in Month t-1, scaled by stock price at the end of the month
preceding the going private announcement. We define the adjusted forecast revision for Month t as the scaled
forecast revision for Month t less the expected forecast revision for Month t, which is estimated based on a
fourth-order moving average expectations model. The t-statistic tests the null hypothesis that the mean
earnings forecast revision differs from 0. The sample includes 323 announcements of going-private
restructuring.
Panel A: Adjusted forecast revisions (AFR) for target firms
Forecast
Month
-3
-2
-1
0
1
2
3
Cumulative forecast windows:
0 to 1
0 to 3
AFR for Current-Year Earnings
AFR for 5-Year Earnings Growth
Adjusted
Forecast
Revisions
-0.00204
-0.00439
0.00061
0.00512***
0.00275
-0.00043
-0.00036
t-test
statistic
t-test
statistic
-0.73
-0.97
0.35
3.17
1.53
-0.52
-0.44
Adjusted
Forecast
Revision
-0.01025
0.01434
-0.00656
-0.00621
-0.00293
-0.00353
-0.00442
0.00716**
0.00509
2.41
1.59
-0.00944
-0.01518
-0.81
-0.82
-1.76
1.83
-1.03
-0.96
-0.38
-0.44
-0.52
Panel B: Adjusted forecast revisions (AFR) for rival firms
-3
-2
-1
0
1
2
3
Cumulative forecast windows:
0 to 1
0 to 3
*Significant at the 0.1 level.
**Significant at the 0.05 level.
***Significant at the 0.01 level.
-0.0003
-0.0002
-0.0000
0.0003**
0.0004**
0.0001
0.0003*
-1.64
-0.87
-0.05
2.01
2.14
0.94
1.87
0.0042
-0.0021
-0.0007
0.0085*
-0.0016
-0.0055
-0.0044
0.80
-0.41
-0.17
1.76
-0.12
-0.84
-0.82
0.0007***
0.0010***
3.00
3.21
0.0161***
0.0057
2.59
0.72
39
Table 5
Ratio of Total Debt to Total Assets for Years Surrounding Going Private for the
Going-Private Sample
This table reports the ratio of total debt to total assets for Year -3 through Year +3. The
ratio is calculated as total debt divided by total assets and then multiplied by 100. Data for
total debt and total assets is obtained from the COMPUSTAT files. Year 0 is the year of
the going-private announcement.
Year
Mean (%)
Standard
Deviation (%)
Number of Firms
46.34
43.28
42.56
48.16
60.49
63.20
66.09
22.35
20.71
20.88
26.71
28.91
30.28
32.18
201
211
213
143
102
92
77
22.28
21.61
21.96
26.73
27.53
28.18
31.60
65
65
65
65
65
65
65
Panel A: All Available Firms
-3
-2
-1
0
1
2
3
Panel B: Firms with data for all years
-3
-2
-1
0
1
2
3
47.80
45.38
44.77
51.71
60.43
63.35
64.93
40
Table 6
Cross-Sectional Regressions of Abnormal Forecast Revisions of Earnings Surrounding the
Going-Private Announcement for the Going-Private Sample
AFRi = b0 +b1ARi +b2 CH_DEBTi +b3CFLOWi +b4PAARi +b5MBOi +b6SIZEi +ei
Where AFR is the cumulative adjusted forecast revisions of current-year earnings per share and
5-year earnings growth rates for the 2-month (0,1) period for Models 1 and 2, respectively, AR
is the announcement-period abnormal return, as measured by the cumulative average abnormal
return for the (-20,1) window based on the market model, CH_DEBT is the change in total debt
to total asset ratio from year-3 to year +3, CFLOW is the ratio of free cash flow to assets for the
year immediately preceding the going-private transaction, PAAR is the pre-announcement
abnormal return, as measured by the cumulative average abnormal return for the (-90,-21)
period based on the market model, MBO is a dummy variable that takes a value of one if the
buyout team for the target firm is led by management, otherwise zero, and SIZE is natural
logarithm of the market value of equity. The t-statistics appear in parentheses.
Independent Variables
Intercept
AR
CH_DEBT
CFLOW
PAAR
MBO
SIZE
F-Statistic
N
R-Square
Model 1:
Current-Year AFR
as Dependent Variable
0.244***
(2.87)
0.177***
(2.72)
-0.035
(-1.05)
-0.298***
(-3.73)
-0.133***
(-2.99)
-0.052**
(-2.10)
-0.015**
(-2.34)
6.93***
65
0.41
*Significant at the 0.1 level.
**Significant at the 0.05 level.
***Significant at the 0.01 level.
41
Model 2:
Five-Year AFR
as Dependent Variable
0.017
(0.09)
-0.083
(-0.55)
0.045
(0.61)
-0.216
(-1.08)
-0.072
(-0.70)
0.035
(0.62)
0.000
(0.02)
0.66
54
0.08
Table 7
Cross-Sectional Regressions of Announcement-Period Abnormal Stock Return for the
Going-Private Sample
ARi = b0 +b1AFRi +b2 CH_DEBTi +b3CFLOWi +b4PAARi +b5MBOi +B6SIZEi +ei
Where AR is the announcement-period abnormal return, as measured by the cumulative average
abnormal return for the (-20,1) window based on the market model, AFR is the cumulative
adjusted forecast revisions of current-year earnings per share and 5-year earnings growth rates
for the 2-month (0,1) period for Models 1 and 2, respectively, CH_DEBT is the change in total
debt to total asset ratio from year-3 to year +3, CFLOW is the ratio of free cash flow to assets
for the year immediately preceding the going-private transaction, PAAR is the preannouncement abnormal return, as measured by the cumulative average abnormal return for the
(-90,-21) day period based on the market model, MBO is a dummy variable that takes a value of
one if the buyout team for the target firm is led by management, otherwise zero, and SIZE is
natural logarithm of the market value of equity. The t-statistics appear in parentheses.
Independent Variables
Intercept
AFR
(Current-Year or Five-Year)
CH_DEBT
CFLOW
PAAR
MBO
SIZE
F-Statistic
N
R-Square
Model 1:
Current-Year AFR
as Independent Variable
-0.051
(-0.30)
0.631***
(2.72)
0.057
(0.90)
0.139
(0.83)
0.253***
(3.02)
0.115**
(2.52)
0.010
(0.79)
3.10***
65
0.24
*Significant at the 0.1 level.
**Significant at the 0.05 level.
***Significant at the 0.01 level.
42
Model 2:
Five-Year AFR
as Independent Variable
0.135
(0.74)
-0.072
(-0.52)
0.076
(1.12)
-0.080
(-0.42)
0.150
(1.56)
0.088*
(1.75)
-0.002
(-0.12)
1.45
56
0.15
Table 8
Cross-Sectional Regressions of Abnormal Forecast Revisions of Earnings Surrounding the
Going-Private Announcement for the Sample of Industry Rivals
AFRi = b0+b1ARi+b2CFLOWi+b3DEBTi+b4RELSIZEi+b5MBOi+b6PAARi +b7PSARi+ei
Where AFR is the cumulative adjusted forecast revisions of current-year earnings per share and
5-year earnings growth rates for the 2-month (0,1) period for Models 1 and 2, respectively, AR is
the cumulative average abnormal return for the (-20,1) window based on the market model,
CFLOW is the ratio of free cash flow to assets for the year immediately preceding the goingprivate transaction, DEBT is total debt over total assets for the year immediately preceding the
announcement, RELSIZE is a dummy variable that takes a value of one if the target is larger than
the rival firm in market value of equity, and zero otherwise, MBO is a dummy variable that takes
a value of one if the buyout team for the target firm is led by management, otherwise zero,
PAAR is the cumulative average abnormal return for the (-90,-21) day period based on the
market model, and PSAR is the cumulative average abnormal return for the (+2, +90) day period
based on the market model. The t-statistics appear in parentheses.
Independent
Variables
Intercept
AR
CFLOW
DEBT
RELSIZE
MBO
PAAR
PSAR
F-Statistic
N
R-Square
Model 1:
Current-Year AFR
as Dependent Variable
0.0012***
(3.50)
0.0055***
(3.82)
-0.0000
(-0.42)
0.0001
(0.33)
0.0010***
(2.56)
0.0002
(0.58)
-0.0008
(-1.54)
0.0004
(0.96)
3.49***
1173
0.02
Model 2:
Five-Year AFR
as Dependent Variable
0.0237*
(1.93)
0.0886*
(1.95)
-0.0100
(-0.80)
0.0209
(0.61)
-0.0100
(-0.80)
-0.0126
(-1.03)
0.0031
(0.20)
-0.0116
(-0.80)
1.29
935
0.01
*Significant at the 0.1 level.
**Significant at the 0.05 level.
***Significant at the 0.01 level.
43
Table 9
Cross-Sectional Regressions of Announcement-Period Abnormal Stock Return for the
Sample of Industry Rivals
ARi = b0 + b1AFRi + b2CFLOWi + b3DEBTi + b4 MBOi + b5PAARi + ei
Where AR is the announcement-period abnormal return, as measured by the cumulative average
abnormal return of the (-20, +1) window based on the market model, AFR is the cumulative
adjusted forecast revisions of current-year earnings per share and 5-year earnings growth rates
for the 2-month (0,1) period for Models 1 and 2, respectively, CFLOW is the ratio of free cash
flow to assets for the year immediately preceding the going-private announcement, DEBT is
total debt over total assets for the year immediately preceding the announcement, MBO is a
dummy variable that takes a value of one if the buyout team for the target firm is led by
management, otherwise zero, and PAAR is the pre-announcement abnormal return, as measured
by the cumulative average abnormal return for the (-90,-21) day period based on the market
model. The t-statistics appear in parentheses.
Independent
Variables
Intercept
AFR
(Current Year or Five Year)
CFLOW
DEBT
MBO
PAAR
F-Statistic
N
R-Square
Model 1:
Current-Year AFR
as Independent Variable
0.0176***
(3.35)
2.2208***
(3.77)
-0.0000
(-0.24)
0.0005
(0.09)
-0.0148*
(-1.84)
0.1119***
(15.23)
50.81***
1173
0.18
*Significant at the 0.1 level.
**Significant at the 0.05 level.
***Significant at the 0.01 level.
44
Model 2:
Five-Year AFR
As Independent Variable
0.0242***
(3.41)
0.0430*
(1.79)
0.0000
(0.26)
-0.0023
(-0.09)
-0.0160*
(-1.79)
0.1014***
(12.02)
30.50***
935
0.14