The Journal of Financial Research • Vol. XXIX, No. 2 • Pages 253–269 • Summer 2006
MARKET EXPECTATIONS AND THE VALUATION EFFECTS OF
EQUITY ISSUANCE
Aigbe Akhigbe and Melinda Newman
University of Akron
Assem Safieddine
American University of Beirut
Abstract
We examine how the wealth effects of equity offers are influenced by investors’
expectation of the equity type (public or private) to be issued. Firms deviating
to the public market may be issuing when information asymmetry or agency
costs are high, and their wealth effects are more negative than for firms that
are anticipated to issue equity publicly. Firms deviating to the private market,
however, may signal firm undervaluation or monitoring benefits and experience
more positive wealth effects than firms that are expected to issue equity privately.
For the private issues, public market accessibility appears to influence the wealth
effects.
JEL Classification: G12, G32
I. Introduction
There is a considerable body of research documenting significant market reaction
to firms’ issuance of common equity. Myers and Majluf (1984) show that under
conditions of information asymmetry, the sale of equity in the public market signals
an overvaluation of the issuing firm to prospective shareholders. As a result, the
market response to public equity issuance is negative. Several studies (e.g., Masulis
and Korwar 1986) empirically support this finding.
However, for firms issuing common equity in the private market, studies
document a positive market response to issue announcements (Wruck 1989; Hertzel
and Smith 1993; Woidtke et al. 2003). Wruck (1989) attributes the positive wealth
effects to a concentration of share ownership arising from private placements, which
subsequently increases monitoring and decreases agency costs within issuing firms.
We thank seminar participants at the University of Akron and the 2004 Financial Management Association meeting for their useful comments. We are especially grateful to William T. Moore (former executive
editor) and an anonymous referee for detailed and insightful comments. Any errors or omissions are our
own.
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Hertzel and Smith (1993) also find evidence of the ownership effects of private
placements but argue that their findings reflect information effects as well. They
assert that private equity sales signal issuing firms’ undervaluation and therefore
mitigate the effects of information asymmetry.
In this article we consider whether the announcement returns to equity
issuance are conditioned on investors’ expectations of issue type. That is, given the
negative market response to public equity issues under asymmetric information,
investors may expect firms with greater information asymmetry to be less likely
to issue equity in the public market. Likewise, investors may anticipate that firms
with greater costs of information asymmetry (Hertzel and Smith 1993) or greater
agency costs (Wruck 1989) will be more likely to place equity privately.
We hypothesize that, regardless of the equity form (public or private),
investors’ expectations significantly influence the wealth effects of equity issuance.
We expect firms that issue equity publicly when private issues are expected are
issuing when information asymmetry or agency costs are relatively high. Therefore,
we expect the valuation effects for these firms to be more negative than for firms
that are anticipated to issue equity publicly. Deviations to the private equity market,
however, may signal undervaluation of the issuing firm’s equity or monitoring
benefits. Therefore, we expect firms that issue equity privately when public issues
are expected to experience more positive announcement effects than firms that
issue equity privately as expected.
We find that the probability of issuing in the public (private) market is
negatively (positively) related to measures of information asymmetry and agency
costs. Consistent with our hypotheses, we find that unanticipated equity issues in
the public market have negative wealth effects, whereas unanticipated equity issues
in the private market have positive wealth effects. A detailed analysis of the private
issue sample shows that the influence of investor expectations varies based on
issuing firms’ characteristics. The valuation effects for firms that are less likely to
have access to the public market (i.e., unprofitable firms and biotechnology firms)
are more favorable when they issue privately as anticipated. The wealth effects for
profitable, nonbiotechnology firms, however, are more favorable for unanticipated
issues and appear consistent with the arguments of Wruck (1989) and Hertzel and
Smith (1993).
Our results are also consistent with those of Bayless and Chaplinsky (1991),
who examine the influence of investors’ expectations on the market reaction to
public issues of equity and debt. They find that the market reaction to an equity
offering is more negative for firms that issue equity when debt is expected. However,
they find a positive and significant announcement response for firms that issue
debt when equity is expected. Bayless and Chaplinsky argue that, consistent with
models of information asymmetry, unexpected issues of public debt signal good
news relative to unexpected issues of public equity.
Market Expectations
255
II. Predictions
We specify a logit model to test the hypothesis that the form of equity issuance is
fundamentally related to observable characteristics (Bayless and Chaplinsky 1991;
Jung, Kim, and Stulz 1996). Based on the prior literature, we categorize those
characteristics as measures of information asymmetry and agency costs, and define
each as follows.
Information Asymmetry
Myers and Majluf (1984) demonstrate that firm-specific information asymmetry
gives rise to an underinvestment problem when external equity financing is required.
Hertzel and Smith (1993) show that if the Myers and Majluf model is extended to
allow private investors to assess firm value at some cost, private equity sales can
diminish the effects of information asymmetry.
Mackie-Mason (1990) examines the choice of public and private equity
issues and finds that firms that are subject to more information asymmetry are
more likely to raise capital in the private market. He maintains that firms that are
unable to signal reliable cash flows through dividends will be subject to a greater
negative stock price effect in the public market and thus avoid public issues. His
results show that firms that do not pay dividends are more likely to use private
sources of funds.
Based on these studies, we expect firms with high (low) information asymmetry to be more likely to issue equity in the private (public) market. Because
smaller firms have less history and a smaller analyst following, we expect these
firms to be subject to greater information asymmetry effects and to be more likely
to place equity privately. Therefore, we include in our model the natural log of the
firm’s book value of assets (LNBVTA) in the year before the equity offering.
Jung, Kim, and Stulz (1996) argue that firms that raise capital when they
have financial slack are more likely to do so because of low information asymmetry
and therefore are more likely to issue public equity. We use the ratio of cash and
marketable securities to total assets (CASH) in the year before the offering as a proxy
for financial slack and expect the measure to positively influence the likelihood of
issuing equity publicly.
We define SIGMA as the market-adjusted residual standard deviation of
the daily stock price abnormal return for days (−220,−20) before the offer date.
To isolate the effects of asset volatility, we adjust for leverage effects and define
ASIGMA as follows:
ASIGMA = SIGMA/(1 +D/E),
(1)
where D = long-term debt book value and E = equity market value in the year
before issuance. We expect firms with higher operating volatility to have greater
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information asymmetry and therefore to be more likely to issue equity privately
(Dierkens 1991).
Finally, several studies suggest that firms time their equity offerings to coincide with periods of low information asymmetry (Korajczyk, Lucas, and
McDonald 1991). For example, Choe, Masulis, and Nanda (1993) show that firms
time public equity issues to coincide with periods of economic expansion and that
the magnitude of the negative stock price response to public equity announcements
is lower during these periods. Based on this argument, we use the compound growth
rate of the Federal Reserve’s monthly index of industrial production (GPROD) in
the year before the issue to control for macroeconomic conditions.1 We expect this
proxy to be positively related to the probability of issuing equity publicly.
Agency Costs
Wruck (1989) argues that a private equity placement concentrates share ownership, which subsequently increases monitoring and decreases agency costs within
the issuing firm. She finds that abnormal returns surrounding private placement
announcements are both positive and positively related to the increase in ownership concentration found in her sample firms. Hertzel and Smith (1993) also find
marginally significant evidence of monitoring effects within their sample.
To test for agency cost effects, we use ex ante proxies for firms most likely to
benefit from increased monitoring through equity private placements. Specifically,
the financial distress dummy variable (IDIS) equals 1 (and 0 otherwise) if the
issuing firm’s cash flow book value (CFBV ) is negative, where CFBV is defined
as (earnings before interest, taxes, depreciation, and amortization)/total asset book
value, and its sales growth (SALEG) is less than the sample median sales growth
in the year before the issue. Following Hertzel and Smith (1993), we hypothesize
that financially distressed firms face an essentially dichotomous resolution of risk
(i.e., they either survive or fail). Therefore, the potential for these firms to be
undervalued or to benefit from increased monitoring is significant. As a result, we
expect financially distressed firms to be more likely to issue equity privately.
Stulz (1990) shows that a firm’s use of leverage limits managerial discretion
through creditor monitoring. Therefore, if a motivation for issuing private equity
is to increase monitoring, we expect firms with higher levels of debt to derive less
marginal benefit from the issuance of private equity. Alternatively, the pecking
order theory asserts that because of information asymmetries, firms prefer debt to
equity issuance. If, ex ante, a firm is an equity issuer (as in our study), it may be that
the same information asymmetries that lead a firm to prefer debt issuance may also
cause the firm to prefer a private placement to a public issuance. If this is the case,
1
The data are from the FRED II database accessible at the Federal Reserve Bank of St. Louis Web site:
http://research.stlouisfed.org/fred2/.
Market Expectations
257
we would expect the firm’s debt level to be positively related to the probability of
issuing equity privately. To capture these possible effects, we define LEVERAGE
as the ratio of long-term debt book value to the sum of long-term debt book value
and equity market value in the year before the equity issue.
Lang, Stulz, and Walkling (1991) argue that firms with high Tobin’s q are
more likely to have positive net present value investment opportunities. If higher
growth opportunities indicate a lower probability of undertaking projects that are
counter to shareholders’ interest, and therefore indicate lower agency problems,
high-q firms are expected to be more likely to issue equity publicly (Jung, Kim,
and Stulz 1996). However, if higher growth opportunities are a proxy for greater
information asymmetry, high-q firms may be more likely to issue equity privately
(Hertzel and Smith 1993). Therefore, we include in our model a proxy for Tobin’s
q, measured as the issuing firm’s equity market-to-book value (MVBV ) in the year
before the issue.
Because greater growth opportunities may translate into greater capital
needs, we define PSHARES as the ratio of issue proceeds to the issuing firms’ equity
market value in the year before the offering. As with MVBV, if a proportionately
large issue is indicative of lower agency costs, we expect a positive relation between
PSHARES and the probability of issuing equity publicly. If, however, larger values
of PSHARES are a proxy for higher information costs, we expect a negative relation
between PSHARES and the probability of issuing equity publicly.
Finally, DeAngelo and DeAngelo (1989) find that after receiving unsolicited offers, firms frequently place blocks of stock with friendly investors to
thwart hostile takeovers. Alternatively, a private equity placement may be indicative of a desired acquisition if the issue purchaser is also the acquiring firm. We
expect that in either case, evidence of takeover activity should be positively related
to the likelihood of a private placement. The variable ACQUIRE equals 1 for firms
that have received a takeover bid in the year before the offering, and 0 otherwise.
III. Data and Method
Sample
Our sample of private and public common equity issues placed by publicly traded
firms is gathered from Thomson Financial’s SDC Global New Issues database.
Observations are included in the sample if they meet the following criteria: (1)
the issuing firm CUSIP and the issue date are available from the SDC database;
(2) the issuing firm has common stock traded on the New York Stock Exchange
(NYSE), American Stock Exchange (AMEX), or NASDAQ and daily return data
at the time of the offering are available from the Center for Research in Security
Prices (CRSP) database; and (3) the issuing firm’s accounting data and four-digit
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Standard Industrial Classification (SIC) code are available from Standard & Poor’s
Compustat database. After applying these criteria and eliminating regulated utilities
and financial services firms, our sample includes 2,094 public issues and 266 private
placements of common equity from 1987 to 2001.
Method
Logistic Model. To determine the observable characteristics significantly
related to the equity issue type, we specify a logit model as follows:
= α + β1 LNBVTA + β2 CASH + β3 ASIGMA + β4 GPROD + β5 I D I S
+β6 LEVERAGE + β7 MVBV + β8 PSHARES + β9 ACQUIRE + ε,
(2)
where the dependent variable () equals 1 for publicly issued equity and 0 for
privately placed equity.
From our logit analysis, we obtain the predicted probability of each firm
issuing in the public market (Bayless and Chaplinsky 1991; Jung, Kim, and Stulz
1996). We designate issues with a probability greater than (less than) the mean of
the predictions as being expected to be placed publicly (privately). Therefore, for
equity issues placed publicly (privately), EXPECT equals 1 if the issue’s predicted
probability is greater than (less than) the mean prediction, and 0 otherwise. Using
this measure, we test whether the market response to equity issue announcements
is conditioned on the expected form of issue.
Analysis of Abnormal Returns. We use standard event-study methodology
to measure the average cumulative abnormal stock returns (CARs) in response to
public issues and private placements. For each firm i that makes a common equity
offering, the event date t = 0 is the offer date of the issue as reported in the SDC
database. We calculate abnormal returns for each day t over days (−1,+1), where
market model parameters are estimated with returns from days (−220,−20) relative
to the offer date, and daily market returns are estimated using the CRSP equally
weighted index.
In testing the influence of the expectations of market choice on announcement return, we use weighted least squares to estimate the following cross-sectional
regression model:
CAR = α + β1 EXPECT + β2 PSHARES + β3 GPROD + β4 RUNUP + ε,
(3)
where RUNUP is the firm’s market-adjusted returns over days (−220,−20) relative
to the offer date. Consistent with prior studies of announcement-day abnormal
returns for equity offerings, we include RUNUP and GPROD in the model to
control for the ex ante uncertainty of the issue (Masulis and Korwar 1986; Choe,
Market Expectations
259
Masulis, and Nanda 1993).2 We expect PSHARES also to influence wealth effects
and therefore include the variable in the model as well (Masulis and Korwar 1986).
IV. Empirical Results
Descriptive Statistics
Panel A of Table 1 shows the distribution of our sample of 2,094 (266) public
(private) equity issues by year. For the public equity sample, two-thirds of the
issues occur in 1995–2001. For the private equity sample, two-thirds of the issues
occur in the last three years of the sample, with nearly half of the issues occurring
in 2001.
Panel B of Table 1 shows that for the public sample, 51.7% of the issues
occur in the manufacturing sector, and 32% occur in the service and wholesale/retail
trade industries. For the private sample, 67.7% of the placements occur in the
manufacturing industries; nearly 46% of the private issues occur in SICs 283 and
384, representing producers of pharmaceutical and biomedical products.
Panel A of Table 2 shows descriptive statistics for the issuing firms and
the equity offerings. For our measures of information asymmetry, the median firm
size for the sample of public equity issuers is larger, as measured by total asset
book value (BVTA) and equity market value (EQMV ) in the year before the issue.
The public issue sample, however, has less financial slack (CASH) at the median
than the private issue sample. Additionally, the median asset volatility (ASIGMA) is
lower for the public issue sample than for the private placement sample. The differences in medians for all of these measures are statistically significant at the 1%
level. Therefore, except for the slack variable, our results indicate that the sample
of public equity issuers has a lower level of information asymmetry than does the
sample of private equity issuers, as expected.
The dummy variable IDIS indicates that a smaller percentage of public
equity issuers are in financial distress. The result appears to be driven by the CFBV
component of the measure, with the median for public (private) issuers being 12.5%
(−18.7%) and significantly different at the 1% level. Based on our findings in
Table 1, this result suggests a concentration of the private issue sample in the
biotechnology sectors and in the post-technology bubble year of 2001.
Public equity issuers have more leverage than private equity issuers at the
median, although the magnitude is small for each sample. MVBV and PSHARES
2
As PSHARES and GPROD are expected to influence both issue type and valuation effects, they are
included in both the logit and cross-sectional regression models. Their inclusion in equation (3), however,
holds their issue uncertainty effects constant and allows EXPECT to capture the effect of security type (see
Bayless and Chaplinsky 1991).
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TABLE 1. Distribution of Public and Private Equity Issues by Year and by Industry.
Panel A. Sample Distribution by Year
Public Issues
Year
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
Total issues
Private Issues
N
%
N
%
65
28
45
33
118
106
158
135
200
223
241
157
202
211
172
2,094
3.1
1.3
2.2
1.6
5.6
5.1
7.6
6.4
9.6
10.6
11.5
7.5
9.6
10.1
8.2
100.0
1
2
14
4
4
11
12
13
7
3
10
5
6
45
129
266
0.4
0.8
5.3
1.5
1.5
4.1
4.5
4.9
2.6
1.1
3.8
1.9
2.3
16.9
48.5
100.0
Panel B. Sample Distribution by Standard Industrial Classification
Public Issues
Private Issues
SIC Codes
Description
N
%
N
%
0100s
1000s
2000–3000s
283
367
384
4000s
5000s
7000–8000s
9000s
Total
Agriculture/forestry/fishing
Mining/construction
Manufacturing
Pharmaceuticals/biological products/diagnostics
Circuit boards/semiconductors/electric components
Surgical/medical/X-ray instruments and apparatus
Transportation/utilities
Wholesale/retail trade
Services
Not classifiable
6
155
1,081
222
157
72
180
294
377
1
2,094
0.3
7.4
51.7
10.6
7.5
3.4
8.6
14.0
18.0
0.0
100.0
1
7
180
85
9
37
12
18
48
0
266
0.4
2.6
67.7
32.0
3.4
13.9
4.5
6.8
18.1
0.0
100.0
Note: The sample of 2,094 public issues and 266 private issues of common equity are from Thomson
Financial’s SDC Global New Issues database for 1987–2001. Panel A shows the distribution of each
sample by year. Panel B provides the distribution of each sample by Standard Industrial Classification
(SIC), as reported in the Compustat database.
are also larger for the public sample, suggesting that the sample of public equity
issuers have greater growth opportunities and therefore greater capital demands.
Consistent with these results, the median level of proceeds raised by the sample of
public issues is greater than that of the sample of private issues, with the difference
being statistically significant at the 1% level. Finally, consistent with the findings
of Masulis and Korwar (1986), our sample of public equity issues are preceded
Market Expectations
261
TABLE 2. Descriptive Statistics of Issuing Firms and Equity Offerings.
Panel A. Summary Statistics
Public Issues
Variable
BVTA ($m)
EQMV ($m)
CASH (%)
ASIGMA (%)
CFBV (%)
SALEG (%)
IDIS (%)
LEVERAGE (%)
MVBV
PSHARES (%)
PROCEEDS ($m)
ACQUIRE (%)
RUNUP (%)
Private Issues
Mean
Median
Mean
Median
1,398.63
1,629.45
52.48
13.44
6.44
0.74
11.89
13.51
14.66
23.69
123.27
12.18
25.96
143.78∗∗∗
367.39∗∗∗
14.10∗∗∗
8.56∗∗∗
12.49∗∗∗
0.18
0.00∗∗∗
5.43∗∗∗
4.39∗∗
16.55∗∗∗
61.15∗∗∗
0.00∗∗
19.49∗∗∗
977.42
1,073.91
64.90
35.28
−28.91
1.41
32.71
9.49
4.27
13.62
30.82
16.54
16.91
49.09
146.56
40.14
24.61
−18.68
0.21
0.00
1.10
3.53
9.28
13.10
0.00
9.90
Panel B. Use of Issue Proceeds
Public Issues
Use of Proceeds
Unknown
Lease-related financing
Acquisition financing
Debt repayment
Secondary shareholders
Refinancing
Retire bank debt
Retire fixed-income debt
Retire acquisition debt
Capital investment
Working capital
Research and development
General corporate purposes
Total
N
Private Issues
%
41
2.0
83
81
309
446
326
60
48
44
34
6
1,050
2,094
4.0
3.9
14.8
21.3
15.6
2.9
2.3
2.1
1.6
0.3
50.1
100.0
N
%
250
13
3
94.0
4.9
1.1
266
100.0
Note: The sample of 2,094 (266) public (private) issues of common equity are from Thomson Financial’s
SDC Global New Issues database for 1987–2001. In Panel A, BVTA = total asset book value; EQMV =
equity market value; CASH = (cash and marketable securities)/BVTA; ASIGMA = leverage-adjusted
standard deviation of the daily stock price return for days (−220,−20) relative to the issue date; CFBV =
(earnings before interest, taxes, depreciation, and amortization)/BVTA; SALEG = firm sales growth; IDIS
= 1 if the issuing firm’s CFBV < 0 and SALEG < median SALEG value; LEVERAGE = long-term debt
book value/(long-term debt book value + equity market value); MVBV = equity market/book value;
PSHARES = issue proceeds/equity market value; PROCEEDS = total issue proceeds; ACQUIRE = 1 if
the firm has been an acquisition target in the year before the issue, and 0 otherwise; RUNUP = issuing
firm’s market-adjusted returns over days (−220,−20). Panel B shows the use of issue proceeds for each
sample, as defined and reported in the SDC database.
∗∗∗
∗∗
Significant at the 1% level.
Significant at the 5% level.
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The Journal of Financial Research
by a positive run-up in stock prices (RUNUP). Although also positive, the median
RUNUP for the private sample is lower and is significantly different at the 1% level.
Panel B of Table 2 shows the use of issue proceeds as categorized and
reported in the SDC database. For the public sample, 50.1% of the issues are applied
to general corporate purposes and an additional 21.3% are used to refinance debt.
For the 266 private issues, information is extremely limited, and it is unknown how
the proceeds are applied for 94% of the sample.
Logit Model Results
Table 3 presents the results of our logit model of equity issue type. Because the
dependent variable is equal to 1 (0) if the issue is publicly (privately) placed, a
positive coefficient estimate indicates a propensity for the firm to issue equity in
the public market.
Consistent with expectations, the positive LNBVTA coefficient estimate
suggests that larger firms are more likely to issue equity publicly or, conversely,
that smaller firms with potentially greater information asymmetry are more likely
to issue equity privately. The positive CASH coefficient estimate is significant at a
10% level and suggests that firms issuing equity in the presence of financial slack
are more likely to have low information asymmetry and therefore favor the public
market.
The negative ASIGMA coefficient estimate implies the greater a firm’s
operating risk, the greater is the information asymmetry, and the more likely is
the firm to issue equity privately. Finally, the positive GPROD coefficient estimate
indicates that firms are more likely to issue equity in the public market during
periods of low information asymmetry.3
Among our measures of agency costs, the IDIS coefficient estimate
(−0.470) is consistent with our prediction that financially distressed firms are more
likely to issue equity privately.4 The negative LEVERAGE coefficient estimate suggests the more levered the firm, the more likely equity will be issued privately.
Combined with the low magnitude of leverage used by each sample as shown in
Panel A of Table 2, this is consistent with leverage reflecting the firm’s preference
to mitigate the effects of information asymmetry rather than the marginal benefits
of increased monitoring.
3
To test for robustness, we reestimate the model using the natural log of firm equity market value (and
necessarily drop MVBV from the model) to proxy for information asymmetry. Consistent with MackieMason (1990), we also estimate the model using an indicator variable that equals 1 if the firm pays a
dividend in the year before issue, and 0 otherwise. The results are qualitatively the same.
4
As an alternative measure of financial distress, we define a dummy variable that equals 1 if the issuing
firm’s equity returns are in the lowest decile of all common equity returns available from the CRSP database
in each of the two years preceding the offering, and 0 otherwise. A second dummy variable equals 1 if
the firm’s interest coverage ratio is less than one in the year before issue, and 0 otherwise. The results are
robust.
Market Expectations
263
TABLE 3. Logit Model of the Choice Between Public and Private Equity Issues.
Variable
Intercept
LNBVTA
CASH
ASIGMA
GPROD
IDIS
LEVERAGE
MVBV
PSHARES
ACQUIRE
% correctly classified
Coefficient Estimates
−0.9857
(.004)∗∗∗
0.4709
(.000)∗∗∗
0.1471
(.069)∗
−2.5229
(.000)∗∗∗
24.4930
(.000)∗∗∗
−0.4702
(.017)∗∗
−3.0342
(.000)∗∗∗
0.0011
(.073)∗
8.2246
(.000)∗∗∗
−0.5463
(.010)∗∗∗
79.4%
Note: The sample of 2,094 (266) public (private) issues of common equity are from Thomson Financial’s
SDC Global New Issues database for 1987–2001. The dependent variable = 1 (0) if the firm issues equity
publicly (privately). LNBVTA = ln(total asset book value); CASH = (cash and marketable securities)/BVTA;
ASIGMA = leverage-adjusted standard deviation of the daily stock price return for days (−220,−20)
relative to the issue date; GPROD = compound growth rate of the monthly industrial production index
for the year before the issue; IDIS = 1 if the issuing firm’s CFBV < 0 and SALEG < median SALEG
value, where CFBV is (earnings before interest, taxes, depreciation, and amortization)/BVTA and SALEG
is firm sales growth; LEVERAGE = long-term debt book value/(long-term debt book value + equity
market value); MVBV = equity market/book value; PSHARES = issue proceeds/equity market value; and
ACQUIRE = 1 if the firm has been an acquisition target in the year before the issue, and 0 otherwise. The
p-values based on the χ 2 -statistic are reported in parentheses.
∗∗∗
Significant at the 1% level.
Significant at the 5% level.
∗
Significant at the 1% level.
∗∗
The coefficient estimates of MVBV and PSHARES are positive and significant at the 10% level and 1% level, respectively. The results imply that, on average,
firms with higher growth opportunities are more likely to issue equity publicly, and
they suggest investment opportunities correspond with lower agency costs. Finally,
the negative coefficient estimate for ACQUIRE suggests that, on average, a firm
that has been a target of acquisition is more likely to place equity privately.
Our logit model correctly classifies 79.4% of the types of equity issuance.
This result is consistent with Bayless and Chaplinsky (1991) and Jung, Kim, and
Stulz (1996), who correctly classify 78%, and between 74% and 82%, respectively,
of their samples of public debt and equity issues. Using our logit specification, we
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The Journal of Financial Research
then estimate the predicted probability of each firm issuing in the public market.
Based on the mean of 0.885, EXPECT equals 1 for public (private) issues with
a predicted probability greater than (less than) the mean, and 0 otherwise.5 We
explore the implications for announcement returns in the following section.
Announcement Return Results
Public and Private Equity Samples. Panel A of Table 4 reflects CAR
results over the announcement period t−1 to t+1 for the public and private equity
issue samples. Consistent with prior studies (Masulis and Korwar 1986; Dierkens
1991), the mean three-day CAR for the public issue sample is −2.78% and is
statistically significant at the 1% level. For the sample of private issues, the mean
3-day CAR is 2.25%, is statistically significant at the 5% level, and is consistent
with the findings of Wruck (1989), Hertzel and Smith (1993), and Woidtke et al.
(2003).
Results of the cross-sectional analysis of each sample are shown in Panel
B of Table 4. For the public issues, the EXPECT coefficient estimate in model 1
is positive and significant at the 1% level. This suggests that, on average, a public
equity issuance that is consistent with market expectations results in a favorable
market response whereas a public equity issuance that is unanticipated by the market
results in a negative market response, as hypothesized.
The significance of EXPECT holds with the addition of PSHARES and
GPROD in model 2, but is lost with the addition of RUNUP in model 3. The
PSHARES coefficient estimate is positive and significant, suggesting the greater
the average firm’s growth opportunities, the less negative is the market response to
a public equity issue. The RUNUP coefficient estimate is negative and significant,
and is consistent with prior empirical findings (Masulis and Korwar 1986).
For private issues, the EXPECT coefficient estimate in model 1 is significant at the 1% level. The negative sign suggests that, on average, a private equity
issuance that is consistent with market expectations results in a less favorable market
response. Conversely, a private equity issuance that is unanticipated by the market
is associated with a more positive wealth effect, as hypothesized.
Although the sign of EXPECT remains negative, the variable is no longer
significant with the addition of the control variables in models 2 and 3. Among
the statistically significant variables, the positive PSHARES coefficient estimate is
consistent with Hertzel and Smith’s (1993) argument that a larger equity issuance
in the public market may reflect a greater potential for undervaluation of the firm,
5
The mean value of 0.885 reflects the heavier weighting (88.7%) of public issues in the total sample.
We also randomly select 308 public issues and repeat the logit analysis for the balanced sample. This results
in a mean predicted probability of 0.523, 79.8% correct classification, and logit coefficient estimates that
are qualitatively the same.
Market Expectations
265
TABLE 4. Cumulative Abnormal Returns and Cross-Sectional Regression Results for Public
and Private Issue Samples.
Panel A. Cumulative Abnormal Returns
Public issue sample
Private issue sample
N
CAR (%)
z-statistic
2,094
266
−2.78
2.25
−22.39∗∗∗
2.13∗∗
Panel B. Cross-Sectional Regression Results
Public Issue Sample
Coefficient Estimates
Variable
Model 1
Model 2
Intercept
−0.0408
(−12.03)∗∗∗
0.0127
(3.02)∗∗∗
−0.0395
(−10.98)∗∗∗
0.0157
(3.37)∗∗∗
0.0073
(2.86)∗∗∗
−0.1675
(−2.27)∗∗
EXPECT
PSHARES
GPROD
RUNUP
R2
Adjusted R2
F-value
N
0.0044
0.0039
9.13∗∗∗
2,091
0.0107
0.0093
7.52∗∗∗
2,091
Private Issue Sample
Coefficient Estimates
Model 3
Model 1
Model 2
Model 3
−0.0219
(−5.15)∗∗∗
0.0016
(0.32)
0.0090
(3.55)∗∗∗
−0.0140
(−0.19)
−0.0278
(−7.56)∗∗∗
0.0371
0.0352
20.09∗∗∗
2,091
0.1267
(4.08)∗∗∗
−0.0968
(−2.91)∗∗∗
0.0106
(0.29)
−0.0301
(−0.85)
0.2927
(5.64)∗∗∗
−0.0151
(−0.05)
0.0149
(0.42)
−0.0020
(−0.06)
0.2758
(5.58)∗∗∗
0.1667
(0.59)
−0.0676
(−5.35)∗∗∗
0.2275
0.2156
19.21∗∗∗
265
0.0310
0.0273
8.45∗∗∗
265
0.1429
0.1331
14.56∗∗∗
265
Note: The sample of 2,094 (266) public (private) issues of common equity are from Thomson Financial’s
SDC Global New Issues database for 1987–2001. In Panel A, abnormal returns are calculated as: ARt =
Rt − (α + βRmt ), where ARt is the daily abnormal return, Rit is the daily return, Rmt is the daily return on
the Center for Research in Security Prices (CRSP) equally weighted index, and α and β are obtained from
the market model, estimated with daily returns from days (−220,−20) relative to the reported offer date, t
= 0. The issuing firm’s CAR is the three-day cumulated abnormal return for days (−1,+1). The z-statistic
tests for the statistical significance of each mean value. In Panel B, EXPECT = 1 for public (private) issues
if the predicted probability of issue type is > (≤) the mean predicted probability as estimated by the logit
model, and 0 otherwise; PSHARES = issue proceeds/equity market value; GPROD = compound growth
rate of the monthly industrial production index for the year before the issue; and RUNUP = issuing firm’s
market-adjusted returns over days (−220,−20). The t-statistics are reported in parentheses.
∗∗∗
∗∗
Significant at the 1% level.
Significant at the 5% level.
and therefore positive information effects, when equity is instead placed privately.
It may also be that the positive PSHARES coefficient estimate reflects the effects
of increased ownership concentration and subsequently an increase in monitoring
within the issuing firm (Wruck 1989; Hertzel and Smith 1993). Therefore, we allow
for the possibility of alternative interpretations of PSHARES.
Finally, the negative and significant RUNUP coefficient estimate indicates
that the higher the pre-announcement stock price run-up, the less positive is the
market response to a private equity placement. This is consistent with the findings
266
The Journal of Financial Research
of Masulis and Korwar (1986), who suggest that high price run-up followed by a
negative announcement return may reflect the positive effects of capital expenditure
announcements being made before, rather than simultaneous with, stock offering
announcements.
Private Equity Subsamples. Woidtke et al. (2003) assert that because public capital markets may be inaccessible for firms in financial distress, these firms
are likely to rely on private equity placements as a source of financing. Their findings support this line of reasoning. Given the negative median CFBV for our private
equity sample, it may be that a portion of this sample behaves in a manner consistent with that of Woidtke et al. Alternatively, nearly half of our private issues are
made by biotechnology firms from SIC 283 and SIC 384. We expect these firms to
be relatively young, high-growth firms with uncertain future cash flows. For these
firms, it may be that because information or agency costs are acute, the private
placement market is their most viable option for raising capital as well.
To allow for these distinctions, we isolate the sample of private placements
that are issued by unprofitable firms (CFBV < 0) or firms in SIC 283 and SIC 384
and repeat our analysis. As expected, Table 5 shows that the unprofitable firms and
biotechnology firms have significantly higher information asymmetry, as measured
by BVTA, EQMV, ASIGMA, MVBV, and PSHARES. The results for CFBV, IDIS, and
LEVERAGE suggest higher agency costs for this subsample as well. As a measure
of firm age, IPO equals 1 if the firm issued an IPO in the three years before
the private placement, and 0 otherwise. According to this measure, a significantly
larger proportion of the unprofitable/biotechnology firms are relatively young. Also
consistent with our expectations, the results for EXPECT indicate that a larger
proportion of these firms are anticipated by the investors to issue equity privately.
Panel A of Table 6 shows a positive three-day CAR for each subsample;
however, only the 2.65% return of the unprofitable and biotechnology subsample
is statistically significant. In the cross-sectional regression results of Panel B, the
EXPECT coefficient estimate for the profitable firms and nonbiotechnology firms
is negative and significant in each model. For the unprofitable firms and biotechnology firms, however, the EXPECT coefficient estimate is positive and significant
in models 2 and 3.
The results suggest that among the sample of private equity issuers, profitable firms and nonbiotechnology firms appear to have relatively lower information
or agency costs and hence are more likely to have access to the public equity market. For this subsample, deviating from market expectations and making a private
placement may be indicative of firm undervaluation or monitoring benefits, and
is associated with more favorable wealth effects (Wruck 1989; Hertzel and Smith
1993). For unprofitable firms and biotechnology firms, however, the public equity
market may be inaccessible. Consequently, issuing equity privately as anticipated
by the market is associated with more favorable wealth effects.
Market Expectations
267
TABLE 5. Descriptive Statistics of Issuing Firm and Equity Offerings for Private Issue
Subsamples.
Profitable,
Nonbiotechnology Firms
Variable
BVTA ($m)
EQMV ($m)
CASH (%)
ASIGMA (%)
CFBV (%)
SALEG (%)
IDIS (%)
LEVERAGE (%)
MVBV
PSHARES (%)
PROCEEDS ($m)
ACQUIRE (%)
RUNUP (%)
IPO
EXPECT
Unprofitable Firms
and Biotechnology Firms
Mean
Median
Mean
Median
1, 891.57
1, 905.47
38.48
23.49
6.39
0.43
13.33
16.86
6.76
12.06
41.42
16.30
17.84
16.30
0.68
123.44∗∗∗
235.03∗∗∗
10.51∗∗∗
14.75∗∗∗
8.98∗∗∗
0.22
0.00∗∗∗
5.38∗∗∗
2.58∗∗∗
7.29∗∗∗
15.00
0.00
11.61
0.00∗∗∗
1.00∗∗∗
35.35
216.96
92.12
47.43
−65.28
2.41
52.67
1.90
1.71
15.24
19.91
16.79
15.95
32.82
0.85
20.45
106.15
68.00
32.70
−50.38
0.18
100.00
0.18
5.65
11.09
11.50
0.00
6.94
0.00
1.00
Note: The sample of 266 private issues of common equity is from Thomson Financial’s SDC Global New
Issues database for 1987–2001. Firms in Standard Industrial Classification (SIC) code 283 and SIC 384
are designated as biotechnology firms. Profitable (unprofitable) firms are defined as firms with CFBV >
0 (< 0), where CFBV is (earnings before interest, taxes, depreciation, and amortization)/BVTA and BVTA
is total asset book value. EQMV = equity market value; CASH = (cash and marketable securities)/BVTA;
ASIGMA = leverage-adjusted standard deviation of the daily stock price return for days (−220,−20)
relative to the issue date; SALEG = firm sales growth; IDIS = 1 if the issuing firm’s CFBV < 0 and SALEG
< median SALEG value; LEVERAGE = long-term debt book value/(long-term debt book value + equity
market value); MVBV = equity market/book value; PSHARES = issue proceeds/equity market value;
PROCEEDS = total issue proceeds; ACQUIRE = 1 if the firm has been an acquisition target in the year
before the issue, 0 otherwise; RUNUP = issuing firm’s market-adjusted returns over days (−220,−20);
IPO = 1 if the firm issued an IPO in the three years before issue, and 0 otherwise; and EXPECT = 1 for
private issues if the predicted probability of issue type is ≤ the mean predicted probability as estimated by
the logit model, 0 otherwise.
∗∗∗
Significant at the 1% level.
V. Conclusion
We examine the influence of investors’ expectations of issue type on the wealth
effects of public and private issues of common equity. We find that the probability of
issuing in the public (private) market is negatively (positively) related to measures
of information asymmetry and agency costs. Therefore, we expect that firms that
issue equity publicly when private issues are expected are issuing when information
asymmetry or agency costs are relatively high. Deviations to the private equity
market, however, may signal the undervaluation of the issuing firm’s equity or
monitoring benefits.
268
The Journal of Financial Research
TABLE 6. Cumulative Abnormal Returns and Cross-Sectional Regression Results for Private
Issue Subsamples.
Panel A. Cumulative Abnormal Returns
Profitable, nonbiotechnology firms
Unprofitable firms and biotechnology firms
N
CAR (%)
z-statistic
t-statistic
105
161
1.65
2.65
0.76
2.85∗∗∗
0.59
Panel B. Cross-Sectional Regression Results
Profitable, Nonbiotechnology
Firms Coefficient Estimates
Variable
Model 1
Model 2
Model 3
Intercept
0.2831
(5.84)∗∗∗
−0.3037
(−5.61)∗∗∗
0.1276
(1.49)
−0.2000
(−2.51)∗∗∗
0.3761
(2.28)∗∗
−0.5984
(−0.98)
0.2338
0.2264
31.44∗∗∗
104
0.3008
0.2801
14.48∗∗∗
104
0.1863
(2.52)∗∗∗
−0.1864
(−2.75)∗∗∗
0.2045
(1.43)
−0.8429
(−1.61)
−0.1048
(−6.24)∗∗∗
0.4968
0.4767
24.68∗∗∗
104
EXPECT
PSHARES
GPROD
RUNUP
R2
Adj R2
F-value
N
Unprofitable Firms and Biotechnology
Firms Coefficient Estimates
Model 1
0.0079
(0.21)
0.0400
(1.02)
0.0065
0.0002
1.03
160
Model 2
Model 3
−0.0947
(−2.32)∗∗
0.0970
(2.45)∗∗
0.2562
(5.13)∗∗∗
0.2882
(0.91)
−0.0942
(−2.32)∗∗
0.1054
(2.63)∗∗∗
0.2566
(5.15)∗∗∗
0.3890
(1.20)
−0.0225
(−1.29)
0.1585
0.1369
7.35∗∗∗
160
0.1496
0.1333
9.20∗∗∗
160
Note: The sample of 266 private issues of common equity is from Thomson Financial’s SDC Global New
Issues database for 1987–2001. Firms in Standard Industrial Classification (SIC) code 283 and SIC 384
are designated as biotechnology firms. Profitable (unprofitable) firms are defined as firms with CFBV >
0 (< 0), where CFBV is (earnings before interest, taxes, depreciation, and amortization)/total asset book
value. In Panel A, abnormal returns are calculated as: ARt = Rt − (α + βRmt ), where ARt is the daily
abnormal return, Rit is the daily return, Rmt is the daily return on the Center for Research in Security Prices
(CRSP) equally weighted index, and α and β are obtained from the market model, estimated with daily
returns from days (−220,−20) relative to the reported offer date, t = 0. The issuing firm’s CAR is the
three-day cumulated abnormal return for days (−1,+1). The z-statistic tests for the statistical significance
of each mean value, and the t-statistic tests for whether the mean values are significantly different. In
Panel B, EXPECT = 1 for private issues if the predicted probability of issue type is ≤ the mean predicted
probability as estimated by the logit model, and 0 otherwise; PSHARES = issue proceeds/equity market
value; GPROD = compound growth rate of the monthly industrial production index for the year before
the issue; RUNUP = issuing firm’s market-adjusted returns over days (−220,−20). The t-statistics are
reported in parentheses.
∗∗∗
∗∗
Significant at the 1% level.
Significant at the 5% level.
Consistent with our hypotheses, we find that the valuation effects for firms
that issue equity publicly when private issues are expected are more negative than
for firms that are expected to issue equity publicly. Firms that issue equity privately
when public issues are expected experience more positive announcement effects
than firms for which a private issue is anticipated.
Market Expectations
269
A detailed analysis of the private issue sample shows that the valuation
effects for firms that are less likely to have access to the public market (i.e., unprofitable firms and biotechnology firms) are more favorable when they issue privately
as anticipated. The wealth effects for profitable firms and nonbiotechnology firms,
however, are more favorable for unanticipated issues and appear consistent with the
arguments of Wruck (1989) and Hertzel and Smith (1993).
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