Do Takeovers Create Value? New Methods and Evidence
Sanjai Bhagat, University of Colorado,
Ming Dong, York University
David Hirshleifer, Ohio State University,
Robert Noah, Cambridge Finance Partners
1
The Question
Do takeovers improve target and bidder
firm value?
Other stakeholders not considered:
Employees
Customers/Suppliers
Bondholders
2
Two important challenges to estimating
value effects of takeovers
I: Truncation Dilemma (of Window Length)
» Short return window: Since not all bids succeed,
return is only a fraction of the value effects of successful
takeovers.
» Long return window: Can capture full value effects.
But, return includes greater noise, and raises questions
of benchmark specification.
3
Two important challenges to estimating
value effects of takeovers
II: Revelation Bias
» Bidder’s return at the time of bid gives a wrong
estimate of the market’s valuation of the
bidder’s gain from takeover, because


Some bidders deliberately time bid announcement
with unrelated negative announcements. Wall
Street’s version of Wag the Dog (WSJ 12/18/98).
The form of the offer and the very fact of an offer may
convey information about the bidder’s stand-alone
value.
4
“It's Wall Street's version of `Wag the Dog.’ ”

“Over the past week, both Mattel and CocaCola have announced acquisitions on the
same day they also issued warnings about
disappointing earnings. ... No one is
suggesting that either company unveiled its
acquisition solely to divert attention from its
problems... But it is also clear that the
acquisitions, like the [Iraq] bombings, helped
shift attention away from other less favorable
developments.''
» WSJ, `Heard on the Street', 12/18/98, p. C1
5
Revelation Examples

Returns to bidding firm shareholders.
Fact of an Offer
» Good news

Bidder expects high cash flow.
» Bad news


Poor internal investment opportunities.
Bidder management with empire-building propensities.
Cash vs. Exchange Offer
» Stock Offer: Bad news, lemons problem with equity
issuance
» Cash offer: Good news that not issuing equity.
6
Solution to Dilemma of Window Length problem
Probability Scaling Method
»Like traditional methods, uses short
return window.
»Method adjusts return from short window
upward to reflect the probability of
success of bid.
7
Solution to Dilemma of Window Length and
Revelation Bias problems
Intervention Method
»Focuses on the returns to the bidder
when something happens (while the bid
is outstanding) that changes the
probability of success of the bidder.
8
What might change the probability of success of a bidder?
Litigation by target firm.
Arrival of other bidders.
Objection by a government regulatory
agency (FTC, Dept. of Justice).
Defensive measures by target (poison pill,
lock-up provision).
9
Arrival of a second bidder:

Decreases probability of success of the first
bidder.
If takeover is in the interest of the first bidder, the
first bidder’s stock price declines at the arrival of
the second bidder.
If takeover is not in the interest of the first bidder, the
first bidder’s stock price rises at the arrival of the
second bidder.
Note: Decline/rise in the first bidder’s stock price is
not related to the stand-alone value of the first
bidder, but only reflects value from the takeover.
10
Findings

Value improvements (as % of combined value) from
tender offers in the competing bid subsample:
– Intervention Method: Mean of 13.1% (median of 12.4%).
– Probability Scaling Method: 14.7% (9.7%).
– Conventional combined abnormal returns: 9.0% (7.6%).

Full sample of tender offers:
– Bradley-Desai-Kim (1988): Conventional combined abnormal
returns: 5.3% (3.7%).
– Probability Scaling Method: 7.3% (4.6%).
11
Findings
Traditional methods lead to incorrect inferences about economic forces in the
takeover market.
 We find that friendly offers, equity offers, and diversifying offers are
associated with lower combined bidder-target stock returns.
A conventional interpretation would be that the gains from combination
are smaller for firms involved with these types of transactions.
However, our new methods indicate that these effects reflect
differences in revelation about stand-alone value of the bidder,
not differences in the gains from combination.

For example, cash offers on average are associated with higher bidder, target and
combined abnormal returns than equity or mixed-payment offers.
In contrast, based on the intervention method, cash offers do not create higher value
improvements than mixed or equity offers.
Hence, apparent superiority of cash offers in creating shareholder value is an illusory
consequence of a more negative revelation effect for the bidder for equity or
mixed offers than for cash offers.
12
Findings

Conventional combined returns, PSM value improvements, and bidder
returns tend to be lower in diversifying acquisitions.
IM estimates of value improvements are similar in diversifying and sameindustry acquisitions.
The relative superiority of same-industry acquisitions with PSM
(which does not filter out revelation effects) compared to IM (which does)
indicates that same-industry acquisitions are associated with more
favorable revelation about the bidder than cross-industry acquisitions.
This finding suggests that investors perceive diversifying acquisitions as
indicating poor investment opportunities within the bidder's own
industry.
13
Findings
Bidder announcement period returns and total value
improvements are negatively related to bidder Tobin's Q.

This result is quite different from the evidence from earlier samples
of Lang, Stulz, and Walkling (1989) and Servaes (1991),

Do bidders overpay?
– Conventional combined abnormal returns: Yes.
– Intervention and Probability Scaling Methods: No.
14
Specifics of the Intervention Method
4 dates
t = 0:
t = 1:
t = 2:
t = 3:
Time prior to first bid.
Arrival of first bid.
Time prior to arrival of competing bid.
Arrival of competing bid.
15
y : Market value of bidder not related with takeover.
t : Bidder's profit from takeover conditional on t.
Pt : Bidder's price at t.
Hence,
P1 = y + 1 ,
P3 = y + 3 .
(8)
16
V0T
: Non-takeover target value.

: Fraction of target held by first bidder prior to first bid.
VC
: Combined post-takeover value.
V0B
: Non-takeover
VI
:Value improvement from takeover.
bidder value.
Then, VI = VC – V0B – V0T(1- )
(1)
17
V1 , V3 : Post-takeover gains.
B1 , B3 : Price ultimately paid by a successful first bidder.
Hence,
1 = Pr(S|1) {V1 + (1-)[V1 + V0T - B1]},
3 = Pr(S|3) {V3 + (1-)[V3 + V0T - B3]}.
(9)
18
Assume, V3 = V1 = V .
[See footnotes 18, 19, sec. 4.5]
Also, R3 = P3 / P1 - 1.
(VI/VC) = {[R3(P1/V0)] / [Pr(S|3) - Pr(S|1)]}
{(1 - ) [l(B1/V0) + (1 - l)(B3/V0) - 1](VOT/ VC)}, (11)
where, l = Pr(S|1) / [Pr(S|1) - Pr(S|3)].
LHS of (11) is the
Intervention Method Improvement Method, IRIM.
Strong Agency / Hubris Hypothesis: IRIM = 0.
IRIM> 0. Implies joint value improvement.
19
The Probability Scaling Method of Estimating Value
Changes : IRPSM
Value Improvement = [Combined Initial Bidder and Target
Return] /
[(Probability a First Bidder arrives
and wins) +
(Probability a First Bidder arrives but
a Later Bidder wins)]
(6)
20
DATA
MERC and SDC datasets.
Table 1: 1018 tender offers during 1962-2001.
Figure 2 : Percentage of
•Successful takeovers,
•Multiple (two) bidder takeovers,
•Hostile takeovers,
•All cash offers.
Figures 3, 4 : Mean percentage and dollar shareholder returns to
•Bidders,
•Targets,
•Combined entity,
over various sub-periods during 1962-2001.
21
50.00
40.00
%
30.00
20.00
10.00
0.00
7/62-6/68
7/68-12/80
1/81-12/84
1/85-12/88
1/89-12/92
1/93-12/96
1/97-3/00
4/00-12/01
7/62-12/01
-10.00
Sub-period
Bidder
Target
Combined
Fig. 3. Mean shareholder returns (%). Announcement period return is the market-model cumulative abnormal return for the target,
bidder or combined, over the period five days before the first bid through five days after. Combined return is the weighted average of
target and bidder returns, where their weights are their market values as a fraction of the total target and bidder market value.
Sample includes 1018 tender offers where both bidder and target were listed on the NYSE, AMEX, or NASDAQ during 1962-2001.
22
$ Million (2001 Dollars)
400.0
300.0
200.0
100.0
0.0
-100.0
7/62-6/68
7/68-12/80
1/81-12/84
1/85-12/88
1/89-12/92
1/93-12/96
1/97-3/00
4/00-12/01
7/62-12/01
-200.0
-300.0
Sub-period
Bidder
Target
Combined
Fig. 4. Mean dollar returns. Target dollar return is target market value (six days before the first bid) multiplied by target CAR; similarly
for bidder and combined dollar returns. CAR is the market-model cumulative abnormal return for the target, bidder or combined, over the
period five days before the first bid through five days after. Combined return is the weighted average of target and bidder CARs, where
their weights are their market values as a fraction of the total target and bidder market value. Sample includes 1018 tender offers where
both bidder and target were listed on the NYSE, AMEX, or NASDAQ during 1962-2001.
23
Table 3, Model B: Entry of second bidder
significantly lowers probability of success of
first bidder.
24
ESTIMATES OF VALUE IMPROVEMENTS
(VI/VC) = {[R3(P1/V0)] / [Pr(S|3) - Pr(S|1)]}
{(1 - ) [l(B1/V0) + (1 - l)(B3/V0) - 1](VOT/ VC)}, (11)
where, l = Pr(S|1) / [Pr(S|1) - Pr(S|3)].
LHS of (11) is the
Intervention Method Improvement Method, IRIM.
R3 : Bidder abnormal return at entry of second bidder = -.43%.
P1/V0 : Size of bidder relative to initial combined value = .656
(median = .690).
25
Pr(S|1) : Unconditional probability of success of
first bidder = 690/1018 =.6778.
Pr(S|3) : Probability of success of first bidder given arrival of
competing bid = 38/147 =.2585.

: Fraction of target's equity owned by first
bidder = .024 (median = .000).
B1/V0
: Average price at which first bidder wins in
full sample = 1.407 (1.384).
B3/V0
: Average price at which first bidder wins
given arrival of competing bid = 1.514 (1.421).
26
Table 4
IRIM : Implicit market estimates of the value improvement
as a result of the takeover.
CIBR : Combined Initial Bid Return = target CAR* (target
market value/target and bidder market values) + bidder
CAR * (bidder market value/target and bidder market
values). CAR is the market-model cumulative abnormal return for the target
or bidder over the period five days before the first bid through five days after.
IRPSM : (CIBR)/(Probability the first bidder succeeds
unconditionally + Probability a later bidder succeeds).
All improvement ratios are expressed as a percent of target and bidder market
values.
27
Table 4
Value improvement measures and comparisons by sub-periods
7/626/68
Median (%)
Binomial p
Sample size
15.79
0.00
18
Median (%)
Binomial p
Sample size
6.42
0.00
63
Median (%)
Binomial p
Sample size
8.57
0.01
18
Median (%)
Binomial p
Sample size
8.42
0.00
63
Median (%)
Binomial p
Sample size
1.25
0.00
63
Median (%)
Binomial p
Sample size
-4.98
0.81
18
Sub-period
7/681/811/851/891/9312/80
12/84
12/88
12/92
12/96
IRIM
12.33
8.51
14.26
9.24
9.99
0.00
0.01
0.00
0.04
0.01
36
12
37
9
11
CIBR
4.20
8.22
3.97
1.76
4.04
0.00
0.00
0.00
0.10
0.00
159
44
212
82
137
IM
IR – CIBR
4.53
-2.37
3.71
7.36
8.37
0.07
0.77
0.51
0.18
0.23
36
12
37
9
11
PSM
IR
5.49
8.82
5.16
2.07
5.19
0.00
0.00
0.00
0.10
0.00
159
44
212
82
137
PSM
IR
– CIBR
0.46
1.08
0.35
0.01
0.38
0.00
0.00
0.00
0.19
0.00
159
44
212
82
137
PSM
IM
IR
- IR (Estimated Revelation Bias)
-1.71
15.90
2.94
-5.35
-5.45
0.62
0.04
0.19
1.00
0.23
36
12
37
9
11
1/973/00
4/0012/01
Total
7/6212/01
9.70
0.01
14
11.48
0.13
4
12.38
0.00
141
2.93
0.00
204
3.00
0.17
75
3.69
0.00
976
2.66
0.42
14
4.47
1.00
4
3.74
0.00
141
3.22
0.00
204
3.17
0.17
75
4.63
0.00
976
0.10
0.00
204
0.00
0.09
75
0.22
0.00
976
4.79
0.79
14
-3.88
1.00
4
1.10
0.61
141
28
A. Histogram of CIBR
300
Frequency
250
200
150
100
50
0
-20
-15
-10
-5
0
5
10
15
20
25
30
35
40
More
CIBR (%)
CIBR: Combined Initial Bid Return
B. Histogram of IRPSM
300
200
150
100
50
0
-20
-15
-10
-5
0
5
10
15
20
25
30
35
40
More
IRPSM (%)
IRPSM: Improvement Ratio based on Probabilty Scaling Method
C. Histogram of IRIM
35
30
Frequency
Frequency
250
25
20
15
10
5
0
-20
-15
-10
-5
0
5
10
15
20
25
30
35
40
More
IRIM (%)
IRIM: Implicit Market estimates of the value to the bidder of the takeover
29
Table 8
Determinants of returns and value improvements (t-statistics in parentheses).
Independent Variable
CIBR
Hostile
1.05
(1.12)
2.69
(3.05)
-4.81
(-2.20)
2.98
(0.84)
2.31
(1.72)
1.37
(1.78)
Dependent Variable
IRPSM
Bidder
CAR
7.63
-1.63
(6.00)
(-1.83)
3.86
2.28
(3.22)
(2.71)
-5.20
-2.41
(-1.76)
(-1.16)
7.18
4.54
(1.49)
(1.34)
2.48
-0.05
(1.36)
(-0.04)
1.47
2.11
(1.42)
(2.89)
-2.53
(-11.14)
-0.65
(-2.41)
-0.28
(-2.66)
0.12
(0.74)
11.64
(6.13)
634
.2242
-3.10
(-10.06)
-0.50
(-1.38)
-0.39
(-2.73)
0.14
(0.62)
11.93
(4.63)
634
.2751
Cash
Stock
Pre-Williams Act
Post-March 2000
Same Industry
Log of Relative Size
Log of Target Size
Bidder Tobin’s Q
Target Tobin’s Q
Constant
Sample Size
Adjusted R2
-0.36
(-1.69)
-0.61
(-2.40)
-0.38
(-3.72)
0.13
(0.83)
2.71
(1.50)
636
.0530
Target
CAR
5.93
(2.46)
2.77
(1.22)
-16.05
(-2.86)
-1.04
(-0.11)
11.22
(3.24)
0.79
(0.40)
3.58
(6.13)
-1.16
(-1.69)
-0.16
(-0.57)
-0.97
(-2.26)
28.47
(5.84)
635
.1147
30
Table 5, Panel B; Table 6, Panel B
IRPSM - IRIM (Estimated Revelation Bias)
Hostile
Mean (%)
t-statistic
Median (%)
NonHostile
Cash
Mixed
Stock
6.06*** -4.42***
2.06**
0.64♦
-13.21 ♦**
-2.75
2.32
1.95
-7.88
1.24
0.18
-2.70
-0.81
1.50
1.36
-0.72
2.98
-2.75
5.42*** -4.01***
♦♦
♦♦
PrePostPreWilliams Williams March
Act
Act
2000
PostMarch
2000
1.77***
-3.38
-11.76 ***
-4.98
1.70
1.10
-3.88
Binomial p
0.02
0.07
0.37
0.54
0.29
0.81
0.47
0.61
1.00
Sample size
82
59
100
24
8
18
123
137
4
CrossIndustry
Mean (%)
t-statistic
Median (%)
SameIndustry
(4-digit)
6.48*
1.91
5.72*
CrossIndustry
0.39*
0.25
-0.02*
SameIndustry
(3-digit)
7.87***
2.63
6.52***
Binomial p
Sample size
0.15
31
1.00
109
0.07
38
0.77
102
-0.55***
-0.35
-1.17***
31
Table 9
Bidder Overpayment: The difference between value improvement measures
and toehold-adjusted bid premium (ToePrem).
ToePrem = (1-alpha) * (bid premium) * Target market value/Combined bidder and target market value, where alpha is the fraction of pre-bid target shares held
by the bidder. All improvement ratios are expressed as a % of combined target and bidder market value.
7/626/68
7/6812/80
1/8112/84
Sub-period
1/851/8912/88
12/92
Mean (%)
Median (%)
% positive
p-value of mean
Binomial p
Sample size
-0.11
0.35
54.2
0.91
0.60
59
-4.41
-2.33
34.5
0.00
0.00
145
-2.34
-4.73
27.3
0.31
0.00
44
-4.26
-3.13
31.8
0.00
0.00
211
-3.53
-2.61
30.9
0.00
0.00
81
Mean (%)
Median (%)
% positive
p-value of mean
Binomial p
Sample size
3.70
3.46
64.4
0.02
0.04
59
-1.71
-0.23
49.0
0.17
0.87
145
2.77
-1.82
45.5
0.32
0.65
44
-1.62
-1.59
42.2
0.07
0.03
211
-2.04
-1.04
39.5
0.06
0.07
81
Mean (%)
Median (%)
% positive
p-value of mean
Binomial p
Sample size
5.46
6.42
82.4
0.00
0.01
17
0.03
1.67
58.1
0.99
0.47
31
-2.47
-7.09
16.7
0.76
0.04
12
-7.27
-3.82
29.7
0.02
0.02
37
3.86
2.32
66.7
0.21
0.51
9
Mean (%)
Median (%)
% positive
p-value of mean
Binomial p
Sample size
-1.15
-0.62
47.1
0.67
1.00
17
-3.51
-1.74
35.5
0.04
0.15
31
0.83
-7.04
33.3
0.92
0.39
12
-10.48
-5.74
27.0
0.00
0.01
37
-2.67
-1.64
33.3
0.26
0.51
9
Mean (%)
Median (%)
% positive
p-value of mean
Binomial p
Sample size
3.41
3.34
58.8
0.37
0.63
17
-0.25
0.37
54.8
0.90
0.72
31
14.78
6.50
75.0
0.09
0.15
12
-2.17
-1.13
48.6
0.52
1.00
37
2.33
-0.48
44.4
0.63
1.00
9
Total
1/974/007/623/00
12/01
12/01
CIBR – ToePrem (full sample)
-1.05
-1.53
-1.96
-2.66
0.57
-1.62
-0.84
-1.93
54.7
42.2
47.3
40.0
0.21
0.02
0.20
0.00
0.31
0.03
0.73
0.00
137
204
74
955
IRPSM – ToePrem (full sample)
0.29
-0.33
-1.70
-0.59
1.19
-0.93
-0.78
-0.48
58.4
45.6
47.3
48.0
0.74
0.67
0.28
0.14
0.06
0.23
0.73
0.22
137
204
74
955
IRIM – ToePrem (competing bid sub-sample)
-0.90
-3.38
7.79
-1.45
3.14
-2.07
6.64
-0.07
54.5
42.9
100.0
49.6
0.84
0.30
0.08
0.27
1.00
0.79
0.13
1.00
11
14
4
135
CIBR – ToePrem (competing bid sub-sample)
-8.32
-4.03
-1.26
-5.06
-5.60
-3.14
4.47
-2.95
36.4
42.9
50.0
35.6
0.12
0.19
0.89
0.00
0.55
0.79
1.00
0.00
11
14
4
135
IRPSM – ToePrem (competing bid sub-sample)
-7.55
2.73
-0.10
0.91
-5.24
2.98
5.06
0.56
45.5
57.1
50.0
54.1
0.17
0.50
0.99
0.56
1.00
0.79
1.00
0.39
11
14
4
135
1/9312/96
32
SENSITIVITY ANALYSIS
1. Sensitivity of mean of estimated IRIM to simultaneous
variation in each of the estimated parameters [Pr(S|1),
Pr(S|3), B1/V0 , B3/V0] in the direction of lower IRIM:
Mean IRIM remains positive with simultaneous 12% shift in
all four estimated parameters.
2. Parameter estimates from
Bhagat-Shleifer-Vishny (1990): IRIM = 9.0% (9.9%).
Parameter estimates from Betton-Eckbo (2000):
IRIM = 17.5% (15.3%).
33
SENSITIVITY ANALYSIS
3. Model Specification: Table 10
•If the arrival of a competing bid causes an upward
revision in the expected post-takeover value of the
target to the first bidder => K > 1.
•If the first bidder fails to acquire the target, the first
bidder will successfully acquire another similar target at
a similar premium=> g > 0.
•An unsuccessful first bidder can sometimes profit by
selling its holdings to a successful competing bidder=>
Pr(S2|3) > 0.
K
1.00
1.10
1.20
1.30
1.40
IRIM (%)
mean/median
14.8/13.8
15.8/15.2
17.5/16.9
18.4/19.0
19.0/20.8
g
0.0
0.2
0.4
0.6
1.0
IRIM (%)
mean/median
14.8/13.8
14.5/13.5
14.3/14.1
14.0/14.6
13.4/14.3
Pr(S2|3)
0.0
0.1
0.3
0.5
0.7
IRIM (%)
Mean/median
14.8/13.8
14.9/13.8
15.3/14.2
15.6/14.3
15.9/14.8
34