Table 1: Sample Incidence of Corporate Control Events



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Table 1: Sample Incidence of Corporate Control Events





Year

Number of companies

Friendly takeovers

Failed friendly bids

Hostile takeovers

Failed hostile bids

Bid targets overall

Bankruptcies

1988

579

26

0

13

5

44

2

1989

550

26

1

10

6

43

10

1990

526

21

3

7

3

34

11

1991

508

19

0

2

3

24

8

1992

495

7

0

3

3

13

6

1993

483

6

1

0

0

7

1

1994

462

6

0

2

2

10

3

1995

438

12

0

6

1

19

1

1996

59

6

0

1

0

7

0

Totals




129

5

44

23

201

42

Notes:


  1. Observations on accounting years are allocated to the current calendar year if the accounting year ends in July-December, and to the preceding calendar year if the accounting year ends in January-June. See also the Data Appendix for a description of the ‘year’ variable.

  2. At time of sampling, only 59 companies had company accounts reported by Datastream for 1996.



Table 2: Takeover likelihood model: Friendly versus Hostile Targets

Marginal effects from multinomial logit regression.

Sample period is 1989-96.

Number of observations = 4100.

2 (26) = 146.6; P-Value= 0.0000. Log Likelihood = -669.1

Likelihood Ratio Index = 0.1186








Friendly Targets

Hostile Targets

Variable

Marginal effect

Standard error

P-Value

Marginal effect

Standard error

P-Value

Log Real Capital Stock

-.0024

.0012

0.049

.00051

.00054

0.34

Return-on-Sales

-.0312

.0233

0.18

-.0099

.0122

0.41

Q

-.0020

.00081

0.01

-.0017

.00062

0.006

Sectoral Q

.0015

.0013

0.25

.00020

.00072

0.77

Leverage

.0055

.0028

0.05

-.0012

.0036

0.73

Sectoral Leverage

-.0096

.0130

0.46

.0038

.0059

0.52

Income Gearing

.00025

.00094

0.78

.000015

.000036

0.67

Sectoral Income Gearing

.00032

.00095

0.73

-.00010

.000048

0.03

Takeover Rumours

.0074

.0029

0.01

.0043

.0012

0.00

Age 1-5 Years Dummy

.0530

.0080

0.00

.0094

.0048

0.05

Age 6-9 Years Dummy

.0238

.0047

0.00

-.0075

.0057

0.19

Aggregate Takeover Activity

.00020

.000071

0.004

.000069

.000035

0.05

Real GDP Growth

.0013

.00083

0.10

.001163

.0004459

0.009

Notes:


  1. Time dummies are excluded.

  2. Industry dummies are insignificant and thus excluded.

  3. Regressors scaled so that means lie on the unit interval. Marginal effects evaluated at means of variables.

  4. 2 statistic is for a Wald test of the null hypothesis that the marginal effects are jointly insignificantly different from zero.

  5. The Likelihood Ratio Index—which is also known as McFadden's (pseudo) R-squared—has been recommended by Cameron-Windmeijer (1997) as a measure of goodness-of-fit for the logit model.



Table 3: Summary Statistics on Actual Sample Frequency and Predicted Probabilities

Sample period 1989-96. 4100 observations.




Probability

Mean

Std. Dev.










Sample Frequency of All-target takeover bids

.0380

.1913

Recursive All-target Predicted Probabilities

.0391

.0544










Sample Frequency of Friendly-target takeover bids

.0263

.1601

Recursive Friendly-target Predicted Probabilities

.0260

.0399










Sample Frequency of Hostile-target takeover bids

.0117

.1075

Recursive Hostile-target Predicted Probabilities

.0130

.0290


Table 4: Prediction Tables. Recursive Model. Hostile targets.

Table 4.1: Hostile-target predicted probabilities for 1989








Actual Bids in Subsequent Year

Probability-Ranked Observations

Top

Bottom

Top/Bottom

10

3

0




20

6

0




30

7

0




40

7

0




50

7

0




100

9

0




200

12

0




290

14

2

7

Total Number of observations: 579

Total number of hostile bids: 16

Table 4.2: Hostile predicted probabilities year-by-year





Year of bid

Number of observations in preceding year

Number of actual bids

Number of bids in top half of ranked observations

Number of bids in bottom half of ranked observations

Top/bottom

1989

579

16

14

2

7

1990

550

10

8

2

4

1991

526

5

5

0



1992

508

6

4

2

2

1993

495

0

0

0



1994

483

4

2

2

1

1995

462

7

6

1

6

1996

438

1

0

1

0


Table 5: Production Function Model

Dependent variable is yit (log real sales).

Sample period is 1989 to 1996.

551 companies; 3413 observations.




Independent Variable

Col. (1)

Col. (2)

Col. (3)

Col. (4)

Col. (5)

yit-1

0.5993

(0.1042)a



0.7935

(0.0536)a



0.6716

(0.0766)a



0.8656

(0.0487)a



0.6630

(0.0798)a



lit

0.7429

(0.1044)a



0.7675

(0.0816)a



0.7236

(0.1009)a



0.7555

(0.0929)a



0.7654

(0.0919)a



lit-1

-0.5723

(0.1147)a



-0.6066

(0.0846)a



-0.5540

(0.1192)a



-0.6409

(0.1028)a



-0.5811

(0.1056)a



kit

0.3495

(0.1344)a



0.1793

(0.1078)c



0.3241

(0.1301)b



0.1588

(0.1210)


0.2635

(0.1191)b



kit-1

-0.2233

(0.1252)c



-0.1397

(0.1014)


-0.2096

(0.1204)c



-0.1409

(0.1099)


-0.1792

(0.1145)c



pFit-1




0.9275

(0.4674)b






0.7519

(0.4779)





pHit-1







0.1369

(0.2436)


-0.0858

(0.2723)





pAit-1













0.4747

(0.2108)b



m1

0.00

0.00

0.00

0.00

0.00

m2

0.86

0.53

0.73

0.48

0.78

Sargan

0.81

0.17

0.54

0.09

0.58

Notes:


  1. Time dummies are included in all specifications. Industry dummies (in the levels equations) are insignificant and thus excluded.

  2. Predicted probabilities generated by a recursively-estimated takeover likelihood model.

  3. All equations estimated with one-step GMM system estimator. Instruments for equations in first-differences are yit-2, lit-2, kit-2, pit-2 and further lags. Instruments for equations in levels are lit-1, kit-1 and pit-1. Instruments yit-1 are rejected by Sargan test, and thus excluded.

  4. In parentheses are asymptotic standard errors robust to general cross-section and time-series heteroskedasticity. The superscript ‘a’ indicates that the coefficient is significantly different from zero at the 0.01 level, ‘b’ at the 0.05 level and ‘c’ at the 0.10 level.

  5. m1 and m2 are test statistics, distributed standard normal, for first- and second-order serial correlation in the first-differenced residuals. Sargan statistic is that for the corresponding two-step GMM estimator, distributed chi-squared. P-values are reported.

Table 6: Production Function Model: Robustness


Dependent variable is yit (log real sales).

Sample period is 1989 to 1996.

551 companies; 3413 observations.


Independent Variable

Col. (1)

Col. (2)

Col. (3)

Col. (4)

Col. (5)

yit-1

0.6814

(0.0744)a



0.6395

(0.0765)a



0.7134

(0.0669)a



0.6319

(0.0855)a



0.8292

(0.0594)a



lit

0.7879

(0.0805)a



0.7685

(0.0888)a



0.7671

(0.0890)a



0.7289

(0.0959)a



0.7779

(0.0836)a



lit-1

-0.5823

(0.0965)a



-0.5709

(0.1025)a



-0.5877

(0.1082)a



-0.5240

(0.1088)a



-0.6361

(0.1021)a



kit

0.1521

(0.1092)


0.2624

(0.1118)b



0.2384

(0.1149)b



0.2562

(0.1187)b



0.0893

(0.0894)


kit-1

-0.0907

(0.1161)


-0.1691

(0.1079)


-0.1538

(0.1109)


-0.1584

(0.1156)


-0.0546

(0.0911)


pAit-1

0.3742

(0.2119)c



0.4618

(0.2061)b



0.7212

(0.2993)b



0.4140

(0.2063)b



0.5339

(0.2775)b



Qit-1

-0.0017

(0.0031)











0.000025

(0.0037)


LEVit-1




0.0246

(0.0081)a









0.0302

(0.0104)a



Rumit-1







-0.0209

(0.0133)





-0.0164

(0.0122)


Ageit-1










-0.0019

(0.0019)


-0.0004

(0.0012)


m1

0.00

0.00

0.00

0.00

0.00

m2

0.65

0.76

0.72

0.70

0.46

Sargan

0.61

0.61

0.50

0.59

0.23

Notes:


  1. Time dummies are included in all specifications. Industry dummies (in the levels equations) are insignificant and thus excluded.

  2. Predicted probabilities taken from a recursively-estimated takeover likelihood model.

  3. All equations estimated with one-step GMM system estimator. All independent variables except for age (which is treated as exogenous) are instrumented. Instruments for equations in first-differences are as in Table 4.1, with additional regressors instrumented with twice- and further-lags. Instruments for equations in levels are the lagged first-differences of the included independent variables, except for yit-1 and LEVit-1, both of which are rejected by the Sargan test.

  4. In parentheses are asymptotic standard errors robust to general cross-section and time-series heteroskedasticity. The superscript ‘a’ indicates that the coefficient is significantly different from zero at the 0.01 level, ‘b’ at the 0.05 level and ‘c’ at the 0.10 level.

  5. m1 and m2 are test statistics, distributed standard normal, for first- and second-order serial correlation in the first-differenced residuals. Sargan statistic is that for the corresponding two-step GMM estimator, distributed chi-squared. P-values are reported.

Table 7: Investment Model

Dependent variable is It/Kit-1 (Investment rate)

Sample period is 1990 to 1996

494 companies; 2697 observations.




Independent Variable

Col. (1)

Col. (2)

Col. (3)

Col. (4)

It-1/Kit-2

-0.0482

(0.0535)


-0.0598

(0.0492)


-0.0487

(0.0524)


-0.0383

(0.0489)


yit

0.1938

(0.0476)a



0.2338

(0.0501)a



0.1800

(0.0412)a



0.2210

(0.0511)a



yit-1

0.0894

(0.0226)a



0.0921

(0.0247)a



0.0945

(0.0210)a



0.0866

(0.0247)a



(kit-2 -yit-2)

-0.0786

(0.0205)a



-0.0835

(0.0193)a



-0.0803

(0.0205)a



-0.0701

(0.0175)a



yit-2

0.0110

(0.0062)c



0.0293

(0.0104)a



0.0104

(0.0062)c



0.0321

(0.0106)a



Ct-1/Kit-2

0.0175

(0.0111)


0.0231

(0.0122)c



0.0150

(0.0105)


0.0219

(0.0122)c



pFit-1

-0.9586

(0.2950)a






-1.0569

(0.3313)a






pHit-2




-0.2045

(0.1137)c



-0.3019

(0.1278)b






pAit-1










-0.2340

(0.1239)b



pAit-2










-0.1275

(0.0905)


Wald on probabilities







0.003

0.14

m1

0.00

0.00

0.00

0.00

m2

0.30

0.47

0.25

0.00

Sargan

0.15

0.10

0.13

0.21

Notes:


  1. Time dummies are included in all specifications. Industry dummies (in the levels equations) are insignificant and thus excluded.

  2. Predicted probabilities taken from a recursively-estimated takeover likelihood model.

  3. All equations estimated with one-step GMM system estimator. Instruments for equations in first differences are (It-2/Kit-3), (kit-2 -yit-2), yit-2, Ct-2/Kit-3, pit-2 and further lags. Instruments for equations in levels are (It-1/Kit-2), yit-1 and pit-1.

  4. In parentheses are asymptotic standard errors robust to general cross-section and time-series heteroskedasticity. The superscript ‘a’ indicates that the coefficient is significantly different from zero at the 0.01 level, ‘b’ at the 0.05 level and ‘c’ at the 0.10 level.

  5. Wald test applies if there are two probabilities included in the model, and is for the null hypothesis that the probabilities are jointly insignificantly different from zero. P-values are reported.

  6. m1 and m2 are test statistics, distributed standard normal, for first- and second-order serial correlation in the first-differenced residuals. Sargan statistic is that for the corresponding two-step GMM estimator, distributed chi-squared. P-values are reported.

Table 8: Investment Model: Robustness

Dependent variable is It/Kit-1 (Investment rate)

Sample period is 1990 to 1996

494 companies; 2697 observations.




Independent Variable

Col. (1)

Col. (2)

Col. (3)

Col. (4)

Col. (5)

It-1/Kit-2

-0.0297

(0.0503)


-0.0745

(0.0530)


-0.0607

(0.0528)


-0.0556

(0.0559)


-0.0195

(0.0476)


yit

0.1577

(0.0373)a



0.1891

(0.0399)a



0.1891

(0.0389)a



0.1799

(0.0412)a



0.1735

(0.0345)a



yit-1

0.0842

(0.0207)a



0.1051

(0.0219)a



0.0950

(0.0211)a



0.0998

(0.0251)a



0.0729

(0.0199)a



(kit-2 -yit-2)

-0.0687

(0.0201)a



-0.0923

(0.0220)a



-0.0855

(0.0213)a



-0.0841

(0.0233)a



-0.0555

(0.0179)a



yit-2

0.0092

(0.0064)


0.0116

(0.0065)c



0.0088

(0.0062)


0.0096

(0.0063)


0.0087

(0.0039)b



Ct-1/Kit-2

0.0026

(0.0075)


0.0032

(0.0090)


0.0148

(0.0106)


0.0146

(0.0105)


0.0030

(0.0091)


pFit-1

-0.8126

(0.2799)a



-1.0974

(0.3481)a



-1.1867

(0.4141)a



-1.0252

(0.3119)a



-0.7602

(0.3398)b



pHit-2

-0.3034

(0.1237)b



-0.3018

(0.1259)b



-0.2591

(0.1286)b



-0.3011

(0.1276)b



-0.2818

(0.1170)b



Qit-1

0.0052

(0.0021)b












0.0031

(0.0022)


Qit-2

-0.0013

(0.0010)











-0.0009

(0.0015)


LEVit-1




0.0031

(0.0047)








-0.0042

(0.0067)


LEVit-2




-0.0054

(0.0045)








-0.0032

(0.0056)


Rumit-1







0.0095

(0.0063)





0.0091

(0.0053)c



Rumit-2







0.0009

(0.0039)





0.0038

(0.0038)


Ageit-1










0.0004

(0.0006)


-0.0003

(0.0004)


Wald on pFit-1 and pHit-2

0.005

0.004

0.01

0.003

0.01

m1

0.00

0.00

0.00

0.00

0.00

m2

0.30

0.20

0.25

0.23

0.23

Sargan

0.17

0.12

0.08

0.13

0.02

Notes:


  1. Time dummies are included in all specifications. Industry dummies (in the levels equations) are insignificant and thus excluded.

  2. Predicted probabilities taken from a recursively-estimated takeover likelihood model.

  3. All equations estimated with one-step GMM system estimator. All independent variables except for age (which is treated as exogenous) are instrumented. Instruments for equations in first-differences are as in Table 4.3, with additional regressors instrumented with twice- and further-lags. Instruments for equations in levels are as in Table 4.3; the Sargan test rejects Qit-1, LEVit-1 and Rumit-1.

  4. In parentheses are asymptotic standard errors robust to general cross-section and time-series heteroskedasticity. The superscript ‘a’ indicates that the coefficient is significantly different from zero at the 0.01 level, ‘b’ at the 0.05 level and ‘c’ at the 0.10 level.

  5. Wald test is for the null hypothesis pFit-1 and pHit-2 are jointly insignificantly different from zero. P-values are reported.

  6. m1 and m2 are test statistics, distributed standard normal, for first- and second-order serial correlation in the first-differenced residuals. Sargan statistic is that for the corresponding two-step GMM estimator, distributed chi-squared. P-values are reported.

Table 9: Dividend Model


Dependent variable is (D/Y)it (Dividend-to-sales ratio)

Sample period is 1990 to 1996

510 companies; 2821 observations.


Independent Variable

Col. (1)

Col. (2)

Col. (3)

Col. (4)

Col. (5)

(D/Y)it-1

0.3063

(0.1753)c



0.2990

(0.1778)c



0.3236

(0.1723)c



0.2962

(0.1645)c



0.3076

(0.1507)b



(/Y)it

0.0685

(0.0259)a



0.0651

(0.0264)a



0.0833

(0.0253)a



0.0581

(0.0300)b



0.0714

(0.0315)b



Ageit

0.00064

(0.00026)b



0.00068

(0.00028)b



0.00046

(0.00021)b



0.00056

(0.00024)b



0.00041

(0.00017)b



pAit

0.2168

(0.1484)


0.1110

(0.1164)











pAit-1

-0.0289

(0.0236)














pHit







0.5252

(0.2128)a






0.3270

(0.1874)c



pFit-1










-0.0720

(0.0462)


-0.0519

(0.0396)


Wald on probabilities

0.31










0.07

m1

0.04

0.04

0.01

0.04

0.02

m2

0.17

0.13

0.12

0.20

0.12

Sargan

0.52

0.51

0.58

0.39

0.39

Notes:


  1. Time dummies are included in all specifications. Industry dummies (in the levels equations) are insignificant and thus excluded.

  2. Predicted probabilities taken from a recursively-estimated takeover likelihood model.

  3. All equations estimated with one-step GMM system estimator. Instruments for equations in first differences are (D/Y)it-2, (/Y)it-2, pit-2 and further lags; age is treated as exogenous. Instruments for equations in levels are (/Y)it-1 and pit-1. Sargan test rejects (D/Y)it-1.

  4. In parentheses are asymptotic standard errors robust to general cross-section and time-series heteroskedasticity. The superscript ‘a’ indicates that the coefficient is significantly different from zero at the 0.01 level, ‘b’ at the 0.05 level and ‘c’ at the 0.10 level.

  1. Wald test applies if there are two probabilities included in the model, and is for the null hypothesis that the probabilities are jointly insignificantly different from zero. P-values are reported.

  1. m1 and m2 are test statistics, distributed standard normal, for first- and second-order serial correlation in the first-differenced residuals. Sargan statistic is that for the corresponding two-step GMM estimator, distributed chi-squared. P-values are reported.



Table 10: Dividend Model: Robustness

Dependent variable is (D/Y)it (Dividend-to-sales ratio)

Sample period is 1990 to 1996

510 companies; 2821 observations.




Independent Variable

Col. (1)

Col. (2)

Col. (3)

Col. (4)

(D/Y)it-1

0.2651

(0.1468)c



0.3271

(0.1601)b



0.3943

(0.1651)b



0.3284

(0.1307)a



(/Y)it

0.0821

(0.0244)a



0.0758

(0.0230)a



0.0712

(0.0182)a



0.0656

(0.0164)a



Ageit

0.00051

(0.00021)b



0.00046

(0.00020)b



0.00022

(0.00011)b



0.00024

(0.00011)b



pHit

0.6163

(0.2056)a



0.4842

(0.1988)a



0.3608

(0.1373)a



0.4304

(0.1424)a



Qit

0.00026

(0.00034)









0.00023

(0.00028)



LEVit




-0.00051

(0.00096)






-0.0010

(0.0010)


Rumit







-0.00096

(0.00051)c



-0.0011

(0.00054)b



m1

0.01

0.02

0.02

0.02

m2

0.13

0.12

0.47

0.65

Sargan

0.31

0.44

0.58

0.21

Notes:


  1. Time dummies are included in all specifications. Industry dummies (in the levels equations) are insignificant and thus excluded.

  2. Predicted probabilities taken from a recursively-estimated takeover likelihood model.

  3. All equations estimated with one-step GMM system estimator. All independent variables except for age (which is treated as exogenous) are instrumented. Instruments for equations in first-differences are as in Table 4.5, with additional regressors instrumented with twice- and further-lags. Instruments for equations in levels are as in Table 4.5, with the addition of Rumit-1 in Columns 3 and 4. Sargan test rejects (D/Y)it-1, Qit-1 and LEVit-1.

  4. In parentheses are asymptotic standard errors robust to general cross-section and time-series heteroskedasticity. The superscript ‘a’ indicates that the coefficient is significantly different from zero at the 0.01 level, ‘b’ at the 0.05 level and ‘c’ at the 0.10 level.

  5. m1 and m2 are test statistics, distributed standard normal, for first- and second-order serial correlation in the first-differenced residuals. Sargan statistic is that for the corresponding two-step GMM estimator, distributed chi-squared. P-values are reported.



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