mergers determinants
DESCRIPTION
Determinants of Mergers and AcquisitionsTRANSCRIPT
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The Determinants of MergersBurcin YurtogluUniversity of Vienna Department of Economics
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Empirical RegularitiesMergers come in waves USA: Late 1890s, 1920s, 1960s, 1980s, 1990s
Merger waves are correlated with increases in share prices and price/earnings ratios
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Diagramm1
43
26
69
303
1208
340
423
379
142
79
226
128
87
50
49
142
103
82
85
39
71
117
195
71
171
206
487
309
311
368
554
856
870
1058
1245
799
464
203
120
101
130
126
124
110
87
140
111
118
213
324
333
419
404
223
126
219
235
288
295
387
683
673
585
589
835
844
954
853
861
854
1008
995
1496
4462
6107
5152
4608
4801
4040
2861
2297
2276
2224
2106
2128
1889
2395
2533
2543
2543
3001
3336
2032
2258
2366
2074
1877
2574
2663
2997
3510
5848
7800
7809
combined data:1895-1920: Nelson (1959)1921-67: FTC1968-83: MA1984-98: GMYZ
Mergers
Figure 8.1Numbers of Mergers
Chart3
4317.1293481572
2616.9573368836
6917.9699722309
30319.4816406839
120821.5381678475
34018.571103806
42322.73651647
37921.9569024678
14217.6365457354
7916.290311499
22619.3125164483
12818.718517101
8713.4092491649
5013.1384143216
4914.8579527304
14213.5498274068
10314.2479052212
8213.7341019615
8511.9469319117
3911.0542518545
7111.4978513694
11711.9986916811
1958.7828469866
716.4410599389
1716.5428237663
2065.3113808461
4875.4066889781
3097.5230652322
3117.8627375829
3688.3718872698
55410.1025217012
85611.7261181982
87015.856800707
105821.7894221765
124527.6008331357
79921.4788426397
46414.6659329281
2038.0703441006
12011.097248433
10112.1964402102
13013.1210346448
12619.258219785
12418.4564520626
11013.9288362725
8715.5660029017
14014.6857117454
11112.2131400924
1189.2383636942
21311.0420847806
32411.342426436
33313.2706302746
41914.0460187135
40411.1728619855
22310.6545457014
1269.9017722617
21911.1825805323
23512.0081853818
28812.4554494991
29512.0025251019
38713.6644005293
68317.5243151484
67318.2586972739
58515.6139753114
58915.1427334654
83518.3669629217
84417.4169250809
95420.4566437038
85318.8235121608
86120.2592394909
85422.5534236629
100823.262154452
99521.3017639497
149621.606171101
446221.4860862636
610719.4274846418
515215.1841516734
460816.8672876013
480117.7687667275
404016.1479152853
286110.9262117887
229710.2362398756
227611.5434639395
222410.4315126312
21069.3791396495
21288.9272334824
18898.8330489903
23958.4632109552
25337.3467455585
25439.6420818166
25439.4295562305
300110.691307551
333613.3877091945
203216.0148687703
225814.4399157717
236616.6136281698
207416.4566305781
187717.9201414191
257419.6358563509
266320.7497684949
299720.4797456567
351022.7207007485
584825.9439560601
780030.9558873084
780936.0077469744
961442.0693621636
1095241.7025081885
842332.0651717447
660023.4441410187
Mergers
Average P/E
Year
Mergers
P/E ratio
Mergers and P/E Ratios
Chart1
17.12934815720.6189620254
16.95733688360.3673570379
17.96997223090.9572627944
19.48164068394.1288979249
21.538167847516.1735414572
18.5711038064.4740035131
22.736516475.4515687785
21.95690246784.7859510541
17.63654573541.757689396
16.2903114990.9589048811
19.31251644832.6910072159
18.7185171011.4956557277
13.40924916490.9979472111
13.13841432160.5632106648
14.85795273040.5421883625
13.54982740681.5439437263
14.24790522121.1034205437
13.73410196150.8657100444
11.94693191170.8845526062
11.05425185450.4001329344
11.49785136940.7183221936
11.99869168111.1674866348
8.78284698661.919496891
6.44105993890.6895684187
6.54282376631.6389234309
5.31138084611.948716148
5.40668897814.5337303205
7.52306523222.831653732
7.86273758292.8061006469
8.37188726983.2700532997
10.10252170124.8493195617
11.72611819827.3825382961
15.8568007077.3944556202
21.78942217658.8637806152
27.600833135710.2834254112
21.47884263976.5078369996
14.66593292813.7520881503
8.07034410061.6298165414
11.0972484330.9566073957
12.19644021020.7994760756
13.12103464481.0218345609
19.2582197850.9835176185
18.45645206260.961232799
13.92883627250.8468676644
15.56600290170.6652401064
14.68571174541.0632701
12.21314009240.8310119899
9.23836369420.87101008
11.04208478061.5504700268
11.3424264362.3262407306
13.27063027462.3586357005
14.04601871352.9283062297
11.17286198552.7864196637
10.65454570141.5181248035
9.90177226170.8468052431
11.18258053231.4532437728
12.00818538181.5290050302
12.45544949911.8379995376
12.00252510191.8473354935
13.66440052932.378803701
17.52431514844.1223003339
18.25869727393.9897664684
15.61397531143.4075239247
15.14273346543.371951973
18.36696292174.6996277129
17.41692508094.6714744626
20.45664370385.1935040827
18.82351216084.5727948193
20.25923949094.5497299754
22.55342366294.4504897915
23.2621544525.1877735212
21.30176394975.0620675621
21.6061711017.5284834333
21.486086263622.2315227248
19.427484641830.131688554
15.184151673425.1253340616
16.867287601322.1900124603
17.768766727522.873232458
16.147915285319.0647879633
10.926211788713.3782861204
10.236239875610.6355891018
11.543463939510.4386906528
10.431512631210.0981203112
9.37913964959.4615543531
8.92723348249.4554661054
8.83304899038.2950563396
8.463210955210.4145830253
7.346745558510.9092631833
9.642081816610.8532818617
9.429556230510.75955794
10.69130755112.5846032558
13.387709194513.8623977839
16.01486877038.3688901336
14.43991577179.2155369284
16.61362816989.5657025495
16.45663057818.2968963303
17.92014141917.4288091324
19.635856350910.0779139423
20.749768494910.3169465148
20.479745656711.4987514896
22.720700748513.3418477889
25.943956060122.026199426
30.955887308429.0992658031
36.007746974428.867801925
42.069362163635.2232145003
41.702508188539.7716543439
32.065171744730.4079422383
23.444141018722.9056059631
Average P/E
Mergers/Population
Year
Mergers and Average P/E ratio
Sheet1
YearNelsonFTCM&AsGMYZ (SDC)GMYZ (SDC Broad)MergersAverage P/EpopMergers/Population
1895434317.12934815720.6466560855694711440.61896202540.6355734749
1896262616.9573368836707758320.3673570379
1897696917.9699722309720805200.9572627944
189830330319.4816406839733852004.1288979249
18991208120821.53816784757468988816.1735414572
190034034018.571103806759945764.4740035131
190142342322.73651647775923445.4515687785
190237937921.9569024678791901124.7859510541
190314214217.6365457354807878801.757689396
1904797916.290311499823856480.9589048811
190522622619.3125164483839834242.6910072159
190612812818.718517101855811921.4956557277
1907878713.4092491649871789600.9979472111
1908505013.1384143216887767280.5632106648
1909494914.8579527304903744960.5421883625
191014214213.5498274068919722641.5439437263
191110310314.2479052212933460961.1034205437
1912828213.7341019615947199360.8657100444
1913858511.9469319117960937760.8845526062
1914393911.0542518545974676080.4001329344
1915717111.4978513694988414400.7183221936
191611711711.99869168111002152801.1674866348
19171951958.78284698661015891201.919496891
191871716.44105993891029629520.6895684187
19191714381716.54282376631043367841.6389234309
19202067062065.31138084611057106241.948716148
19214874875.40668897811074170644.5337303205
19223093097.52306523221091235122.831653732
19233113117.86273758291108299522.8061006469
19243683688.37188726981125363923.2700532997
192555455410.10252170121142428324.8493195617
192685685611.72611819821159492807.3825382961
192787087015.8568007071176557207.3944556202
19281058105821.78942217651193621608.8637806152
19291245124527.600833135712106860810.2834254112
193079979921.47884263971227750486.5078369996
193146446414.66593292811236644723.7520881503
19322032038.07034410061245538961.6298165414
193312012011.0972484331254433120.9566073957
193410110112.19644021021263327360.7994760756
193513013013.12103464481272221601.0218345609
193612612619.2582197851281115840.9835176185
193712412418.45645206261290010080.961232799
193811011013.92883627251298904240.8468676644
1939878715.56600290171307798480.6652401064
194014014014.68571174541316692721.0632701
194111111112.21314009241335720800.8310119899
19421181189.23836369421354748960.87101008
194321321311.04208478061373776961.5504700268
194432432411.3424264361392805122.3262407306
194533333313.27063027461411833122.3586357005
194641941914.04601871351430861282.9283062297
194740440411.17286198551449889282.7864196637
194822322310.65454570141468917441.5181248035
19491261269.90177226171487945440.8468052431
195021921911.18258053231506973601.4532437728
195123523512.00818538181536947201.5290050302
195228828812.45544949911566920961.8379995376
195329529512.00252510191596894561.8473354935
195438738713.66440052931626868162.378803701
195568368317.52431514841656841924.1223003339
195667367318.25869727391686815523.9897664684
195758558515.61397531141716789123.4075239247
195858958915.14273346541746762723.371951973
195983583518.36696292171776736484.6996277129
196084484417.41692508091806710084.6714744626
196195495420.45664370381836910085.1935040827
196285385318.82351216081865380004.5727948193
19638611,36186120.25923949091892420004.5497299754
19648541,95085422.55342366291918889924.4504897915
196510082,125100823.2621544521943030085.1877735212
19669952,37799521.30176394971965600005.0620675621
196714962,975149621.6061711011987120007.5284834333
19684,4624,46221.486086263620070600022.2315227248
19696,1076,10719.427484641820267699230.131688554
19705,1525,15215.184151673420505200025.1253340616
19714,6084,60816.867287601320766099222.1900124603
19724,8014,80117.768766727520989600022.873232458
19734,0404,04016.147915285321190899219.0647879633
19742,8612,86110.926211788721385400013.3782861204
19752,2972,29710.236239875621597299210.6355891018
19762,2762,27611.543463939521803500810.4386906528
19772,2242,22410.431512631222023900810.0981203112
19782,1062,1069.37913964952225849929.4615543531
19792,1282,1288.92723348242250550089.4554661054
19801,8891,8898.83304899032277260008.2950563396
19812,3957438592,3958.463210955222996600010.4145830253
19822,5331,1201,4662,5337.346745558523218800010.9092631833
19832,5431,4012,3242,5439.642081816623430700810.8532818617
19842,5431,4362,5322,5439.429556230523634800010.75955794
19853,0014001,6993,00110.69130755123846600012.5846032558
19863,3365102,6063,33613.387709194524065100813.8623977839
19872,0325042,8072,03216.01486877032428040008.3688901336
19882,2586033,1332,25814.43991577172450209929.2155369284
19892,3668054,1912,36616.61362816982473420009.5657025495
19902,0747244,3862,07416.45663057812499729928.2968963303
19911,8779154,3291,87717.92014141912526649927.4288091324
19922,5741,2204,7602,57419.635856350925541000010.0779139423
19932,6631,3755,3012,66320.749768494925811900810.3169465148
19942,9971,5676,5042,99720.479745656726063699211.4987514896
19953,5101,8477,8253,51022.720700748526308200013.3418477889
19965,8481,8928,7475,84825.943956060126550200022.026199426
19977,8002,1729,6437,80030.955887308426804800029.0992658031
19987,8092,21710,5387,80936.007746974427050899228.867801925
19999,6149,61442.069362163627294499235.2232145003
200010,95210,95241.702508188527537200039.7716543439
20018,4238,42332.065171744727700000030.4079422383
20023,0986,60023.444141018728813907022.9056059631
Sheet2
Sheet3
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Types of MergersHorizontalinvolve two firms operating in the same kind of business activity, e.g. Daimler-ChryslerVerticaloccur between firms in different stages of production operationConglomerateoccur between firms engaged in unrelated types of business activityproduct-extension: broadens the product lines of firmsgeographic market-extension: between firms whose operations have been conducted in non-overlapping geographic areas
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Hypothesis about Mergers There are a big number of hypothesis as to why mergers occur, these can be grouped into two broad categories:
Neoclassical theories that assume that managers maximize profits or shareholder wealth and thus that mergers increase either market power or efficiencyNon-neoclassical or behavioral theories that posit some other motivation for mergers and/or other consequences.
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Neoclassical TheoriesMarket Power IncreasesEfficiency IncreasesNon-neoclassical or BehavioralSpeculative MotivesThe Adaptive Firm HypothesisThe Market for Corporate ControlThe Economic Disturbance HypothesisFinancial EfficienciesThe Capital Redeployment HypothesisThe Life-Cycle-Growth-Maximization HypothesisThe Winners Curse- Hubris Hypothesis
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(1a) Market Power IncreasesHorizontal Mergersfewer firms in an industry have greater incentives to cooperate and raise the priceIn a symmetric Cournot equilibrium, with homogeneous product and all firms having the same, constant unit cost c
H :Herfindahl index :price elasticity of demand for the industry
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Since a horizontal merger increases industry concentration, it increases H, it must also increase the industry price-cost margin and profits.
Salant, Switzer and Reynolds (1983)However, Salant et al. (1983) show that mergers in such a setting are not privately profitable. When all firms have identical costs, they all must have the same size.The above equation must hold before and after the merger. Since the immediate effect of the merger is to make the merged firm twice as big as ist competitors, it needs to shrink following the merger to return to the new size of ist rivals.The loss of profits to the merging firms from having to shrink to rejoin the symmetric Cournot equilibrium more than offsets the gain in profits from the increase in price cost margin caused by the increase in H.
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Vertical mergersby increasing the barriers to entry at one or more links in the vertical production chainExample: a firm which wished to enter into aluminum refining in the USA prior to the Second World War would have found that all known bauxite deposits were owned by ist main competitor ALCOA. ALCOA could easily foreclose the bauxite market to the entrant and thus created an entry barrier.Conglomerate mergersmultimarket contact (Scott, 1982, 1993)An increase in concentration leads to a greater increase in profits in a market in which the sellers also face one another in other markets than when such multimarket contact is not present. This motive may also be the cause of purposeful diversification mergers.
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(1b) Efficiency IncreasesHorizontal Mergers
ACOutputABCDE
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In such an industry, one would expect the merging firms to be smaller than non-merging firms, because the expected cost reductions are greter for pairs of small firms.
Empirical Evidence:In Belgium, Germany, USA, and UK merging firms were significantly larger than non-merging firmsIn France, the Netherlands, and Sweden merging pairs were in significantly different in size from randomly selected nonmerging companies.
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Vertical mergers
Can increase the efficiency of the merging firms by eliminating steps in the production process, which reduces the transaction costs from bargaining due to asset specificity
Asset Specificity refers to the relative lack of transferability of assets intended for use in a given transaction to other uses. Highly specific assets represent sunk costs that have relatively little value beyond their use in the context of a specific transaction. Williamson has suggested six main types of asset specificity: Site, physical asset, human asset, brand names, dedicated assets, temporal specificity
High asset specificity requires strong contracts or internalization to combat the threat of opportunism. Small subcontractors locating and investing next to only customer who could potentially turn to alternative suppliers (site- and physical asset specificity).
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General Motors and Fisher Body 1919-1926
After a 10 year contractual agreement was signed in 1919, GM's demand for closed-body cars increased to extent that it became unhappy with the contractual price provisions and "urged Fisher to locate its body plants adjacent to GM assembly plants, thereby to realize transportation and inventory economies." [Williamson, AJS, p.561]
Finally, Fisher Body was merged into GM in 1926 after Fisher had resisted GM's locational demands.
As Coase recalls:"I was told [by GM officials] that the main reason for the acquisition was to make sure that the body plants were located next to General Motors assembly plants." [Coase, "The Nature of the Firm: Origin", in: Williamson & Winter, eds., The Nature of the Firm. 1993, p.43.]
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Conglomerate Mergers
Economies of scope (ESC) arise when the production of two different products by the same firm leads to lower production costs for one or both products.
Example: warehousing and delivery of products
Formally, ESC is said to exist if the cost function is subadditive
C(x1, x2) < C(x1,0) + C(0, x2)
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(2a) Speculative MotivesStudies of early merger waves often mention promoters profits as a cause for mergers. During these waves men like J.P. Morgan often approached corporate managers and suggested a possible merger. They earned large fees for their advice and for other services they rendered to facilitate and finance the deals.Underwriters of the securities floated in the great merger that created the United States Steel Corp. In 1901, earned fees of $575.5 million over $1 billion in todays dollars (The Economist, April 27, 1991, p. 11).Michael Milken
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Fee Revenue from underwriting and M&A transactions in 1998 (Saunders and Srinivasan, 2001 )
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(2b) The Adaptive (Failing Firm) HypothesisDonald Dewey (1961):mergers as a civilized alternative to bankruptcyJohn McGowan (1965):An adaptive theory to account for why small firms are typically the targets in mergers and why the much more competitive US and UK economies had more mergers than the less competitive ones.Two implications:Mergers should follow a counter-cyclical pattern. Why dont we see merger waves during recessions?Profit rates of acquirers should be higher than targetsEmpirical EvidenceMost studies of mergers in the USA have found that acquired firms have the same average profit rates as similar non-acquired companiesDuring the conglomerate merger wave acquiring companies had below average profit rates and also profit rates lower than the firms they acquired.
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Characteristics of Acquiring and Target Companies, 1980-1998Gugler, Mueller, Yurtoglu, and Zulehner (2003)
Profit rateNumberof MergersAcquirerTargetUnited States of America1,9670.0290.019United Kingdom3790.0660.039Continental Europe1720.0350.033Japan160.0110.030Australia/N.Zealand/Canada1720.0240.027Rest of the World470.0520.013
All mergers2,7530.0340.023
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(2c) The Market for Corporate Control Mt: market value of the firm in year tKt: the value of the assets of the firm in year tIf Mt > Kt: the assets bundled together as a firm are worth more than their sum as measured by Kt.Marris (1963, 1964) called Mt / Kt the valuation ratio, Vt Tobin (1969) measured Kt as the replacement cost of the firms asset and called qt = Mt / Kt.Manne (1965):Buyers in the market for corporate control would step in whenever Vt falls short of its maximum value, and thus that this process ensures that corporate assets are managed by the most competent managers and those intend shareholder wealth maximization.
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Smiley (1976):Actual market values of acquired companies are compared to a projected value (control group).The market values of takeover targets began to fall below their predicted values on average 10 years before the takeover, and that the cumulative decline was 50% of predicted values.Other Studieshave found the shares of acquiring firms to be underperforming prior to their takeover (Mandelker, 1974; Langetieg, 1978; Asquith, 1983; Malatesta, 1983)Exception Dodd and Ruback (1977)
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(2d) The Economic Disturbance HypothesisGort (1969)a group of non-holders suddenly raises its expectations about firm Bs future profits. If these non-holders are managers of another firm, the transaction takes the form of a merger.Mergers under this hypothesis are more likely to happen in periods in which stock market experiences rapid changes in value.Consistent with the wave patternBut also consistent with merger waves during sudden drops in stock market values (even more intense merger activity!)
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(2e) Financial EfficienciesSavings on Borrowing Costs
Riskpooling
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(2f) The Capital Redeployment HypothesisWeston (1970)Similar to financial efficiencies argument, but goes beyond it by positing ongoing potential gains from a central management teams ability to monitor the investment opportunities of each division and shift capital across them.
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(2g) The Life-Cycle Growth Maximization HypothesisMueller (1969)Mergers are the quickest way to grow and diversify and thus an attractive way for managers with limited time horizons to achieve growth.Predictionsdiversification mergers by mature firms
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Direct Evidence by Harford (1999):Cash rich firms are more likely to acquireTheir acquisitions are more likely to be diversifyingThe abnormal price reaction is negative and lower for bidders who are cash richOperating performance deteriorates after mergers by cash rich companies
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(2h) The Winners Curse Hubris hypothesisThere are a number of biddersThe bidder with the highest valuation acquires the targetWith rational expectations, the expected true value of the target should be at the mean of the distributionThe winner will bid too much!Why bid then?Roll (1986):Because managers of acquiring firms suffer from hubris, excessive pride and arrogance.
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Testing Competing Hypotheses about the Determinants of MergersThree categories of hypothesesSynergye.g., a horizontal merger that increases the market power of the two merging companiesThe ynergistic gains arise from specific characteristics of the two merging firms.It is reasonable to assume that both firms share these gains, since each firms participation in the merger is required for there be any gains at all.A weaker assumption would be simply that the shareholders of both firms benefit from the merger.
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Market for Corporate ControlAll of the gains from the merger are tied to the target firm. In principle, any other firm could buy the target and replace its managers and obtain the wealth increase from its action.If the bidding for the target continues until the targets share price rises by enough to reflect all of the gains from replacing ist management, the bidders shareholders will experience no gain from the merger.Targets shareholders receive positive welath increasesBidders gains averge zero and are unrelated to the gains to the targets.
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Managerial DiscretionThere are no net gains from the mergersEach dollar paid to the target shareholders represents a dollar loss to the acquirers shareholders.Thus, the gains to the targets and bidders shareholders should be inversely related.It is not possible to distinguish a merger motivated by pure hubris from one stemming from managerial empirebuilding. In both cases, the targets gains are bidders losses. It is also possible, however, that managerial hubris may arise with mergers that do generate positive net wealth gains. Out of overoptimism the bidder pays too much for the target.In such a mixed case, we would expect a net positive gain from the merger, but a loss to the bidder. Moreover, the bigger the gain to the target, the more likely it is that the bidder overbid, and the bigger ist expected loss.
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Tests: Mueller and Sirower (2002)G: Gain to the bidder in dollars over a 24-month period beginning with the month of the mergerP: Premium paid to the targets shareholders in dollarsVT: Market value of the target firm
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The predicted coefficients
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Relationship between gains to acquirers and premia paid to targets
efN / R2efN / R2ContestedUncontested0.03-0.2144 / -0.0230.26-2.23124 / 0.053(0.06)(0.19)(0.97)(2.81)Multiple BiddersSingle Bidder0.48-1.9445 / 0.0510.09-1.34123 / 0.015(1.13)(1.84)(0.32)(1.68)Related (3 Digit)Unrelated (3 Digit)0.20-0.6895 / -0.0000.13-2.5473 / 0.052(0.79)(1.00)(0.31)(2.23)Cash OnlyNoncash (mixed)0.49-1.4690 / 0.0230.05-2.4878 / 0.057(1.42)(1.75)(0.16)(2.38)
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The mean gain to the bidders is -$50The variance around this mean is $ 3,579,664 millionAre you willing to play in a game in whichthe expected winnings are -$50you might lose as much as $10, 000,000You might also win as much as $13,000,000
These are summary statistics from the above sample, except that they are measured in millions.Why do managers of these firms undertake such gambles?Hubris? Averages do not apply themManagerial discretion? They are not gambling with other peoples money!