Reverse Breakup Fees and Antitrust Approval Albert H. Choi and - - PowerPoint PPT Presentation

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Reverse Breakup Fees and Antitrust Approval Albert H. Choi and - - PowerPoint PPT Presentation

Reverse Breakup Fees and Antitrust Approval Albert H. Choi and Abraham L. Wickelgren June 2019 Choi and Wickelgren Breakup Fees June 2019 1 / 1 Introduction Reverse breakup fees common in mergers Choi and Wickelgren Breakup Fees June 2019


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SLIDE 1

Reverse Breakup Fees and Antitrust Approval

Albert H. Choi and Abraham L. Wickelgren June 2019

Choi and Wickelgren Breakup Fees June 2019 1 / 1

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SLIDE 2

Introduction Reverse breakup fees common in mergers

Choi and Wickelgren Breakup Fees June 2019 2 / 1

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SLIDE 3

Introduction Reverse breakup fees common in mergers

Acquirer pays to the target if the merger rejected

Choi and Wickelgren Breakup Fees June 2019 2 / 1

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SLIDE 4

Introduction Reverse breakup fees common in mergers

Acquirer pays to the target if the merger rejected Many high profile examples

Choi and Wickelgren Breakup Fees June 2019 2 / 1

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SLIDE 5

Introduction Reverse breakup fees common in mergers

Acquirer pays to the target if the merger rejected Many high profile examples

AT&T paid $4 billion to T-Mobile

Choi and Wickelgren Breakup Fees June 2019 2 / 1

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SLIDE 6

Introduction Reverse breakup fees common in mergers

Acquirer pays to the target if the merger rejected Many high profile examples

AT&T paid $4 billion to T-Mobile Fox rejected Comcast’s higher offer, accepted Disney’s with $2.5 billion breakup fee

Choi and Wickelgren Breakup Fees June 2019 2 / 1

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SLIDE 7

Introduction Reverse breakup fees common in mergers

Acquirer pays to the target if the merger rejected Many high profile examples

AT&T paid $4 billion to T-Mobile Fox rejected Comcast’s higher offer, accepted Disney’s with $2.5 billion breakup fee Antitrust breakup fees in 12% of deals (24% challenged)

Choi and Wickelgren Breakup Fees June 2019 2 / 1

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SLIDE 8

Introduction Reverse breakup fees common in mergers

Acquirer pays to the target if the merger rejected Many high profile examples

AT&T paid $4 billion to T-Mobile Fox rejected Comcast’s higher offer, accepted Disney’s with $2.5 billion breakup fee Antitrust breakup fees in 12% of deals (24% challenged)

Possible effects of breakup fees

Choi and Wickelgren Breakup Fees June 2019 2 / 1

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SLIDE 9

Introduction Reverse breakup fees common in mergers

Acquirer pays to the target if the merger rejected Many high profile examples

AT&T paid $4 billion to T-Mobile Fox rejected Comcast’s higher offer, accepted Disney’s with $2.5 billion breakup fee Antitrust breakup fees in 12% of deals (24% challenged)

Possible effects of breakup fees

Signal to both target and competition authority

Choi and Wickelgren Breakup Fees June 2019 2 / 1

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SLIDE 10

Introduction Reverse breakup fees common in mergers

Acquirer pays to the target if the merger rejected Many high profile examples

AT&T paid $4 billion to T-Mobile Fox rejected Comcast’s higher offer, accepted Disney’s with $2.5 billion breakup fee Antitrust breakup fees in 12% of deals (24% challenged)

Possible effects of breakup fees

Signal to both target and competition authority

Raises the stakes, affecting litigation behavior

Choi and Wickelgren Breakup Fees June 2019 2 / 1

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SLIDE 11

Introduction Reverse breakup fees common in mergers

Acquirer pays to the target if the merger rejected Many high profile examples

AT&T paid $4 billion to T-Mobile Fox rejected Comcast’s higher offer, accepted Disney’s with $2.5 billion breakup fee Antitrust breakup fees in 12% of deals (24% challenged)

Possible effects of breakup fees

Signal to both target and competition authority

Raises the stakes, affecting litigation behavior Our signaling model w/ endogenous litigation spending captures these features to suggest if there is any rational for regulating breakup fees

Choi and Wickelgren Breakup Fees June 2019 2 / 1

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SLIDE 12

Preview of Results Main results

Choi and Wickelgren Breakup Fees June 2019 3 / 1

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SLIDE 13

Preview of Results Main results

Best case–Fixed litigation spending, asymmetric information

Choi and Wickelgren Breakup Fees June 2019 3 / 1

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SLIDE 14

Preview of Results Main results

Best case–Fixed litigation spending, asymmetric information Worst case–Full information, endogenous litigation spending

Choi and Wickelgren Breakup Fees June 2019 3 / 1

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SLIDE 15

Preview of Results Main results

Best case–Fixed litigation spending, asymmetric information Worst case–Full information, endogenous litigation spending Asymmetric information & endogenous litigation spending:

Choi and Wickelgren Breakup Fees June 2019 3 / 1

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SLIDE 16

Preview of Results Main results

Best case–Fixed litigation spending, asymmetric information Worst case–Full information, endogenous litigation spending Asymmetric information & endogenous litigation spending:

Supra-compensatory breakup fees could be socially desirable

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SLIDE 17

Preview of Results Main results

Best case–Fixed litigation spending, asymmetric information Worst case–Full information, endogenous litigation spending Asymmetric information & endogenous litigation spending:

Supra-compensatory breakup fees could be socially desirable Even if they are, equilibrium breakup fees exceed the social optimum

Choi and Wickelgren Breakup Fees June 2019 3 / 1

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SLIDE 18

Related literature Several papers on breakup fees paid by target

Choi and Wickelgren Breakup Fees June 2019 4 / 1

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SLIDE 19

Related literature Several papers on breakup fees paid by target

Mostly empirical: Bates and Lemmon (2003), Officer (2003), Boone and Mulherin (2007)

Choi and Wickelgren Breakup Fees June 2019 4 / 1

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SLIDE 20

Related literature Several papers on breakup fees paid by target

Mostly empirical: Bates and Lemmon (2003), Officer (2003), Boone and Mulherin (2007) Not related to regulatory approval: Che and Lewis (2007) bidder participation model

Choi and Wickelgren Breakup Fees June 2019 4 / 1

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SLIDE 21

Related literature Several papers on breakup fees paid by target

Mostly empirical: Bates and Lemmon (2003), Officer (2003), Boone and Mulherin (2007) Not related to regulatory approval: Che and Lewis (2007) bidder participation model

Reverse breakup fees papers

Choi and Wickelgren Breakup Fees June 2019 4 / 1

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SLIDE 22

Related literature Several papers on breakup fees paid by target

Mostly empirical: Bates and Lemmon (2003), Officer (2003), Boone and Mulherin (2007) Not related to regulatory approval: Che and Lewis (2007) bidder participation model

Reverse breakup fees papers

No game-theoretic analysis that we know of

Choi and Wickelgren Breakup Fees June 2019 4 / 1

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SLIDE 23

Related literature Several papers on breakup fees paid by target

Mostly empirical: Bates and Lemmon (2003), Officer (2003), Boone and Mulherin (2007) Not related to regulatory approval: Che and Lewis (2007) bidder participation model

Reverse breakup fees papers

No game-theoretic analysis that we know of Mostly about risk allocation and investment incentives: Afrasharipour (2010), Quinn (2010), Choi and Triantis (2010), Mahmudi, Virandi, and Zhao (2015), Coates, Palia, and Wu (2018)

Choi and Wickelgren Breakup Fees June 2019 4 / 1

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SLIDE 24

Model 3 players: Acquirer (A), Target (T), Regulator (R)

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SLIDE 25

Model 3 players: Acquirer (A), Target (T), Regulator (R)

Timeline

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SLIDE 26

Model 3 players: Acquirer (A), Target (T), Regulator (R)

Timeline

Period 0 : A learns type, t ∈ {ac, pc};ac-type occurs with probability q

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SLIDE 27

Model 3 players: Acquirer (A), Target (T), Regulator (R)

Timeline

Period 0 : A learns type, t ∈ {ac, pc};ac-type occurs with probability q Period 1: A makes take it or leave it offer {p, b} to T

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SLIDE 28

Model 3 players: Acquirer (A), Target (T), Regulator (R)

Timeline

Period 0 : A learns type, t ∈ {ac, pc};ac-type occurs with probability q Period 1: A makes take it or leave it offer {p, b} to T Period 2: R observes contract & costless signal, s ∈ {sh, sl},

  • f whether the merger is ac or not

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SLIDE 29

Model 3 players: Acquirer (A), Target (T), Regulator (R)

Timeline

Period 0 : A learns type, t ∈ {ac, pc};ac-type occurs with probability q Period 1: A makes take it or leave it offer {p, b} to T Period 2: R observes contract & costless signal, s ∈ {sh, sl},

  • f whether the merger is ac or not

Probability s = sh if t = i is hi

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SLIDE 30

Model 3 players: Acquirer (A), Target (T), Regulator (R)

Timeline

Period 0 : A learns type, t ∈ {ac, pc};ac-type occurs with probability q Period 1: A makes take it or leave it offer {p, b} to T Period 2: R observes contract & costless signal, s ∈ {sh, sl},

  • f whether the merger is ac or not

Probability s = sh if t = i is hi 0 < hpc < hac < 1 : signal is informative but imperfect

Choi and Wickelgren Breakup Fees June 2019 5 / 1

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SLIDE 31

Model 3 players: Acquirer (A), Target (T), Regulator (R)

Timeline

Period 0 : A learns type, t ∈ {ac, pc};ac-type occurs with probability q Period 1: A makes take it or leave it offer {p, b} to T Period 2: R observes contract & costless signal, s ∈ {sh, sl},

  • f whether the merger is ac or not

Probability s = sh if t = i is hi 0 < hpc < hac < 1 : signal is informative but imperfect

Period 3: If R challenges, A & R litigate; court blocks or allows

Choi and Wickelgren Breakup Fees June 2019 5 / 1

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SLIDE 32

Model 3 players: Acquirer (A), Target (T), Regulator (R)

Timeline

Period 0 : A learns type, t ∈ {ac, pc};ac-type occurs with probability q Period 1: A makes take it or leave it offer {p, b} to T Period 2: R observes contract & costless signal, s ∈ {sh, sl},

  • f whether the merger is ac or not

Probability s = sh if t = i is hi 0 < hpc < hac < 1 : signal is informative but imperfect

Period 3: If R challenges, A & R litigate; court blocks or allows

R & pcA spending fixed (φ and ψpc); acA spending (ψac) endogenous

Choi and Wickelgren Breakup Fees June 2019 5 / 1

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SLIDE 33

Model 3 players: Acquirer (A), Target (T), Regulator (R)

Timeline

Period 0 : A learns type, t ∈ {ac, pc};ac-type occurs with probability q Period 1: A makes take it or leave it offer {p, b} to T Period 2: R observes contract & costless signal, s ∈ {sh, sl},

  • f whether the merger is ac or not

Probability s = sh if t = i is hi 0 < hpc < hac < 1 : signal is informative but imperfect

Period 3: If R challenges, A & R litigate; court blocks or allows

R & pcA spending fixed (φ and ψpc); acA spending (ψac) endogenous R never wins against pcA;R wins against acA with probability π(ψac);π′ < 0, π′′ > 0.

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SLIDE 34

Model–Payoffs

Offer rejected

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SLIDE 35

Model–Payoffs

Offer rejected

T gets v; A gets 0; R gets 0

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SLIDE 36

Model–Payoffs

Offer rejected

T gets v; A gets 0; R gets 0

Offer accepted

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SLIDE 37

Model–Payoffs

Offer rejected

T gets v; A gets 0; R gets 0

Offer accepted

No challenge: T gets p, A gets ui − p, R gets B or −L

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SLIDE 38

Model–Payoffs

Offer rejected

T gets v; A gets 0; R gets 0

Offer accepted

No challenge: T gets p, A gets ui − p, R gets B or −L Approved: T gets p, A gets ui − p − ψi, R gets

B − φ − zψpc or −L − φ − zψac

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SLIDE 39

Model–Payoffs

Offer rejected

T gets v; A gets 0; R gets 0

Offer accepted

No challenge: T gets p, A gets ui − p, R gets B or −L Approved: T gets p, A gets ui − p − ψi, R gets

B − φ − zψpc or −L − φ − zψac

Rejected: T gets v + b,A gets −b − ψac,R gets −φ − zψac

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SLIDE 40

Litigation Stage A’s litigation strategy

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SLIDE 41

Litigation Stage A’s litigation strategy

pcA spends ψpc and wins

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SLIDE 42

Litigation Stage A’s litigation strategy

pcA spends ψpc and wins

acA chooses ψac to maximize

(1 − π(ψac ))(uac − p) − π(ψac)b − ψac

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SLIDE 43

Litigation Stage A’s litigation strategy

pcA spends ψpc and wins

acA chooses ψac to maximize

(1 − π(ψac ))(uac − p) − π(ψac)b − ψac

FOC: −(ψac)(uac + b − p) = 1 implicitly defines ψ∗

ac(b, p)

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SLIDE 44

Litigation Stage A’s litigation strategy

pcA spends ψpc and wins

acA chooses ψac to maximize

(1 − π(ψac ))(uac − p) − π(ψac)b − ψac

FOC: −(ψac)(uac + b − p) = 1 implicitly defines ψ∗

ac(b, p)

R challenge decision

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SLIDE 45

Litigation Stage A’s litigation strategy

pcA spends ψpc and wins

acA chooses ψac to maximize

(1 − π(ψac ))(uac − p) − π(ψac)b − ψac

FOC: −(ψac)(uac + b − p) = 1 implicitly defines ψ∗

ac(b, p)

R challenge decision

Define qR as R’s posterior belief that merger is anti-competitive

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Litigation Stage A’s litigation strategy

pcA spends ψpc and wins

acA chooses ψac to maximize

(1 − π(ψac ))(uac − p) − π(ψac)b − ψac

FOC: −(ψac)(uac + b − p) = 1 implicitly defines ψ∗

ac(b, p)

R challenge decision

Define qR as R’s posterior belief that merger is anti-competitive

Challenge if and only if: qR(π(ψ∗

ac(b, p))L − zψ∗ ac(b, p)) − (1 − qR)zψpc − φ ≥ 0

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SLIDE 47

Benchmark 1: Fixed Litigation Costs Fix ψac ≥ ψpc :b doesn’t affect it

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SLIDE 48

Benchmark 1: Fixed Litigation Costs Fix ψac ≥ ψpc :b doesn’t affect it

R makes inferences about A’s type (but not litigation

effort) from b

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SLIDE 49

Benchmark 1: Fixed Litigation Costs Fix ψac ≥ ψpc :b doesn’t affect it

R makes inferences about A’s type (but not litigation

effort) from b Assume in pooling eqm, R challenges iff s = sh

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SLIDE 50

Benchmark 1: Fixed Litigation Costs Fix ψac ≥ ψpc :b doesn’t affect it

R makes inferences about A’s type (but not litigation

effort) from b Assume in pooling eqm, R challenges iff s = sh

π(ψac) > 0implies acA more likely to pay b than pcA

Choi and Wickelgren Breakup Fees June 2019 8 / 1

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SLIDE 51

Benchmark 1: Fixed Litigation Costs Fix ψac ≥ ψpc :b doesn’t affect it

R makes inferences about A’s type (but not litigation

effort) from b Assume in pooling eqm, R challenges iff s = sh

π(ψac) > 0implies acA more likely to pay b than pcA

Pooling equilibrium for small b

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SLIDE 52

Benchmark 1: Fixed Litigation Costs Fix ψac ≥ ψpc :b doesn’t affect it

R makes inferences about A’s type (but not litigation

effort) from b Assume in pooling eqm, R challenges iff s = sh

π(ψac) > 0implies acA more likely to pay b than pcA

Pooling equilibrium for small b

Larger bworse for acA than for pcA, but

Choi and Wickelgren Breakup Fees June 2019 8 / 1

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SLIDE 53

Benchmark 1: Fixed Litigation Costs Fix ψac ≥ ψpc :b doesn’t affect it

R makes inferences about A’s type (but not litigation

effort) from b Assume in pooling eqm, R challenges iff s = sh

π(ψac) > 0implies acA more likely to pay b than pcA

Pooling equilibrium for small b

Larger bworse for acA than for pcA, but Revealing ac type implies offer (0, v)and always challenged, instead of challenged with probability hac

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SLIDE 54

Benchmark 1: Fixed Litigation Costs Fix ψac ≥ ψpc :b doesn’t affect it

R makes inferences about A’s type (but not litigation

effort) from b Assume in pooling eqm, R challenges iff s = sh

π(ψac) > 0implies acA more likely to pay b than pcA

Pooling equilibrium for small b

Larger bworse for acA than for pcA, but Revealing ac type implies offer (0, v)and always challenged, instead of challenged with probability hac

(1 − hacπac(ψac))(uac − p) − hacπac(ψac)b − hacψac ≥ (1 − π(ψac))(uac − v) − ψacif b small enough

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Benchmark 1: Fixed Litigation Costs Partial pooling for large b

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SLIDE 56

Benchmark 1: Fixed Litigation Costs Partial pooling for large b

If b large & R challenges w/ sh: acA separates rather than risk large breakup fee

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SLIDE 57

Benchmark 1: Fixed Litigation Costs Partial pooling for large b

If b large & R challenges w/ sh: acA separates rather than risk large breakup fee Complete separation impossible: R won’t challenge if only

pcA offers high b contract

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SLIDE 58

Benchmark 1: Fixed Litigation Costs Partial pooling for large b

If b large & R challenges w/ sh: acA separates rather than risk large breakup fee Complete separation impossible: R won’t challenge if only

pcA offers high b contract acA mixes between high bcontract and revealing contract

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SLIDE 59

Benchmark 1: Fixed Litigation Costs Partial pooling for large b

If b large & R challenges w/ sh: acA separates rather than risk large breakup fee Complete separation impossible: R won’t challenge if only

pcA offers high b contract acA mixes between high bcontract and revealing contract R mixes with high b contract & sh; probability of challenge

decreasing in b

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SLIDE 60

Benchmark 1: Fixed Litigation Costs Partial pooling for large b

If b large & R challenges w/ sh: acA separates rather than risk large breakup fee Complete separation impossible: R won’t challenge if only

pcA offers high b contract acA mixes between high bcontract and revealing contract R mixes with high b contract & sh; probability of challenge

decreasing in b

Partial pooling raises R welfare

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SLIDE 61

Benchmark 1: Fixed Litigation Costs Partial pooling for large b

If b large & R challenges w/ sh: acA separates rather than risk large breakup fee Complete separation impossible: R won’t challenge if only

pcA offers high b contract acA mixes between high bcontract and revealing contract R mixes with high b contract & sh; probability of challenge

decreasing in b

Partial pooling raises R welfare

R welfare equivalent to challenging all mergers with high

signal and some acA with low signal

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SLIDE 62

Benchmark 1: Fixed Litigation Costs Partial pooling for large b

If b large & R challenges w/ sh: acA separates rather than risk large breakup fee Complete separation impossible: R won’t challenge if only

pcA offers high b contract acA mixes between high bcontract and revealing contract R mixes with high b contract & sh; probability of challenge

decreasing in b

Partial pooling raises R welfare

R welfare equivalent to challenging all mergers with high

signal and some acA with low signal Pooling equilibrium only has challenges from all mergers with high signal

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Benchmark 2: Complete Information

R behavior

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SLIDE 64

Benchmark 2: Complete Information

R behavior

Never challenge pcA

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SLIDE 65

Benchmark 2: Complete Information

R behavior

Never challenge pcA Challenge acA iff π(ψ∗

ac(b, p)) ≥ (zψ∗ ac(b, p) + φ)/L

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SLIDE 66

Benchmark 2: Complete Information

R behavior

Never challenge pcA Challenge acA iff π(ψ∗

ac(b, p)) ≥ (zψ∗ ac(b, p) + φ)/L

ψ∗

ac(b, p). is increasing in b, so

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SLIDE 67

Benchmark 2: Complete Information

R behavior

Never challenge pcA Challenge acA iff π(ψ∗

ac(b, p)) ≥ (zψ∗ ac(b, p) + φ)/L

ψ∗

ac(b, p). is increasing in b, so

π is decreasing in b

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SLIDE 68

Benchmark 2: Complete Information

R behavior

Never challenge pcA Challenge acA iff π(ψ∗

ac(b, p)) ≥ (zψ∗ ac(b, p) + φ)/L

ψ∗

ac(b, p). is increasing in b, so

π is decreasing in b

There might exist a b∗∗ such that

π(ψ∗

ac(b∗∗, p)) = (zψ∗ ac(b∗∗, p) + φ)/L

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SLIDE 69

Benchmark 2: Complete Information

R behavior

Never challenge pcA Challenge acA iff π(ψ∗

ac(b, p)) ≥ (zψ∗ ac(b, p) + φ)/L

ψ∗

ac(b, p). is increasing in b, so

π is decreasing in b

There might exist a b∗∗ such that

π(ψ∗

ac(b∗∗, p)) = (zψ∗ ac(b∗∗, p) + φ)/L

Optimal merger contracts

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SLIDE 70

Benchmark 2: Complete Information

R behavior

Never challenge pcA Challenge acA iff π(ψ∗

ac(b, p)) ≥ (zψ∗ ac(b, p) + φ)/L

ψ∗

ac(b, p). is increasing in b, so

π is decreasing in b

There might exist a b∗∗ such that

π(ψ∗

ac(b∗∗, p)) = (zψ∗ ac(b∗∗, p) + φ)/L

Optimal merger contracts

pcA indifferent because never challenged

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SLIDE 71

Benchmark 2: Complete Information

R behavior

Never challenge pcA Challenge acA iff π(ψ∗

ac(b, p)) ≥ (zψ∗ ac(b, p) + φ)/L

ψ∗

ac(b, p). is increasing in b, so

π is decreasing in b

There might exist a b∗∗ such that

π(ψ∗

ac(b∗∗, p)) = (zψ∗ ac(b∗∗, p) + φ)/L

Optimal merger contracts

pcA indifferent because never challenged acA offers b > b∗∗ if possible and is never challenged,

  • therwise

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SLIDE 72

Benchmark 2: Complete Information

R behavior

Never challenge pcA Challenge acA iff π(ψ∗

ac(b, p)) ≥ (zψ∗ ac(b, p) + φ)/L

ψ∗

ac(b, p). is increasing in b, so

π is decreasing in b

There might exist a b∗∗ such that

π(ψ∗

ac(b∗∗, p)) = (zψ∗ ac(b∗∗, p) + φ)/L

Optimal merger contracts

pcA indifferent because never challenged acA offers b > b∗∗ if possible and is never challenged,

  • therwise

acA offers (0, v)

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SLIDE 73

Implications of Benchmarks

Informational effects of breakup fees are desirable

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SLIDE 74

Implications of Benchmarks

Informational effects of breakup fees are desirable

They can help identify anti-competitive mergers

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SLIDE 75

Implications of Benchmarks

Informational effects of breakup fees are desirable

They can help identify anti-competitive mergers Not perfect, but better than with small or no breakup fees

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SLIDE 76

Implications of Benchmarks

Informational effects of breakup fees are desirable

They can help identify anti-competitive mergers Not perfect, but better than with small or no breakup fees

Litigation effects are undesirable

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SLIDE 77

Implications of Benchmarks

Informational effects of breakup fees are desirable

They can help identify anti-competitive mergers Not perfect, but better than with small or no breakup fees

Litigation effects are undesirable

Raising the cost of losing a challenge commits acquirer to fight harder

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SLIDE 78

Implications of Benchmarks

Informational effects of breakup fees are desirable

They can help identify anti-competitive mergers Not perfect, but better than with small or no breakup fees

Litigation effects are undesirable

Raising the cost of losing a challenge commits acquirer to fight harder Makes it harder to block anti-competitive mergers

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SLIDE 79

Implications of Benchmarks

Informational effects of breakup fees are desirable

They can help identify anti-competitive mergers Not perfect, but better than with small or no breakup fees

Litigation effects are undesirable

Raising the cost of losing a challenge commits acquirer to fight harder Makes it harder to block anti-competitive mergers

What happens if both effects are present?

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SLIDE 80

Full Model Equilibria Assumption: If pooling at b = 0,R challenges if and

  • nly if s = sh

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SLIDE 81

Full Model Equilibria Assumption: If pooling at b = 0,R challenges if and

  • nly if s = sh

Pooling equilibrium with no challenges

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SLIDE 82

Full Model Equilibria Assumption: If pooling at b = 0,R challenges if and

  • nly if s = sh

Pooling equilibrium with no challenges

R indifferent to challenging: q∗

R = zψpc+φ πac(ψ∗

ac)L−z(ψ∗ ac−ψpc) Choi and Wickelgren Breakup Fees June 2019 12 / 1

slide-83
SLIDE 83

Full Model Equilibria Assumption: If pooling at b = 0,R challenges if and

  • nly if s = sh

Pooling equilibrium with no challenges

R indifferent to challenging: q∗

R = zψpc+φ πac(ψ∗

ac)L−z(ψ∗ ac−ψpc)

Let ¯

ψ∗

ac satisfy this for q∗ R given by pooling & sh

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SLIDE 84

Full Model Equilibria Assumption: If pooling at b = 0,R challenges if and

  • nly if s = sh

Pooling equilibrium with no challenges

R indifferent to challenging: q∗

R = zψpc+φ πac(ψ∗

ac)L−z(ψ∗ ac−ψpc)

Let ¯

ψ∗

ac satisfy this for q∗ R given by pooling & sh

If there is a b∗ large enough that ψ∗

ac(b∗, p) ≥ ¯

ψ∗

ac, R won’t challenge

for any b > b∗

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SLIDE 85

Full Model Equilibria Assumption: If pooling at b = 0,R challenges if and

  • nly if s = sh

Pooling equilibrium with no challenges

R indifferent to challenging: q∗

R = zψpc+φ πac(ψ∗

ac)L−z(ψ∗ ac−ψpc)

Let ¯

ψ∗

ac satisfy this for q∗ R given by pooling & sh

If there is a b∗ large enough that ψ∗

ac(b∗, p) ≥ ¯

ψ∗

ac, R won’t challenge

for any b > b∗ Both types will offer a contract with b > b∗

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SLIDE 86

Full Model Equilibria Pooling equilibrium with challenges

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SLIDE 87

Full Model Equilibria Pooling equilibrium with challenges

There exists a ˆ

b s.t., acA is indifferent between

Choi and Wickelgren Breakup Fees June 2019 13 / 1

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SLIDE 88

Full Model Equilibria Pooling equilibrium with challenges

There exists a ˆ

b s.t., acA is indifferent between

Pooling (challenged w/ probability hac) and

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SLIDE 89

Full Model Equilibria Pooling equilibrium with challenges

There exists a ˆ

b s.t., acA is indifferent between

Pooling (challenged w/ probability hac) and Offering b = 0 and challenged for sure

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SLIDE 90

Full Model Equilibria Pooling equilibrium with challenges

There exists a ˆ

b s.t., acA is indifferent between

Pooling (challenged w/ probability hac) and Offering b = 0 and challenged for sure

If b ≤ ˆ b: pooling eqm & R challenges iff s = sh

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SLIDE 91

Full Model Equilibria Pooling equilibrium with challenges

There exists a ˆ

b s.t., acA is indifferent between

Pooling (challenged w/ probability hac) and Offering b = 0 and challenged for sure

If b ≤ ˆ b: pooling eqm & R challenges iff s = sh

Partial pooling equilibrium

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SLIDE 92

Full Model Equilibria Pooling equilibrium with challenges

There exists a ˆ

b s.t., acA is indifferent between

Pooling (challenged w/ probability hac) and Offering b = 0 and challenged for sure

If b ≤ ˆ b: pooling eqm & R challenges iff s = sh

Partial pooling equilibrium

If b > ˆ

b, only partial pooling possible

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SLIDE 93

Full Model Equilibria Pooling equilibrium with challenges

There exists a ˆ

b s.t., acA is indifferent between

Pooling (challenged w/ probability hac) and Offering b = 0 and challenged for sure

If b ≤ ˆ b: pooling eqm & R challenges iff s = sh

Partial pooling equilibrium

If b > ˆ

b, only partial pooling possible pcA offers (b, p)and acA mixes between (b, p)and (0, v)

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SLIDE 94

Full Model Equilibria Pooling equilibrium with challenges

There exists a ˆ

b s.t., acA is indifferent between

Pooling (challenged w/ probability hac) and Offering b = 0 and challenged for sure

If b ≤ ˆ b: pooling eqm & R challenges iff s = sh

Partial pooling equilibrium

If b > ˆ

b, only partial pooling possible pcA offers (b, p)and acA mixes between (b, p)and (0, v) R always challenges (0, v), sometimes challenges (b, p)if sh

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SLIDE 95

Full Model Equilibria Pooling equilibrium with challenges

There exists a ˆ

b s.t., acA is indifferent between

Pooling (challenged w/ probability hac) and Offering b = 0 and challenged for sure

If b ≤ ˆ b: pooling eqm & R challenges iff s = sh

Partial pooling equilibrium

If b > ˆ

b, only partial pooling possible pcA offers (b, p)and acA mixes between (b, p)and (0, v) R always challenges (0, v), sometimes challenges (b, p)if sh

Probability of challenge decreasing in b

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SLIDE 96

Full Model Equilibria Pooling equilibrium with challenges

There exists a ˆ

b s.t., acA is indifferent between

Pooling (challenged w/ probability hac) and Offering b = 0 and challenged for sure

If b ≤ ˆ b: pooling eqm & R challenges iff s = sh

Partial pooling equilibrium

If b > ˆ

b, only partial pooling possible pcA offers (b, p)and acA mixes between (b, p)and (0, v) R always challenges (0, v), sometimes challenges (b, p)if sh

Probability of challenge decreasing in b Probability acA offers (b, p)drops at ˆ

b & then increases in b

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SLIDE 97

Welfare Comparison Pooling with no challenges worst

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SLIDE 98

Welfare Comparison Pooling with no challenges worst Pooling with challenges best at b = 0

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SLIDE 99

Welfare Comparison Pooling with no challenges worst Pooling with challenges best at b = 0

Larger b increases litigation costs & harder to block ac mergers

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SLIDE 100

Welfare Comparison Pooling with no challenges worst Pooling with challenges best at b = 0

Larger b increases litigation costs & harder to block ac mergers

Partial pooling best at ˆ

b

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SLIDE 101

Welfare Comparison Pooling with no challenges worst Pooling with challenges best at b = 0

Larger b increases litigation costs & harder to block ac mergers

Partial pooling best at ˆ

b

Probability of separation largest at ˆ

b

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SLIDE 102

Welfare Comparison Pooling with no challenges worst Pooling with challenges best at b = 0

Larger b increases litigation costs & harder to block ac mergers

Partial pooling best at ˆ

b

Probability of separation largest at ˆ

b R welfare comes from when acA separates

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SLIDE 103

Welfare Comparison Pooling with no challenges worst Pooling with challenges best at b = 0

Larger b increases litigation costs & harder to block ac mergers

Partial pooling best at ˆ

b

Probability of separation largest at ˆ

b R welfare comes from when acA separates pcA wants largest b because min challenge probability

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SLIDE 104

Welfare Comparison Pooling with no challenges worst Pooling with challenges best at b = 0

Larger b increases litigation costs & harder to block ac mergers

Partial pooling best at ˆ

b

Probability of separation largest at ˆ

b R welfare comes from when acA separates pcA wants largest b because min challenge probability

Comparing b = ˆ

b and b = 0

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SLIDE 105

Welfare Comparison Pooling with no challenges worst Pooling with challenges best at b = 0

Larger b increases litigation costs & harder to block ac mergers

Partial pooling best at ˆ

b

Probability of separation largest at ˆ

b R welfare comes from when acA separates pcA wants largest b because min challenge probability

Comparing b = ˆ

b and b = 0

Either could be better

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SLIDE 106

Welfare Comparison Pooling with no challenges worst Pooling with challenges best at b = 0

Larger b increases litigation costs & harder to block ac mergers

Partial pooling best at ˆ

b

Probability of separation largest at ˆ

b R welfare comes from when acA separates pcA wants largest b because min challenge probability

Comparing b = ˆ

b and b = 0

Either could be better Pooling better w/ smaller L and hac close to one

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SLIDE 107

Welfare Comparison Pooling with no challenges worst Pooling with challenges best at b = 0

Larger b increases litigation costs & harder to block ac mergers

Partial pooling best at ˆ

b

Probability of separation largest at ˆ

b R welfare comes from when acA separates pcA wants largest b because min challenge probability

Comparing b = ˆ

b and b = 0

Either could be better Pooling better w/ smaller L and hac close to one Partial pooling better w/ larger L and hpc close to zero

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SLIDE 108

Conclusion Model justifies some regulation of breakup fees

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SLIDE 109

Conclusion Model justifies some regulation of breakup fees

Supra-compensatory breakup fees could be optimal (to help signal type), but may not be

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SLIDE 110

Conclusion Model justifies some regulation of breakup fees

Supra-compensatory breakup fees could be optimal (to help signal type), but may not be Parties have incentive to choose larger breakup fees than are socially optimal

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SLIDE 111

Conclusion Model justifies some regulation of breakup fees

Supra-compensatory breakup fees could be optimal (to help signal type), but may not be Parties have incentive to choose larger breakup fees than are socially optimal

Robustness

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SLIDE 112

Conclusion Model justifies some regulation of breakup fees

Supra-compensatory breakup fees could be optimal (to help signal type), but may not be Parties have incentive to choose larger breakup fees than are socially optimal

Robustness

Relax pcA always wins at trial

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SLIDE 113

Conclusion Model justifies some regulation of breakup fees

Supra-compensatory breakup fees could be optimal (to help signal type), but may not be Parties have incentive to choose larger breakup fees than are socially optimal

Robustness

Relax pcA always wins at trial

Challenging less desirable

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SLIDE 114

Conclusion Model justifies some regulation of breakup fees

Supra-compensatory breakup fees could be optimal (to help signal type), but may not be Parties have incentive to choose larger breakup fees than are socially optimal

Robustness

Relax pcA always wins at trial

Challenging less desirable Easier to have breakup fee that deters challenges

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SLIDE 115

Conclusion Model justifies some regulation of breakup fees

Supra-compensatory breakup fees could be optimal (to help signal type), but may not be Parties have incentive to choose larger breakup fees than are socially optimal

Robustness

Relax pcA always wins at trial

Challenging less desirable Easier to have breakup fee that deters challenges Other comparisons unaffected

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SLIDE 116

Conclusion Model justifies some regulation of breakup fees

Supra-compensatory breakup fees could be optimal (to help signal type), but may not be Parties have incentive to choose larger breakup fees than are socially optimal

Robustness

Relax pcA always wins at trial

Challenging less desirable Easier to have breakup fee that deters challenges Other comparisons unaffected

Renegotiation

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SLIDE 117

Conclusion Model justifies some regulation of breakup fees

Supra-compensatory breakup fees could be optimal (to help signal type), but may not be Parties have incentive to choose larger breakup fees than are socially optimal

Robustness

Relax pcA always wins at trial

Challenging less desirable Easier to have breakup fee that deters challenges Other comparisons unaffected

Renegotiation

If R challenges, high b not jointly optimal, but...

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slide-118
SLIDE 118

Conclusion Model justifies some regulation of breakup fees

Supra-compensatory breakup fees could be optimal (to help signal type), but may not be Parties have incentive to choose larger breakup fees than are socially optimal

Robustness

Relax pcA always wins at trial

Challenging less desirable Easier to have breakup fee that deters challenges Other comparisons unaffected

Renegotiation

If R challenges, high b not jointly optimal, but... Renegotiation never happens

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slide-119
SLIDE 119

Conclusion Model justifies some regulation of breakup fees

Supra-compensatory breakup fees could be optimal (to help signal type), but may not be Parties have incentive to choose larger breakup fees than are socially optimal

Robustness

Relax pcA always wins at trial

Challenging less desirable Easier to have breakup fee that deters challenges Other comparisons unaffected

Renegotiation

If R challenges, high b not jointly optimal, but... Renegotiation never happens Asymmetric information may impede it

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SLIDE 120

Conclusion Model justifies some regulation of breakup fees

Supra-compensatory breakup fees could be optimal (to help signal type), but may not be Parties have incentive to choose larger breakup fees than are socially optimal

Robustness

Relax pcA always wins at trial

Challenging less desirable Easier to have breakup fee that deters challenges Other comparisons unaffected

Renegotiation

If R challenges, high b not jointly optimal, but... Renegotiation never happens Asymmetric information may impede it R challenge decision never really final until all costs spent

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