1. Lecture VI: Principal-Agent Models Recommended Reading (beyond syllabus): Milgrom & Roberts, Economics, Organization & Management, Chs 6, 7, 12.

2. Lecture VI: Principal-Agent Models The Problem: –Delegation leads to agency loss –Undercuts efficiency, offsets gains from trade or specialization Sources: 1.Divergent preferences 2.Information Asymmetry: expertise, In Strom’s (2000) terms: –Ex ante: Hidden Information (adverse selection) See Akerlof (1970) –Ex post: Hidden Action (moral hazard) See Grossman & Hart (1983)

3. Lecture VI: Principal-Agent Models Solutions (again, Strom): 1.Screening Revelation of type 2.Contract Design Incentive compatibility 3.Monitoring Reduce information asymmetry 4.Institutional checks veto power competition

4. Akerloff: The Market For Lemons Information asymmetry undercuts efficient exchange Creates divergence between price & quality Bad quality drives out good until market collapses Example: market for used cars –Some fraction, q, cars are good, 1-q are lemons –People prefer good cars to lemons –Only know if you own a lemon after sale & driving it –Thus, we expect used car market to have > 1-q lemons…. If a used car were good, why is it for sale…. at that price?

5. Akerloff: The Market For Lemons 1.Two types of traders, with utility functions: U 1 = M +  x i U 2 = M +  3 / 2 x i where, –x i is utility from the quality of the i th car –M is utility from other goods 2.M costs 1 unit (say $1) 3.Type 1s own all N cars 4.Car quality, x ~ U[0, 2] & observed only by type 1s

6. Akerloff: The Market For Lemons Type 2s get more utility from cars than type 1s A type 1 could sell a car to a type 2 for a price, p  (1, 3/2): –Type 1 surrenders 1 unit of x, but can afford > 1 unit of M –Type 2 surrenders p units of M, buts gets more utility from x But as Type 1’s MRS between M & x = 1, type 1s sell only x < 1p 02 x ≥ 1 not put up for sale x < 1 put up for sale  μ x-used = 1/2 μ x = 1

7. Akerloff: The Market For Lemons Average quality of cars on market is p/2 Type 2s willing to trade up to p = 3 / 2 × p/2 = 3p/4 This price does not compensate Type 1s enough Bad quality good drive out good & market collapses 02 x ≥ 1 not put up for sale x < 1 put up for sale  μ x-used = 1/2 μ x = 1

8. Akerloff: The Market For Lemons 1.Bad quality good drive out good & market collapses: adverse selection 2.More realistically: i.(Low) Price of used good reflects information asymmetry as well as wear & tear ii.Given low resale price, less of good offered for resale; inefficient

9. Adverse Selection & Politics How do voters know if politician is honest? How does PM know if Cabinet Minister is loyal? How do party delegates know which leadership contestant is a “winner”? Is applicant to civil service competent, discrete, non- partisan?

10. Technology of Adverse Selection Already introduced: Signalling game –Agent (type 1, 2, … N) send costly signal –Principal updates on type via Baye’s Rule (if possible)  Pooling  Separating  Semi-separating –Low quality agents want to pool; principal wants agents to separate –Incentive compatibility: Principal can structure contract (i.e. payoffs) to compensate high quality but not low quality agents for costly signalling.

11. Moral Hazard No types here, but information asymmetry still a problem Agent has incentives for ex post opportunism: shirking, sabotage Political Examples: i.Ministers prefer to “coast” (i.e., shirk) rather than advance potentially controversial policies (Dewan & Myatt 2007) ii.Bureaucrats undermine political initiatives that upset a comfortable status quo or maximize budgets not efficiency (Niskanen 1971) iii.Coalition partners alter pre-election policy agreements

12. Moral Hazard: Typical Game Structure 1.Principal delegates production of a good x to agent in exchange for some payment, p –e.g., Cabinet delegates policy implementation to civil service & provides ministries with budgets to do so 2.Production of x is costly to agent –Political science analog: moving policy from sq to x requires civil servants to exert effort (e) or move policy from their ideal point 3.  U P /  x > 0,  U P /  p 0

13. Moral Hazard: Typical Game Structure Agent knows more about production process than principal –Example 1: x = effort + θ, θ ~ N (μ,σ 2 ) –Example 2: x = (1-θ)(effort) + θbudget, θ ~ N(μ,σ 2 ) –Agent observes θ: higher θ allows less effort, can maintain effort and obtain larger budget & keep surplus, etc. depending on U A –Principal knows f(x) & θ ~ N(μ,σ 2 ), but sees only x Can Principal structure payment scheme to limit Agent’s opportunism & enhance efficiency?

14. Moral Hazard: Typical Game Structure Typical modelling trick: –Principal is risk neutral in p, Agent is risk averse in p –Mathematically, U P is linear in p, U A quadratic in p Utility p UAUA UPUP

15. An Example: Indridason & Kam (2007) Puzzle: Why do PMs reshuffle ministers frequently if reshuffling only serves to undercut ministerial experience & amplify civil servants’ informational advantage? Argument: 1.Ministers have incentives to use their portfolios in manner that runs contrary to PM & cabinet’s collective interests, e.g., run up budget’s to boost their own profile, make a leadership run, etc. 2.By reshuffling ministers, PM can rein in ministers’ propensity to deviate from cabinet & PM.

16. An Example: Indridason & Kam (2007) 1.PM sets status quo policy, x*  2 ; w.l.o.g. set x* = (0,0) 2.M i & M j spend $, s 0  {-ω, ω} where ω is PM’s oversight 3. s 0 alters policy: x* → x 0 = (s 0 i, s 0 j ) 3.PM reshuffles (r = 1) or not (r = 0) 4.M i & M j spend again, s 1  {-ω, ω} x 0 → x 1 = (s 0 i + (1-r)s 1 i + rs 1 j, s 0 j + rs 1 i + (1-r)s 1 j ) 5.Payoffs

17. An Example: Indridason & Kam (2007) PM utility tied to government’s policy: U PM (x 0, x 1 ) = -||x 0 || 2 - ||x 1 || 2 M i ’s policy tied to government policy & spending in portfolio: U Mi (x 0, x 1 ) = -||x 0 || 2 - ||x 1 || 2 +  i x 0i + (1-r)  i x 1i + r  i x 1~I where  i represents M i ’s preference for spending over policy

18. $ Shift ω s1js1j UMjUMj j2j2 s0is0i Reshuffle: r = 1  M j is within ω of  /2  if M j can obtain  /2 in t 1, she does so; else M j spends ω  So would M i ever spend s0 < ω? A Reshuffle Equilibrium t0t0 t1t1

19. $ Shift ω s1js1j UMi*UMi* s0is0i ω s0i*s0i* s1j*s1j* In restraining spending at t 0, M i : Forgoes spending utility at t 0 Depends on  Avoids policy disutility by limiting M j ’s spending at t 1 Depends on ω In equilibrium when:   (  / 6,  / (2 + 2 / 3  6) ) A Reshuffle Equilibrium

20. Calvert, McCubbins, Weingast (1989) Theme: Another look at the agency drift model set out by McNollgast. Question: To what extent can bureaucracy substitute its own discretion for political instructions ex post? Argument: Political institutions allow bureaucrats discretion only within limits allowed by politicians

21. Calvert, McCubbins, Weingast (1989) L E A L & E bargain over selection of A (Nash Cooperative Solution) Policy setting is delegated to A A sets policy x A on contract curve normalized to L = 0, E = 1 Either L or E may veto x A

22. Calvert, McCubbins, Weingast (1989) L E A Utility Functions: U A = ν A - |x – x A | U E = ν E - |1 – x| U L = ν L - |x| i.e., the higher ν i, the more the actor is willing to give up in terms of agency discretion to get some policy

23. Calvert, McCubbins, Weingast (1989) L = 0 E = 1 xAxA Full Information Game:  x A must be closer to both principals than their respective reservation values, ν E and ν L  Any x further away ν i than provides u i < 0: veto νEνE νLνL

24. Calvert, McCubbins, Weingast (1989) L = 0 E = 1 xAxA Add uncertainty:  x A = xA* + , where  is a r.v. such that xA  [0, 1]  Does this change game?  Not much: Within   of veto points, A has some wriggle room νEνE νLνL 

25. Calvert, McCubbins, Weingast (1989) L = 0 E = 1 xAxA Principal’s capacity to veto, i.e., exert ex post correct limits agency discretion even in presence of uncertainty νEνE νLνL 