incentives. overview misaligned goals or interests hidden action moral hazard problems solutions...

Incentives

Overview

Misaligned Goals or Interests Hidden Action

Moral Hazard Problems Solutions Risk-Reward Tradeoff

Hidden Information Adverse selection problems Solutions

The Strategic Process

Align BusinessSystem


AnticipateObstaclesAnticipateObstacles LeadershipLeadership

Strategic PlanStrategic Plan

FeasibilityFeasibility

Strategic OptionsStrategic Options

EXECUTIONEXECUTION

Where Are We Now?Where Are We Now? Where Do We Want to Be?Vision / Mission

Where Do We Want to Be?Vision / Mission

Incentives in the Strategic Process







EXECUTIONEXECUTION



Existing incentivesaffect

Incentives in the Strategic Process







EXECUTIONEXECUTION



Existing incentivesaffect

Execution canrequire changing

incentives

Where Incentives Come into Play Executive compensation

Done correctly can encourage risk taking and doing unpleasant jobs (e.g., restructuring)

Done incorrectly can ruin the company or create problems International Harvester (Navistar) American Airlines

Divisional incentives Done correctly can encourage cooperation and development of

synergies Done incorrectly can lead to infighting & inefficiency (e.g., bad

transfer pricing) Employee level

Can encourage better performance But can be implemented poorly – typists at Lincoln Electric

An Organizational Chart

U

Biff & Buffy Banyon, Haas ‘03Co-Owners

Joe Flunky, Stanford ‘03Peon

Ralph B. Kisser, HBS ‘03Gopher

Ima Loser, Kellogg ‘03Toady

Principals and Agents A principal-agent relationship exists when

one party, the principal, hires or employs another party, the agent, to do some set of tasks.

Example: Biff & Buffy are the principals and Joe, Ralph, and Ima are the agents.

Example: DoD hires a defense contractor. Example: Shareholders (P) and CEOs (A).

Agency Problems An agency problem exists when the goals or interests of the

principal & agent are not in alignment. Example: principal wishes employees promoted solely on merit,

while agent (manager) considers his friendships with employees as well as merit.

A hidden-action problem is an agency problem in which some of the agent’s actions are unobservable to the principal.

Example: agent may know how much effort (negative leisure) he is exerting on a problem, but the principal may be unable to observe or measure his effort directly.

Also called a moral hazard problem.

The Role of MonitoringAgency problems in which the principal can fully and costlessly monitor the agent are easily dealt with through contracts that stipulate exactly what the agent is to do. More serious agency problems arise when the principal can neither fully nor costlessly monitor the agent. Recall that costly monitoring can result in mixed-strategy

equilibria in which there is not full monitoring and, thus, undesired behavior.

Hence, even when monitoring is feasible, if it is costly may also wish to use incentive contracts.

Hidden Action FrameworkPrincipal’s Targets

Agent’s Actions

ExogenousFactors

PerformanceMeasures

CompensationFunction

Agent’sReward

Incentive Scheme

A Theoretical Framework Principal’s targets: what she wants agent to

do. Agent’s actions: what he does in response to

incentive scheme. Exogenous factors: noise that prevents

principal from getting perfect signal.

The Incentive Scheme Performance Measures: That upon which the

agent’s performance is measured. Compensation Function: The contractual

relationship between the performance measures and the agent’s compensation.

Agent’s Reward: The agent’s realized compensation.

Example: A Hidden-Action Problem Agent has choice of two actions: work hard or be

lazy. “Costs” the agent $10 to work hard rather than to be

lazy. Can think of “hard” and “lazy” as metaphors

Pleasant vs. unpleasant actions (toughness on subordinates; implement new strategy; etc.)

Pursue actions possibly at odds with career concerns (rock the boat; choose risky projects; etc.)

If the agent works hard, then probability that firm does well is q.

If he is lazy, then probability that firm does well is 0.

Example continued … If firm does well, principal earns $30. If firm does poorly, she earns $0. Both principal & agent are risk neutral. Negative pay is not permitted. Let W = agent’s pay if firm does well & let P =

his pay if firm does poorly.

Example continued …

qFirm does well

W -10Work Hard

qW + (1-q )P - 10 1-qFirm does poorly

P -10?

Be Lazy Firm does poorlyP

P

Example continued … Agent works hard if qW + (1-q)P - 10 P;

that is, if q(W - P) 10. Principal’s problem is to minimize her

expected wage bill subject to the constraints imposed by the problem; that is,

min

, , .,W P

qW q P

W P q W P

1

0 0 10

subject to

and

Example continued … Solution is P = 0 and W = 10/q. The difference W - P is the power of the

incentives. Note that the power of the incentives increases as

q falls. As q falls, there is less information in the firm

doing poorly with respect to whether the agent worked hard or not.

General conclusion: The less informative the performance measure, the more powerful the incentives must be.

Example continued … Does principal use incentives? Profit without incentives is $0. Expected profit with incentives is

($30 - $10/q)q + ($0 - $0)(1-q) = $30q - $10. So uses incentives provided q 1/3. General Conclusion: The less informative

the performance measure, the less likely it is that the principal uses incentives.

Example extended … Realistic to expect in many situations that the

agent is risk averse (e.g., top managers w/ incentive pay as large percentage of income).

Let agent have utility function y - e, where 0 < 1 and e = 0 or 10. Less risk averse as becomes larger.

Example extended …

qFirm does well

W - 10

Work hard

qW + (1-q )P

- 10 1-q

Firm does poorly

P - 10

?

Be lazy Firm does poorly

P

P

Example extended …Principal’s problem:

min

, , .

.

.

,W P

q

q

qW q P

W P qW q P P

P W

q

1

0 0 1 10

0 10

10

subject to

and

Readily shown that and

Hence, expected wage bill is

Example extended … = 1

q 1.0.8.6.4.2

11

10.5

10

9.5

9

Expected Wage

Example extended … = ¾

q 10.80.60.40.2

45

40

35

30

25

Expected Wage

Risk & Incentives The lower is q, the more powerful the

incentives; that is, the greater the difference between P and W.

This means the risk is greater.

10.80.60.40.2

200

150

100

50

0

q

Variance of pay when = ¾

Risk & Incentives Because agent is risk averse, he dislikes this

risk and must be compensated for bearing the risk inherent in the incentive scheme.

The greater the risk, the greater the compensation for risk; hence, the more expensive the incentive scheme.

General Conclusion: There is a trade-off between the power of incentives and their cost due to compensation for bearing risk.

Implications for Designing Incentive Schemes

Want to limit noise in the performance measure; extract exogenous factors as much as possible.

Example: performance relative to industry rather than performance relative to entire stock mkt.

Other Issues in the Design of Incentives Avoid performance measures that can be

manipulated by the agent. Int’l Harvester

Don’t reward A, while hoping for B. Int’l Harvester

Don’t ratchet—stay committed to scheme. Frequent problem with piece-rate systems

Be careful of violating horizontal equity norms. Be careful of violating vertical equity norms.

Remember Donald J. Carty

More on Agency Problems – Hidden Information

A hidden-information problem is an agency problem in which the agent acquires information about the possible tasks that the principal does not possess.

Example: agent may know how difficult a task is, while the principal may not.

Also called an adverse selection problem.

A Model of Task Difficulty Agent’s utility function is y - x2/2t, where y is

money, x is output, and t is type. Assume t = 2 (good type) or t = 1 (bad type).

Price per unit of output is $1. Prob{t = 1} = h. If agent quits, his utility is zero.

Timing

Principal hires Agent.

Agent only learns t.

Principal & Agentset output targets

Agent producesoutput target

Agent quits.

Suppose, momentarily, that t is known by both principal and agent

Principal can order any x she wants provided that compensation, y, is adequate:

So

Benchmark: t is common knowledge

y xt 12

2 0.

yx

t

2

2.

Benchmark continued … Principal’s profit is x - y = (2tx - x2)/(2t). Maximizing her profit yields x(t) = t. So x(1) = 1 and x(2) = 2. Follows that y(1) = ½ and y(2) = 1.

Principal does not know t Problem is that one type may mimic the

other; in particular, good type may claim to be bad type.

Under benchmark solution good type gets 0 if he tells the truth (1 - ¼[2]2 = 0); but he gets ¼ if he lies (½ - ¼[1]2 = ¼).

General problem: agents over-state difficulty of tasks and the resources required.

The principal’s problem

Principal wants to maximize her expected profit

subject to " truth - telling" constraints and

"participation" constraints:

subject to

; ;

; &

max

.

, , ,y y x xh x y h x y

y x y x y x

y x y x y x

1 2 1 21 1 2 2

112 1

22

12 2

21

12 1

2

214 2

21

14 1

22

14 2

2

1

0

0

Solution

x

x h

y x

y x

hh

hh

h

2

12

1

112 1

2 12

214

21

14 2

2

2

1

1 1

(note: distortion as )

Expected profit =

2

11+

.

.

Compared to the benchmark case Good type has the same target, but the bad

type is given a lower target. The good type is paid more than before and

more than is necessary to keep him from quitting, while the bad type is paid less than before and no more than is necessary to keep him from quitting.

Intuition When the principal does not know the agent’s type (e.g., t), she

must “bribe” a good-type agent to admit that he is the good type. This bribe or information rent is an additional cost of doing

business. To reduce this cost, somewhat, the principal lowers what she

pays a bad-type agent, which makes it less desirable for a good-type agent to pretend to be the bad-type agent; which, in turn, reduces the information rent.

Of course, if the principal lowers what she pays a bad-type agent, she must also lower his output target.

Applications

Application: IBM used a scheme along this line for setting commissions for sales agents: Type corresponding to how good territory is. Adjust compensation package to encourage salespeople with good

territories to (i) take advantage of them; but (ii) not capture entire value.

Ideas often used in price regulation of utilities Type is utility’s information about cost structure. Has led move from cost-plus pricing to price-cap and other reforms.

Ideas increasingly used in design of transfer-pricing schemes Type is upstream’s information about cost. Has led to new managerial accounting (e.g., ABC)

Applying the theory Unlikely to have such detailed information in the real

world. Unlikely to have deterministic production in the real

world. Hence, an exact solution like the one we just

derived is usually not possible in the real world. The issues, however, still remain. The theoretical insights still apply.

Conclusions

Incentives critical to strategy Existing incentives are part of “where you are” and

help to determine feasibility of strategies. Incentive problems are part of what determines

feasibility of strategy. Designing correct incentives can be critical to

execution.

Conclusions continued …

Design of incentives involves tradeoffs Recall monitoring often involves tradeoff of cost against

frequency of undesired behavior. Resolution of moral hazard problems involves tradeoff of

the risk incentives impose against the requirement to compensate for risk.

Resolution of adverse selection problems involves tradeoff of the efficiency of actions against the desire to limit information rents.

Because of these tradeoffs, most incentive systems are inherently imperfect; that is, second best.

Conclusions continued …

Cost drivers in moral hazard problems: Degree of misalignment between principal and

agent’s objectives and goals. How informative performance measures are about

underlying actions taken. How risk averse agent is.

Cost drivers in adverse selection: Principal’s uncertainty about agent’s type.

incentives. overview misaligned goals or interests hidden action moral hazard problems solutions...

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