Incentives Overview n Misaligned Goals or Interests q

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Incentives

Incentives

Overview n Misaligned Goals or Interests q Hidden Action n q Moral Hazard Problems

Overview n Misaligned Goals or Interests q Hidden Action n q Moral Hazard Problems Solutions Risk-Reward Tradeoff Hidden Information n n Adverse selection problems Solutions

The Strategic Process Where Do We Want to Be? Vision / Mission Where Are

The Strategic Process Where Do We Want to Be? Vision / Mission Where Are We Now? Strategic Options Feasibility Strategic Plan EXECUTION Anticipate Obstacles Leadership Align Business System

Incentives in the Strategic Process Where Do We Want to Be? Vision / Mission

Incentives in the Strategic Process Where Do We Want to Be? Vision / Mission Where Are We Now? Strategic Options Existing incentives affect Feasibility Strategic Plan EXECUTION Anticipate Obstacles Leadership Align Business System

Incentives in the Strategic Process Where Do We Want to Be? Vision / Mission

Incentives in the Strategic Process Where Do We Want to Be? Vision / Mission Where Are We Now? Strategic Options Existing incentives affect Feasibility Strategic Plan Execution can require changing incentives EXECUTION Anticipate Obstacles Leadership Align Business System

Where Incentives Come into Play n Executive compensation q q Done correctly can encourage

Where Incentives Come into Play n Executive compensation q q Done correctly can encourage risk taking and doing unpleasant jobs (e. g. , restructuring) Done incorrectly can ruin the company or create problems n n n Divisional incentives q q n International Harvester (Navistar) American Airlines Done correctly can encourage cooperation and development of synergies Done incorrectly can lead to infighting & inefficiency (e. g. , bad transfer pricing) Employee level q q Can encourage better performance But can be implemented poorly – typists at Lincoln Electric

An Organizational Chart SP 4 U Biff & Buffy Banyon, Haas ‘ 03 Co-Owners

An Organizational Chart SP 4 U Biff & Buffy Banyon, Haas ‘ 03 Co-Owners Joe Flunky, Stanford ‘ 03 Peon Ralph B. Kisser, HBS ‘ 03 Gopher Ima Loser, Kellogg ‘ 03 Toady

Principals and Agents n n A principal-agent relationship exists when one party, the principal,

Principals and Agents n n 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: Do. D hires a defense contractor. Example: Shareholders (P) and CEOs (A).

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

Agency Problems n An agency problem exists when the goals or interests of the principal & agent are not in alignment. q n 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. q 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. q Also called a moral hazard problem.

The Role of Monitoring Agency problems in which the principal can fully and costlessly

The Role of Monitoring Agency 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. q q 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 Framework Principal’s Targets Agent’s Actions Performance Measures Compensation Function Incentive Scheme Exogenous

Hidden Action Framework Principal’s Targets Agent’s Actions Performance Measures Compensation Function Incentive Scheme Exogenous Factors Agent’s Reward

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

A Theoretical Framework n n n 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 n n n Performance Measures: That upon which the agent’s performance

The Incentive Scheme n n n 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 n n n Agent has choice of two actions: work

Example: A Hidden-Action Problem n n n 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 q q n n 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 … n n n If firm does well, principal earns $30. If

Example continued … n n n 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 …

Example continued …

Example continued … n n Agent works hard if q. W + (1 -q)P

Example continued … n n Agent works hard if q. W + (1 -q)P - 10 ³ P; that is, if q(W - P) ³ 10. Principal’s problem is to minimize her expected wage bill subject to the constraints imposed by the problem; that is,

Example continued … n n n Solution is P = 0 and W =

Example continued … n n n 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 … n n n Does principal use incentives? Profit without incentives is

Example continued … n n n Does principal use incentives? Profit without incentives is $0. Expected profit with incentives is ($30 - $10/q)q + ($0 - $0)(1 -q) = $30 q - $10. So uses incentives provided q ³ 1/3. General Conclusion: The less informative the performance measure, the less likely it is that the principal uses incentives.

Example extended … n n Realistic to expect in many situations that the agent

Example extended … n n 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 yb - e, where 0 < b £ 1 and e = 0 or 10. Less risk averse as b becomes larger.

Example extended …

Example extended …

Example extended … Principal’s problem:

Example extended … Principal’s problem:

Example extended … b = 1 Expected Wage 11 10. 5 10 9. 5

Example extended … b = 1 Expected Wage 11 10. 5 10 9. 5 9 . 2 . 4 q . 6 . 8 1. 0

Example extended … b = ¾ Expected Wage

Example extended … b = ¾ Expected Wage

Risk & Incentives n n The lower is q, the more powerful the incentives;

Risk & Incentives n n 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. Variance of pay when b = ¾ q

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

Risk & Incentives n n n 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 n n Want to limit noise in the performance

Implications for Designing Incentive Schemes n n 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 n Avoid performance measures that can be

Other Issues in the Design of Incentives n Avoid performance measures that can be manipulated by the agent. q n Don’t reward A, while hoping for B. q n n Int’l Harvester Don’t ratchet—stay committed to scheme. q n Int’l Harvester Frequent problem with piece-rate systems Be careful of violating horizontal equity norms. Be careful of violating vertical equity norms. q Remember Donald J. Carty

More on Agency Problems – Hidden Information q A hidden-information problem is an agency

More on Agency Problems – Hidden Information q A hidden-information problem is an agency problem in which the agent acquires information about the possible tasks that the principal does not possess. q q 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 n n Agent’s utility function is y - x

A Model of Task Difficulty n n Agent’s utility function is y - x 2/2 t, 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 Agent produces output target Principal hires Agent. Principal & Agent set output targets

Timing Agent produces output target Principal hires Agent. Principal & Agent set output targets Agent only learns t. Agent quits.

Benchmark: t is common knowledge n n n Suppose, momentarily, that t is known

Benchmark: t is common knowledge n n n 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 continued … n n Principal’s profit is x - y = (2 tx

Benchmark continued … n n Principal’s profit is x - y = (2 tx - x 2)/(2 t). 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 n n n Problem is that one type may

Principal does not know t n n n 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

The principal’s problem

Solution

Solution

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

Compared to the benchmark case n n 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 n n When the principal does not know the agent’s type (e. g.

Intuition n n 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. q To reduce this cost, somewhat, the principal lowers what she pays a bad-type agent, which makes it less desirable for a goodtype agent to pretend to be the bad-type agent; which, in turn, reduces the information rent. q Of course, if the principal lowers what she pays a bad-type agent, she must also lower his output target.

Applications n Application: IBM used a scheme along this line for setting commissions for

Applications n Application: IBM used a scheme along this line for setting commissions for sales agents: q q n Ideas often used in price regulation of utilities q q n 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. 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 q q Type is upstream’s information about cost. Has led to new managerial accounting (e. g. , ABC)

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

Applying theory n n n 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 n Incentives critical to strategy q q q Existing incentives are part of

Conclusions n Incentives critical to strategy q q q 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 … n Design of incentives involves tradeoffs q q Recall monitoring often

Conclusions continued … n Design of incentives involves tradeoffs q q 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 … n Cost drivers in moral hazard problems: q q q n

Conclusions continued … n Cost drivers in moral hazard problems: q q q n 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: q Principal’s uncertainty about agent’s type.