Beyond Pay for Performance Financial University, Moscow March 23, 2017 Bengt Holmström

Agenda The Principal-Agent Problem Single task (“effort”) Towards a more realistic model Linear incentives Multitasking Low-powered incentives Incentives in firms Orchestrating alternative incentives V. Firm boundaries The dual role of ownership of assets

I. Principal-Agent Problem Employer-Employee, Client-Lawyer, Board-CEO, etc. Two difficulties Interests/preferences not aligned Performance imperfectly measured Pay-for-performance to align interests Trade-off: incentives versus risk

I. P-A Problem – An “effort” model Agent’s unobserved choice: “effort” e Measured performance: x = e + ,  = measurement error Contract: Payment s(x) from P to A Preferences: Principal: B(e) – s(x) Agent: s(x) – C(e)  rVar(s) Timing: Contract, A chooses e, Outcome x realized, Payments

I. P-A Problem – First best and second best First best cases: Maximize B(e)  C(e) agent’s choice e verifiable; s(x) = constant (routine job) agent risk neutral; s(x) = x + constant (taxi cabs) Second best: Maximize B(e)  C(e)  rVar(s) Note: principal has to compensate agent for cost of effort and risk Complicated problem in general

I. P-A problem – The informativeness principle When is additional information y valuable? Whenever y contains additional information about the agent’s action e beyond x Example where y is not of value: insurance deductibles Information could be about effort e or external factor  Vesting (lagged information) Relative performance evaluation (CEO pay) Controllability principle (filtering out risk)

I. P-A Problem – Lessons from informativeness Pros: Informativeness reveals exactly how the model “thinks” (as if this were a statistical inference problem) Explains odd features of effort-model Cons: Theory says little about shape, because optimal contracts oversensitive to information

II. Toward a more realistic model – When are incentives linear? A disturbing example: x = e + ,   Normal distribution. punishing very rare failures very severely approximates first-best (tails of Normal distribution very informative) In dynamic version linear incentive optimal, because it provides constant incentive pressure and avoids gaming (robust) Making the model more complex simplifies the solution. Justifies linear incentives in the static model

II. Toward a more realistic model – The linear model behaves sensibly Stronger incentive (higher commission) when: Performance measure more precise (less risk) Agent less risk averse Value of agent’s effort higher Agent’s responsiveness to incentive higher The linear model a great “conversation partner” But why are incentives in firms often low-powered?

III. Multitasking – Beyond pay-for-performance Big change in focus when agent has many tasks about allocation of effort rather than level of effort Incentives for multitasking very different when easy-to-measure and hard-to-measure tasks compete for agent’s attention performance measure is easy to manipulate performance measure and value are misaligned

III. Multitasking – “You get what you pay for” Wells Fargo – fraudulent shell accounts BP and oil Gulf spill – pressure to perform compromised safety Teachers teaching to test (hard skills, not soft skills) Atlanta teaching scandal (teachers corrected answers)

III. Multitasking - Lessons Two ways to provide incentives for a task Pay more for that task Pay less for competing (substitute) tasks Low powered incentives No incentive may be best incentive even for a task that can be perfectly measured Must consider full portfolio of tasks when designing incentives

IV. Incentives in firms – Many alternative instruments Job design define scope of jobs (Google 20% freedom) separate easy-to-measure tasks from hard-to-measure tasks Bureaucratic rules and constraints Have people work in the office rather than at home Don’t allow work for other companies Authority and promotions (career incentives) Control information flows (accounting system) f

IV. Incentives in firms – Orchestrated design bonuses job design bureaucratic constraints authority access to information hiring and promotions monitoring and evaluation Instruments need to be coordinated (Lincoln Electric) Desire to be appreciated is a strong incentive in firms Incentive System

V. Firm boundaries – Employment versus Contracting Employee No ownership of assets Low-powered financial incentives Work is assigned and constrained by rules Contractor Ownership of assets High-powered incentives (market price) Free to organize work and choose clients Context determines choice: Stable, complex jobs with low cost of input monitoring favor employment.

V. Firm Boundaries – The dual role of asset ownership External role (power in the market) Assets strategic chips in market Internal role (power within firm) Assets empower firms to set the terms of employment, structure incentives, pursue desired strategies – “set the rules of the game” The right to exit disciplines the firm

Summary A fixed wage (no pay-for-performance) is sometimes the best financial incentive because of multitasking concerns The comparative advantage of firms lies in their ability to influence workers through a multitude of cheaper non-monetary incentives. Incentives need to be design with the totality of tasks in mind.

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