Chapter 19 – Decisions Involving Private Information

Adverse Selection: When Sellers Know More Than Buyers

  • Private (asymmetric) information

    • One side of the market knows something the other side does not.
    • Here: sellers possess knowledge about product quality that buyers cannot directly observe.
    • Buyer fear: “Will I get ripped off?”
    • Common settings: used‐car lots, online marketplaces (eBay), health supplements, stocks.
  • “Lemon” example (used‐car market)

    • Lemon = a junk car with numerous hidden problems.
    • Buyers cannot distinguish lemons from high-quality cars, so a single market price emerges.
    • That price lies between a buyer’s willingness to pay (WTP) for a lemon and WTP for a high-quality car.
    • Consequences for different sellers
    • High-quality sellers receive less than the car’s true value ➔ many keep their cars.
    • Lemon sellers receive more than true value ➔ gladly sell.
    • Definition: Adverse selection of sellers = market mix skews toward low-quality goods when buyers cannot observe quality.
    • “Spiral” logic (illustrated graphically in lecture)
    1. Low-quality goods become a larger share of supply.
    2. Average market price falls.
    3. The lower price drives even more high-quality sellers out.
  • Numerical illustration (step-by-step)

    1. Suppose 100 potential sellers:
    • 40 lemons (reservation price =1{,}000)
    • 20 high‐quality cars (reservation price =7{,}000)
    • 40 very high‐quality cars (reservation price =10{,}000)
    1. Buyer valuations (risk-neutral):
    • Lemon: 1{,}500
    • High-quality: 14{,}000
    1. If buyers believe lemons share = 40\/(40+20)=0.667,
    • Expected value = 0.667\times1{,}500 + 0.333\times14{,}000 = 5{,}666.25
    • Only lemons (cost 1{,}000) remain willing to sell. High-quality exit.
    1. When lemons = 100\% of cars on the lot,
    • Buyer WTP collapses to 1{,}500.
    • Market for quality vehicles disappears entirely.
  • Policy & market solutions (goal: bridge info gap)

    1. Third-party verifiers
    • Consumer Reports, Carfax, Yelp, professional inspections.
    1. Credible signals from sellers (must be too costly for low-quality sellers to mimic)
    • College degrees signal ability & grit.
    • Warranties, maintenance records, brand reputation.
    1. Government intervention
    • Mandatory disclosure laws (e.g., home sellers must reveal asbestos).
    • Banning lowest-quality goods (licensing for doctors; FDA minimum standards).
  • Key takeaway

    • Without corrective measures, markets with seller private information devolve toward low quality.
    • Solutions rely on information creation (verification), incentive-compatible signaling, or regulation.

Adverse Selection: When Buyers Know More Than Sellers

  • Definition

    • Adverse selection of buyers = market mix skews toward high-cost customers when sellers cannot observe buyer type.
    • Buyers possess private knowledge about their risk/cost level; sellers set uniform prices.
  • Classic setting: Health insurance

    • Insurer cannot perfectly observe individual health.
    • Uniform premium lies between cost of insuring low-risk and high-risk clients.
    • Low-risk (healthy) find price too high ➔ exit.
    • High-risk find price attractive ➔ purchase.
    • Results
    • Average cost of remaining pool rises ➔ premiums rise further ➔ additional low-risk exit (adverse-selection spiral).
  • When ignorance helps

    • Insurance works best if neither side holds predictive private info (e.g., homeowners’ flood risk unknown to both).
    • Allowing people to opt in only after getting sick deepens the spiral (pre-existing condition problem).
  • Risk aversion as a stabilizer

    • Risk-averse individuals dislike uncertainty enough to pay more than the actuarially fair premium.
    • Their willingness to overpay offsets part of the cost of high-risk customers, mitigating (not eliminating) adverse selection.
    • Actuarially fair: policy with \text{expected payouts} = \text{premiums collected}.
  • Market & policy solutions

    1. Use correlated information
    • Auto insurers price by age, gender, zip code, driving record, credit score.
    1. Contract menu / self-selection
    • Low vs. high deductibles, copays; healthy behaviors discounts.
    1. Government roles
    • Anti-fraud enforcement (incentivize truth-telling).
    • Premium subsidies (partially pay for low-risk to stay insured).
    • Mandates (require everyone to purchase insurance) remove opt-out option.
    • Public provision (Medicare, Medicaid cover ≈40 % of Americans).
  • Key takeaway

    • Buyer private information drives out low-cost customers and raises average price.
    • Targeted information, contract design, and policy interventions keep low-cost buyers in the pool.

Moral Hazard: The Problem of Hidden Actions

  • Definition

    • Moral hazard = changes in behavior that occur because actions are not fully observable and the actor is partially insulated from consequences.
    • Distinct from adverse selection (info about type before contract). Moral hazard concerns actions after an agreement.
  • Two critical ingredients

    1. Not fully observable actions (hidden effort, care, honesty).
    2. Partial insulation from costs/benefits (insurance, principals bearing consequences).
    • Example: Slacking at work when pay is fixed; speeding after buying car insurance.
  • Market implications

    • Once insured against a bad outcome, individuals take fewer precautions ➔ bad outcome becomes more likely ➔ cost of insurance rises ➔ possible market collapse.
  • Principal–agent problem

    • Principal hires agent but cannot perfectly observe agent’s effort.
    • Divergent incentives: agent may under-deliver or pursue self-interest.
    • Mechanic recommends unnecessary repairs; CEO undertakes vanity projects; real-estate agent shows pricier houses for higher commission.
  • Technology & monitoring

    • GPS telematics lets auto insurers observe speed, braking, tailgating ➔ converts hidden actions into observable metrics.
    • Lower premiums reward safe drivers, aligning incentives.
  • Five broad solution categories

    1. Monitoring (make hidden actions observable)
    • Employer web surveillance; IRS audits; dog-walker GPS.
    1. Reward complements (promote correlated behaviors)
    • Gym discounts, driver education breaks, free coffee for alertness.
    1. “Skin in the game” (shared risk/reward)
    • Security deposits, copays, deductibles, pay-for-performance compensation.
    • Caveat: poorly designed incentives can misfire (e.g., Wells Fargo account scandal).
    1. Government rules & social norms
    • Anti-fraud laws, FDA standards, societal value of honesty.
    1. Pick the right agents
    • Favor trustworthy individuals inside personal networks; reputation-sensitive partners; intrinsically motivated workers.
  • Key takeaway

    • Hidden actions + insulation from consequences ⇒ misaligned incentives.
    • Combining monitoring, incentive design, regulation, and careful partner choice realigns behavior with social/contracting goals.