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)
- Low-quality goods become a larger share of supply.
- Average market price falls.
- The lower price drives even more high-quality sellers out.
Numerical illustration (step-by-step)
- 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)
- Buyer valuations (risk-neutral):
- Lemon: 1{,}500
- High-quality: 14{,}000
- 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.
- 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)
- Third-party verifiers
- Consumer Reports, Carfax, Yelp, professional inspections.
- Credible signals from sellers (must be too costly for low-quality sellers to mimic)
- College degrees signal ability & grit.
- Warranties, maintenance records, brand reputation.
- 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
- Use correlated information
- Auto insurers price by age, gender, zip code, driving record, credit score.
- Contract menu / self-selection
- Low vs. high deductibles, copays; healthy behaviors discounts.
- 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
- Not fully observable actions (hidden effort, care, honesty).
- 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
- Monitoring (make hidden actions observable)
- Employer web surveillance; IRS audits; dog-walker GPS.
- Reward complements (promote correlated behaviors)
- Gym discounts, driver education breaks, free coffee for alertness.
- “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).
- Government rules & social norms
- Anti-fraud laws, FDA standards, societal value of honesty.
- 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.