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Adverse Selection

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Bayesian Games (Games of Incomplete Information)The Principal-Agent Problem+4 more→→Adverse Selection and Market EquilibriumCredit Constraints in Developing Markets+5 more
contract-theory hidden-information information-asymmetry

Core Idea

Adverse selection occurs when one party has private information about their type/quality and this affects contracting. Example: insurance buyers know health risk better than insurers. High-risk types seek coverage eagerly; insurers cannot distinguish types. Standard contracts collapse (high risks drive out low risks). Solutions: screening (insurer offers menu of contracts) or signaling (informed party reveals type).

Explainer

You have learned from Bayesian games and the principal-agent model that strategic interaction looks very different when one party holds private information. Adverse selection is the specific problem that arises when this information concerns a fixed characteristic — a *type* — that exists before any contract is signed. The classic setting is insurance: each buyer knows their own health risk, but the insurer can only observe the population distribution. A high-risk person knows they are likely to file large claims; a low-risk person knows they are unlikely to. The insurer knows that some buyers are high-risk and some are low-risk, but cannot tell them apart.

The trouble begins when the insurer tries to offer a single contract at a price reflecting the average risk in the population. For high-risk buyers, this is a great deal — they will likely collect more in claims than they pay in premiums. For low-risk buyers, it is a bad deal — they are effectively subsidizing the high-risk group. Rational low-risk buyers drop out of the market, leaving a riskier pool. The insurer now faces a pool that is worse than average and must raise prices, which pushes out more low-risk buyers. This unraveling logic — which Akerlof famously analyzed in the market for used cars ("lemons") — shows that adverse selection can cause markets to collapse entirely or serve only the worst risks.

Two solutions have been studied extensively. *Screening* is initiated by the uninformed party (the insurer): rather than offering one contract, the insurer designs a *menu* of contracts. Full coverage at a high premium is attractive to high-risk types; partial coverage at a low premium is designed to attract low-risk types. Crucially, the contracts are designed so that each type prefers the contract meant for them — this is the incentive-compatibility constraint. The resulting *separating equilibrium* effectively extracts the private information through self-selection, but at a cost: the low-risk contract must be distorted below full coverage to deter high-risk mimics, creating an efficiency loss relative to the full-information benchmark.

*Signaling*, by contrast, is initiated by the informed party. Rather than being screened, the high-quality agent voluntarily takes a costly action that only high types can afford (e.g., getting an expensive education, posting a bond, offering a warranty). If the signal is credible — if low-quality types cannot profitably mimic it — the signal separates types and credibly communicates private information. Signaling games, which you will study next, formalize the conditions under which such equilibria exist.

A key institutional implication is that mandatory participation can restore efficiency. If everyone must buy insurance (as in social insurance systems), the adverse selection death spiral is broken — low-risk types cannot exit, so the pooling premium is stable. This is part of the economic rationale for mandatory health insurance coverage requirements, even from a purely efficiency standpoint, separate from any distributional motivation.

Practice Questions 3 questions

Prerequisite Chain

Understanding Zero → The Number Zero → Counting to Five → Counting to 10 → Counting to 20 → Counting a Set of Objects Up to 20 → Cardinality: The Last Number Counted → Matching Numerals to Quantities → Subitizing Small Quantities → Addition Within 10 → Number Bonds to 10 → Addition Within 20 → Doubles and Near Doubles → Doubles Facts Within 10 → Near Doubles Facts Within 20 → Mental Math Strategies for Addition → Mental Math: Adding and Subtracting Tens → Addition Within 100 → Repeated Addition as Multiplication → Multiplication as Equal Groups → Multiplication: Arrays → Basic Multiplication Facts (0s, 1s, 2s, 5s, 10s) → Multiplication Facts Within 100 → Division as Equal Sharing → Division as Grouping (Measurement Division) → Division: Grouping (Repeated Subtraction) Model → Division: Fair Sharing Model → Division as Equal Sharing → Division as Grouping → Basic Division Facts → Division Facts Within 100 → Multiplication and Division Fact Families → Relationship Between Multiplication and Division → Division Facts as Inverse of Multiplication → Remainders and Quotients in Division → Division Word Problems → Multi-Step Word Problems → Solving Multi-Step Word Problems → Multiplication Word Problems → Division Word Problems → Introduction to Long Division → Factors and Multiples → Prime and Composite Numbers → Equivalent Fractions → Relating Fractions and Decimals → Decimal Place Value → Integers and the Number Line → Comparing and Ordering Integers → Absolute Value → Adding Integers → Subtracting Integers → Multiplying Integers → Dividing Integers → Unit Rates → Proportions → Percent Concept → Converting Between Fractions, Decimals, and Percents → Operations with Rational Numbers → Two-Step Equations → Solving Multi-Step Equations → Equations with Variables on Both Sides → Literal Equations → Slope-Intercept Form → Point-Slope Form → Writing Linear Equations → Parallel and Perpendicular Line Slopes → Graphing Linear Equations → Piecewise Functions → One-Sided Limits → Continuity Definition → Limits and Continuity in Multiple Variables → Functions of Several Variables → Continuity in Multiple Variables → Partial Derivatives: Definition and Computation → Differentiability in Multiple Variables → Differentiability in Multivariable Functions → Total Differential and Linear Approximation → Chain Rule for Multivariable Functions → Implicit Differentiation → Related Rates → Optimization Problems → Critical Points of Multivariable Functions → Critical Points and Classification of Extrema → Second Partial Test for Local Extrema (Hessian) → The Hessian Matrix and Second Derivative Test → Unconstrained Optimization: Finding Extrema → Optimization in Multiple Variables → Lagrange Multipliers → Constrained Optimization and Lagrange Multipliers → Utility and Preferences → Marginal Utility and Diminishing Returns → Profit Maximization → Perfect Competition → Shutdown and Breakeven Decisions → Monopoly → Monopolistic Competition → Oligopoly and Strategic Behavior → Game Theory Basics → Nash Equilibrium → Nash Equilibrium Refinements → Strategic Form Games and Nash Equilibrium → Extensive Form Games and Game Trees → Subgame Perfect Equilibrium → Perfect Bayesian Equilibrium → Pooling and Separating Equilibria → Adverse Selection and Screening Mechanisms → Insurance Markets with Adverse Selection → Adverse Selection

Longest path: 108 steps · 569 total prerequisite topics

Prerequisites (6)

Leads To (7)