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Signaling Games: Separating and Pooling Equilibria

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Bayesian Games (Games of Incomplete Information)Adverse Selection and Screening Mechanisms+2 more→→Labor Market Signaling: Education as a Signal
game-theory information-asymmetry

Core Idea

In signaling games, the informed player moves first with an action (signal) that communicates private information. Separating equilibria have different types taking different actions; pooling equilibria have all types taking the same action. The Intuitive Criterion eliminates equilibria depending on unreasonable out-of-equilibrium beliefs, selecting among multiple equilibria.

Explainer

From your study of adverse selection and screening, you know that information asymmetry creates problems: when one side of a market knows more than the other, uninformed parties cannot distinguish good types from bad. In screening models, the uninformed party moves first, designing a menu of contracts to sort the informed party. Signaling games flip this structure — here the informed party moves first, taking a costly action that conveys information about their type. The classic example is Spence's job market signaling: a worker knows their own productivity, and they choose how much education to get before an employer makes a wage offer. Education may or may not improve productivity directly — what matters is that it is differentially costly across types, allowing it to function as a credible signal.

A separating equilibrium is one where different types choose different signals, fully revealing their private information. In the education example, high-ability workers get a degree while low-ability workers do not. This works when the signal is costly enough that low types would not want to mimic high types, even for the higher wage. The condition is called the single-crossing property: the marginal cost of the signal must differ across types so that indifference curves of different types cross only once in signal-wage space. High-ability workers find education less costly (in effort, time, or difficulty), so they are willing to invest in a level of education that low-ability workers would find prohibitively expensive. The employer, observing the education level, correctly infers the worker's type and pays accordingly.

A pooling equilibrium is one where all types choose the same signal, so no information is transmitted. If all workers get the same education level regardless of ability, the employer learns nothing and pays the average-productivity wage. Pooling equilibria can be sustained when the signal cost is high enough that no type finds it worthwhile to deviate — or when beliefs about deviators are pessimistic enough that deviating is not rewarded. This multiplicity of equilibria is a characteristic feature of signaling games: for many parameter values, both separating and pooling equilibria exist, along with partial-pooling equilibria where some types separate and others pool.

The Intuitive Criterion, introduced by Cho and Kreps, is the standard refinement for selecting among these equilibria. The idea is to eliminate equilibria that are sustained only by unreasonable beliefs about off-equilibrium actions. If a particular deviation from the equilibrium strategy could only conceivably benefit a high type (because a low type would lose money even with the most optimistic belief about the employer's response), then the employer should infer that any deviator is a high type. Formally, if a signal is equilibrium dominated for one type — meaning that type would never benefit from sending it regardless of how the receiver responds — then the receiver should not attribute that signal to that type. Applying this criterion typically eliminates pooling equilibria and many partial-pooling equilibria, selecting the most efficient separating equilibrium as the unique prediction. This refinement is widely applied in industrial organization, finance (firms signaling quality through dividends or debt), and political economy (candidates signaling competence through policy positions).

Practice Questions 5 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 → Signaling Games → Signaling Games: Separating and Pooling Equilibria

Longest path: 110 steps · 574 total prerequisite topics

Prerequisites (4)

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