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Extensive Form Games and Subgame Perfect Equilibrium

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Strategic Form Games and Nash Equilibrium→→Stackelberg Competition: Sequential Quantity Leadership
game-theory sequential-play

Core Idea

Extensive form represents games as game trees with nodes and branches. Subgame perfect equilibrium (SPE) requires Nash equilibrium play in every subgame, eliminating non-credible threats. SPE is found by backward induction: optimize at the last decision node, then work backward. SPE is more restrictive than Nash equilibrium in strategic form, as converting to extensive form may eliminate non-credible equilibria.

Explainer

In strategic-form games, you represented interactions as a matrix of payoffs where players choose simultaneously. But many real strategic situations are sequential: one player moves first, the other observes the move, then responds. A game tree captures this timing explicitly. Each node represents a point where a specific player must make a decision, branches represent the available actions, and terminal nodes list the payoffs for all players. The tree structure encodes who moves when, what they know at the time, and what outcomes result from each combination of choices.

The key insight that motivates subgame perfection is that ordinary Nash equilibrium allows players to make non-credible threats — strategies they would never actually follow through on if called upon to act. Consider a simple entry game: an incumbent threatens to start a price war if a rival enters the market. In the strategic form, "enter, and the incumbent fights" can be a Nash equilibrium if the incumbent's threat deters entry. But look at the game tree: if entry actually happens, fighting is costly for the incumbent too. The incumbent would rationally accommodate rather than fight. The threat to fight is not credible because, at the decision node where the incumbent must act, fighting is suboptimal. Nash equilibrium does not catch this problem because it only checks that each player's overall strategy is a best response — it does not verify that the strategy remains optimal at every decision point within the game.

Subgame perfect equilibrium fixes this by requiring that strategies form a Nash equilibrium not just in the overall game, but in every subgame — every portion of the game tree that could stand alone as a well-defined game. The method for finding SPE is backward induction: start at the final decision nodes, determine each player's optimal choice there, then move one step earlier in the tree and optimize given that you now know what will happen downstream. Continue working backward to the root of the tree. At every step, players are choosing optimally given what will actually happen later, not what someone threatens will happen. This guarantees credibility at every decision point.

Backward induction is simple to execute in finite games of perfect information (where every player observes all previous moves). In the entry game, you start at the incumbent's node: accommodate beats fight, so the incumbent will accommodate. Moving backward, the entrant knows this, so entry is profitable, and the entrant enters. The unique SPE is (enter, accommodate) — the price war threat is pruned away. In more complex games with multiple stages, backward induction can produce strikingly different predictions than Nash equilibrium analysis of the strategic form. This refinement is foundational for analyzing sequential bargaining, Stackelberg competition, and any setting where the order of moves and the credibility of commitments determine the outcome.

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 Subgame Perfect Equilibrium

Longest path: 102 steps · 524 total prerequisite topics

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