A topic in the Open Knowledge Graph — a free, open map of 15,290 topics and the order to learn them in.

Second-Price Sealed-Bid Auction (Vickrey Auction)

Research Depth 105 in the knowledge graph ☐ I know this ☆ Set as goal
630prerequisites beneath it
See this on the map →
Auction TheoryAuction Design: First-Price and Second-Price Sealed-Bid Auctions→
auctions bidding truthful-revelation

Core Idea

In a Vickrey auction, the highest bidder wins but pays the second-highest bid. Truthful bidding is a weakly dominant strategy: bid true valuation regardless of others' bids. This simplicity makes Vickrey auctions attractive for online advertising and spectrum sales, though they differ slightly from pure Vickrey in practice.

How It's Best Learned

Analyze bidder payoffs graphically. Show that truthful bid maximizes utility for any bid distribution. Compare revenue with first-price auctions.

Explainer

From your study of auction theory, you know that auction design is about setting rules that determine who wins and what they pay. In a second-price sealed-bid auction (also called a Vickrey auction), each bidder submits a single sealed bid without seeing others' bids. The highest bidder wins the item, but — and this is the crucial twist — they pay the *second*-highest bid, not their own. This payment rule, which seems counterintuitive at first, produces a remarkably clean strategic result.

The key insight is that bidding your true valuation is a weakly dominant strategy. To see why, suppose you value a painting at $500. If you bid $500 (truthfully), there are two cases. If the highest competing bid is below $500 — say $350 — you win and pay $350, netting $150 in surplus. If the highest competing bid is above $500 — say $600 — you lose, but that is fine because winning would have meant paying more than the item is worth to you. Now consider deviating. If you bid above your value — say $550 — you might win when the second-highest bid is $520, but then you pay $520 for something worth only $500 to you, losing $20. If you bid below your value — say $400 — you might lose when the second-highest bid is $450, missing a deal that would have given you $50 of surplus. Truthful bidding avoids both pitfalls: it wins exactly when winning is profitable and loses exactly when winning would be unprofitable.

This logic holds regardless of how many bidders participate, what their valuations are, or what strategies they use. Your optimal bid depends only on your own valuation — you never need to guess what others will do. This dominant strategy property makes the Vickrey auction especially attractive in practice because bidders face no strategic complexity. Contrast this with the first-price auction, where the winner pays their own bid: there, optimal bidding requires shading your bid below your true value (to capture surplus), which in turn requires estimating the distribution of competing bids. The first-price auction demands sophisticated strategic reasoning; the second-price auction demands only self-knowledge.

A natural question is whether the auctioneer sacrifices revenue by using this generous payment rule. The revenue equivalence theorem shows that under standard assumptions (risk-neutral bidders, independent private values), the expected revenue is identical across first-price and second-price auctions. In the first-price auction, bidders shade their bids down but pay what they bid; in the second-price auction, bidders bid truthfully but pay less than their bid. These effects exactly offset. The Vickrey auction is the single-item case of the more general VCG mechanism — the same "pay your externality" logic that makes truth-telling dominant in broader mechanism design problems. In practice, second-price auctions form the backbone of online advertising markets (Google's ad auctions use a variant), precisely because the dominant-strategy property means bidders can participate without needing complex bidding algorithms.

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 → Bayesian Games (Games of Incomplete Information) → Mechanism Design: Strategic Implementation → The Revelation Principle → Vickrey-Clarke-Groves (VCG) Mechanisms → Auction Formats and Revenue Equivalence → Auction Theory → Second-Price Sealed-Bid Auction (Vickrey Auction)

Longest path: 106 steps · 630 total prerequisite topics

Prerequisites (2)

Leads To (0)

No topics depend on this one yet.