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

First-Price Sealed-Bid 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+1 more→
auctions bidding sealed-bid

Core Idea

In a first-price auction, the highest bidder wins and pays their own bid. Bidders shade bids below true valuations: in symmetric equilibrium with N bidders and uniform valuations on [0, v], equilibrium bid is b(v) = ((N-1)/N)v. Revenue increases with N. Unlike second-price auctions, truthful bidding is not dominant.

Explainer

From auction theory, you know the four standard auction formats and the revenue equivalence theorem. The first-price sealed-bid auction is the format that most clearly illustrates strategic bid shading — the central tension between wanting to win and wanting to pay less. Each bidder submits a single sealed bid, the highest bidder wins, and they pay exactly what they bid. Unlike the second-price auction where truthful bidding is dominant, here bidding your true value guarantees zero surplus if you win. The entire strategic problem is figuring out how far below your true value to bid.

Consider the tradeoff facing a bidder who values the item at $80. Bidding $80 guarantees zero profit even if she wins. Bidding $50 yields $30 profit if she wins — but she might lose to someone who bid $60. The optimal bid balances the probability of winning (which increases with your bid) against the surplus if you win (which decreases with your bid). The expected payoff is (v - b) × Pr(win | b), and the bidder chooses b to maximize this expression. Solving this optimization requires knowing the distribution of competing bids, which depends on the distribution of competing valuations.

In the symmetric independent private values model with N bidders whose valuations are drawn uniformly from [0, v̄], the equilibrium bidding strategy has an elegant closed form: b(v) = ((N-1)/N) × v. A bidder with valuation v bids a fraction (N-1)/N of her true value. With 2 bidders, you bid half your value; with 10 bidders, you bid 90% of your value. The intuition is direct: more competition means a smaller gap between the highest and second-highest valuations, so you cannot afford to shade as aggressively. As N grows large, bids converge to true values and the auction approaches full surplus extraction — competition does the seller's work.

This equilibrium bidding function reveals why revenue equivalence holds despite the very different feel of first-price and second-price auctions. In a second-price auction, the winner pays the second-highest value and there is no shading. In a first-price auction, the winner pays her own shaded bid, which is lower than her value but higher than the second-highest bid. The expected payment turns out to be identical: in both cases, the expected revenue equals the expected value of the second-highest order statistic of the valuation distribution. Revenue equivalence breaks down when bidders are risk-averse (they shade less in first-price auctions, raising revenue above the second-price benchmark), when valuations are asymmetric (different bidders draw from different distributions), or when valuations have a common-value component (introducing the winner's curse).

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 → First-Price Sealed-Bid Auction

Longest path: 106 steps · 630 total prerequisite topics

Prerequisites (3)

Leads To (0)

No topics depend on this one yet.