First-Price Auction

In a first-price auction, all participants submit confidential bids simultaneously. The auctioneer then opens the bids, and the participant who submitted the highest bid is declared the winner. The critical, defining feature is that the winner's payment equals their own bid amount. This contrasts with a second-price auction (or Vickrey auction), where the winner pays the amount of the second-highest bid. The sealed-bid nature prevents bidders from reacting to others' offers in real-time, making strategic bidding crucial.

The primary strategic challenge in a first-price auction is the bid shading dilemma. A rational bidder must balance the desire to win against the desire to maximize profit. Bidding one's true maximum valuation guarantees winning if it's the highest bid, but results in zero surplus (profit) upon payment. Therefore, bidders typically shade their bid—submitting an amount lower than their true private value—to secure a profit margin. The optimal shading strategy depends on the bidder's assumptions about the valuations and strategies of other participants.

In blockchain ecosystems, first-price auctions are most commonly used in block space markets, such as transaction fee mechanisms. In networks like Ethereum (pre-EIP-1559) and Bitcoin, users submit transactions with a fee bid (gasPrice or feeRate). Validators or miners select transactions to include in the next block, typically prioritizing those with the highest bids. The winning transactions are included and the users pay the exact fee they specified. This creates inefficiencies like fee overestimation and unpredictable clearing prices.

Compared to other mechanisms, first-price auctions have distinct advantages and drawbacks. They are conceptually simple and guarantee the seller receives the highest submitted price. However, they often lead to inefficient outcomes and bidder regret. Winners may feel they overpaid (the "winner's curse"), and the lack of price transparency can result in volatile and unpredictable costs for participants. These shortcomings have driven the exploration of alternative designs, such as Ethereum's EIP-1559 base fee model, which introduces a network-set base price to improve user experience.

The analysis of first-price auctions is a cornerstone of auction theory and game theory. Bidders are engaged in a game of incomplete information, where formulating a winning strategy requires estimating the competition. In repeated auction environments, like those for digital advertising or blockchain blocks, sophisticated bidding agents often use algorithms to dynamically adjust their bids based on historical data and market conditions, turning the auction into a complex, automated competition.

A first-price auction is a sealed-bid auction mechanism where the highest bidder wins the auction and pays the exact amount they bid. In blockchain contexts, this model is most famously applied in Ethereum's transaction fee market prior to the London upgrade (EIP-1559). Users submit transactions with a gasPrice bid, and miners select the highest-paying transactions to include in the next block. The winning user pays their full bid, creating a strategic environment where participants must guess the minimum bid necessary to win without overpaying—a challenge known as the "winner's curse."

The mechanics create significant inefficiencies and user experience challenges. Bidders are incentivized to engage in complex guesswork, often leading to overbidding (wasting capital) or underbidding (causing transaction delays). This opacity results in high fee volatility and necessitates the use of fee estimation tools. Unlike a second-price auction (Vickrey auction), where the winner pays the second-highest bid, the first-price model lacks incentive compatibility, meaning a bidder's dominant strategy is not simply to bid their true valuation of the item.

In Ethereum's history, the first-price auction for block space led to several negative outcomes, including fee spirals during network congestion and economically inefficient overpayment. These issues were primary motivations for the protocol's shift to a base fee and tip model with EIP-1559, which incorporates a base fee that is burned and a priority fee (tip) in a simplified auction for miner ordering. However, first-price auctions remain relevant in other blockchain domains such as NFT sales, certain DeFi liquidation processes, and validator selection in some proof-of-stake systems.

Strategically, participants in a first-price auction must analyze public mempool data and network demand to formulate a bid. Optimal bidding often involves bid shading—submitting a bid below one's true maximum value to avoid the winner's curse. This requires sophisticated modeling of other participants' behavior, making the system complex for ordinary users. The model's transparency of outcomes (winning bids are public) but opacity of ongoing bidding creates a challenging strategic landscape distinct from other auction types.

The first-price auction serves as a critical case study in mechanism design, highlighting the trade-offs between simplicity, revenue for resource providers (miners/validators), and bidder efficiency. Its limitations in the context of a public, transparent blockchain have driven innovation toward hybrid fee models and more sophisticated transaction ordering mechanisms like MEV (Maximal Extractable Value) auctions, where searchers bid for the right to influence transaction ordering within a block.

In a first-price auction, the winning bidder pays exactly the amount they submitted, creating a complex strategic environment where participants must balance the desire to win against the risk of overpaying. Unlike in a second-price auction (Vickrey auction), where the dominant strategy is to bid one's true private value, bidders in a first-price format must strategically shade their bids—submitting a value below their true maximum willingness to pay—to secure a profit margin. This bid shading is the core of bidder strategy, as the highest bid wins but also determines the price paid.

The optimal level of bid shading depends on several factors, including the number of competing bidders and the auctioneer's reserve price. With more bidders, competition increases, forcing participants to bid closer to their true value to have a chance of winning. Conversely, with fewer competitors, bidders can afford to shade their bids more aggressively. A rational bidder must estimate the valuations of others, often modeled using game theory and Bayesian Nash equilibrium, to determine the bid that maximizes their expected payoff, which is the probability of winning multiplied by the profit (true value minus bid price).

A critical risk in this environment is the Winner's Curse, a phenomenon where the winner tends to be the bidder who most overestimates the true value of the item, often leading to a loss. In common value auctions—where the item's value is the same for everyone but unknown (e.g., mineral rights, blockchain block space)—winning the auction can be a negative signal that your estimate was too high. The curse arises because the winning bid is, by definition, the highest estimate, which is statistically likely to exceed the item's actual common value. Rational bidders must preemptively adjust their bids downward to account for this adverse selection.

In blockchain contexts like Maximal Extractable Value (MEV) auctions or validator selection, these dynamics are paramount. Searchers bidding for the right to order transactions in a block face a first-price, sealed-bid auction. They must estimate the profit from their proposed bundle and shade their bid accordingly, all while contending with the Winner's Curse—overestimating network fees or future token prices can turn a winning bid into a net loss. Understanding these principles is essential for developers and analysts designing or participating in on-chain auction mechanisms.