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Priority Gas Auction Cadence and Searcher Competition: Evidence from Flashblocks on Base

Pranay Anchuri, Edward W. Felten, Akaki Mamageishvili · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.03922 · cited by 0 works (OpenAlex) · open-access PDF

Portuguese

Os parâmetros de flash diminui agora para dividir o leilão de gás de prioridade de um bloco em leilões sequenciais mais curtos que cometem a ordem de transação antes que o bloco seja completo. Perguntamos como essa taxa de leilão mais baixa afeta a licitação e a concorrência entre os árbitros automatizados ou os pesquisadores. Em julho de 2025, a Base substituiu um leilão de gás de prioridade único de 2 s por dez leilões de 200 ms. Usamos esta mudança para estimar a resposta do buscador a partir dos dados da cadeia sozinho. Em um painel de endereço de 3032 pesquisadores e 8 053 controles de taxa de descompressão de atividades, um design de diferença-em-diferenças informa como uma queda de 0,187

Machine translation (Meta M2M100); the English original follows.

Abstract

Flashblocks divide a block's priority gas auction into shorter sequential auctions that commit transaction order before the block is complete. We ask how this auction cadence affects bidding and competition among automated arbitrageurs, or searchers. In July 2025 Base replaced a single 2 s auction with ten 200 ms auctions. We use this change to estimate the searcher response from on-chain data alone. On an address-day panel of 3,032 searchers and 8,053 activity-matched controls, a difference-in-differences design estimates a 0.187 gwei fall in the effective priority fee (59% of the searcher pre-period mean). The share of searcher priority-fee value paid in the first tenth of block gas falls from 0.98 to 0.28. This fee compression is the identified effect. The revert-rate response is not (causally) identified and is reported descriptively. At the level of a single opportunity, the winning fee splits into an approximately invariant floor and a competitive premium. The premium scales about linearly with auction duration at high contention and less steeply at low contention. A first-price auction model with uncertain arrival and partial payments by losing searchers accounts for this pattern. We match attempts to the pool they contest. A higher-fee transaction reverts behind a lower-fee winner that landed earlier in 1.9 to 2.7% of contested opportunities by value, an upper bound. Latency therefore decides part of the ordering. A micro-auction model projects diminishing returns from shortening the window below 200 ms, as bids approach a nonzero floor. Rollups such as Arbitrum One now make auction cadence a governance tunable parameter, so these estimates inform how it is set.

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Topics: Bidding, Vickrey–Clarke–Groves auction, English auction, Common value auction, Commit, Computer science

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