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
Los parámetros de flash ahora disminuyen, por lo que la subasta de gas de prioridad de un bloque se divide en subastas secuenciales más cortas que cometen la orden de transacción antes de que el bloque esté completo. Preguntamos cómo esta cadencia de subasta afecta a la licitación y la competencia entre los árbitros automatizados o los buscadores. En julio de 2025 la Base sustituyó a una subasta de gas de prioridad de 2 s por diez subastas de 200 ms. Utilizamos este cambio para estimar la respuesta del buscador a partir de los datos de la cadena solo. En un panel de día de dirección de 3,032 buscadores y 8,053 controles de compresiones de tasas de actividad, un diseño de diferencia-en-diferencias de información estima una caída de 0,187 gwei en la tasa efectiva de prioridad (5
Machine translation (Meta M2M100); the English original follows.
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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