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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

German

Flash-Parameter reduzieren nun eine Block-Prioritäts-Gas-Auktion in kürzere aufeinanderfolgende Auktionen, die Transaktionsbestellungen vor dem Block abgeschlossen haben. Wir fragen, wie diese niedrigere Auktionskadenz das Angebot und den Wettbewerb unter automatisierten Schiedsrichtern oder Suchern beeinflusst. Im Juli 2025 nahm die Basis eine einzelne 2 s-Auktion mit zehn 200 ms-Auktionen ab. Wir verwenden diese Änderung, um die Transaktionsantwort des Suchers aus den Daten der Block allein zu schätzen. Auf einem Adress-Tag-Panel von 3,032 Suchern und 8,053 Tätigkeits-komprimierten Kontrollen ist eine Differenz-in-Differenzen-Design eine Differenz-in-Differenz-Design schätzt

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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