Paper: arXiv 2610.03922

Authors: Pranay Anchuri, Edward W. Felten, Akaki Mamageishvili

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.

Complexity vs Empirical Score

  • Math Complexity: 7.5/10
  • Empirical Rigor: 8.0/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: This paper presents a highly rigorous empirical analysis of a novel phenomenon in blockchain economics, supported by a sophisticated auction model. The combination of advanced mathematical modeling and robust empirical methodology places it firmly in the ‘Holy Grail’ quadrant. Its findings offer significant practical implications for blockchain governance.

Research Flowchart

  flowchart TD
    A[Research Goal: How does auction cadence affect bidding and competition among automated arbitrageurs?] --> B{Methodology: Difference-in-Differences Design};
    B --> C[Data/Inputs: On-chain data from Base (July 2025 change from 1x 2s auction to 10x 200ms auctions), Address-day panel (3,032 searchers, 8,053 controls)];
    C --> D{Computational Processes: Estimate searcher response, Analyze fee structure (floor + premium), First-price auction model with uncertain arrival, Micro-auction model};
    D --> E[Key Findings/Outcomes: 0.187 gwei fall in effective priority fee (59% reduction), Fee compression identified, Share of fee value in first tenth of block gas falls from 0.98 to 0.28, Premium scales linearly with auction duration, Revert rate not causally identified, Latency decides ordering in 1.9-2.7% of contested opportunities, Diminishing returns below 200ms window];