Paper: arXiv 2610.16588

Authors: Farbod Ghasemlu

Abstract

Ethereum sells data-availability capacity to rollups through “blobs” priced by a controller: the blob fee rises and falls exponentially with cumulative usage above or below a target, and no auction sets it. We measure what this mechanical price costs. The Pectra upgrade of 7 May 2025 doubled blob capacity on a date fixed weeks in advance, while the market was congested, and the blob fee fell from 0.82 mETH per blob (about USD 1.40) to its 1-wei floor. Rollups’ blob purchases rose 24%. The 95% interval, built from the same estimator at 516 placebo dates, runs from 8% to 40%, so removing the entire price raised purchases by at most 40%. The implied elasticity at the pre-shock price is -0.19, and no value below -0.31 is consistent with the interval. The estimate includes any rise in L2 activity that coincided with the fork, so it bounds the price response from above. With demand this inelastic, the controller works mainly as a transfer. Rollups paid USD 14.8 million in blob fees under the first blob regime, 67% of it in two quarters when capacity was full and any market-clearing mechanism would have collected comparable scarcity rents. Where capacity was slack, the reserve price introduced in December 2025 cost at most 2.6 ETH (USD 8,039) in deadweight loss under the most elastic demand the data allow. Mempool records for 5.4 million blob transactions show that when the fee sits at its floor, capacity is slack: transactions miss about one block and are almost never priced out.

Complexity vs Empirical Score

  • Math Complexity: 6.0/10
  • Empirical Rigor: 9.0/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: This paper demonstrates strong empirical rigor through its use of a natural experiment and robust statistical methods, combined with a solid understanding of the underlying blockchain mechanics. Its novelty lies in providing the first empirical elasticity estimate for Ethereum’s blob market, with significant welfare implications. The paper is well-written and provides good detail for reproducibility.

Research Flowchart

  flowchart TD
    A[Research Goal: Measure Cost of Mechanical Price, Elasticity & Welfare in Ethereum's DA Market] --> B{Key Methodology: Observe Price Shock from Pectra Upgrade};
    B --> C[Data Inputs: Pectra Upgrade (May 2025) w/ 2x Blob Capacity, Blob Fee Data, 516 Placebo Dates, Mempool Records (5.4M Blob Tx)];
    C --> D{Computational Processes: Measure Blob Purchases Pre/Post Shock, Estimate Elasticity, Calculate Deadweight Loss, Analyze Tx Confirmation Times};
    D --> E[Key Finding 1: Blob Purchases Rose 24% (Max 40%) after Price Fall to Floor];
    E --> F[Key Finding 2: Implied Elasticity at Pre-Shock Price: -0.19 (No value below -0.31 consistent)];
    F --> G[Key Finding 3: Controller Acts as Transfer (Inelastic Demand), $14.8M in Blob Fees (67% Scarcity Rents), Max $8,039 DWL in Slack Periods];
    G --> H[Key Finding 4: When Fee is at Floor, Capacity is Slack (Tx rarely priced out, miss ~1 block)];