Auction-Theoretic MEV Tax

• Auction-Theoretic MEV Tax is a mechanism that leverages auction design to convert blockchain MEV into regulated protocol revenue through structured tax schemes.
• It employs various auction formats, such as FPSB, SPSB, and Timeboost, to balance bid shading, revenue extraction, and decentralization in competitive environments.
• Empirical and theoretical analyses calibrate optimal tax rates and auction parameters, addressing trade-offs between welfare distribution, user rebates, and centralized incentives.

An auction-theoretic MEV tax is a mechanism that leverages auction design to convert maximal extractable value (MEV)—the economic rents from transaction ordering, inclusion, or censorship in blockchains—into explicit, systematized protocol revenue or user rebates, rather than allowing these rents to dissipate inefficiently among searchers, sequencers, or builders. By embedding MEV capture within principled auction formats and related tax structures, such mechanisms enforce competitive allocation of blockspace and redistribute extracted surplus according to rigorously defined rules. This approach enables precise calibration of welfare, revenue, and decentralization properties in next-generation blockchain protocols.

1. Auction-Theoretic Models of MEV Extraction

Core auction-theoretic frameworks analyze MEV extraction as a competition for block inclusion and ordering rights among $n$ symmetric (or nearly symmetric) searchers or builders. Valuations are typically modeled under a log-normal distribution with right-tail concentration, reflecting empirical MEV data, and inter-bidder affiliation is incorporated via Gaussian common-factor models. Let each searcher's signal be $$x_i = \sqrt{\rho}\, X + \sqrt{1-\rho}\, \varepsilon_i$$ for $X, \varepsilon_i \sim \mathcal{N}(0,1)$, where $\rho \in [0,1]$ quantifies affiliation. The value from a block opportunity is $V_i = \exp(\mu + \sigma x_i)$ (Adadurov et al., 17 Mar 2026).

Auction formats studied include first-price (FPSB), second-price (SPSB), English, Dutch, and all-pay. The equilibrium bid functions and expected revenue expressions vary according to format, number of bidders $n$, and affiliation $\rho$:

Format	Equilibrium strategy $\beta(v)$	Expected revenue $R$
FPSB/Dutch	$v - \frac{\int_0^v F(y)^{n-1}dy}{F(v)^{n-1}}$	$$x_i = \sqrt{\rho}\, X + \sqrt{1-\rho}\, \varepsilon_i$$0
SPSB/English	$$x_i = \sqrt{\rho}\, X + \sqrt{1-\rho}\, \varepsilon_i$$1 (truthful)	$$x_i = \sqrt{\rho}\, X + \sqrt{1-\rho}\, \varepsilon_i$$2
All-pay	$$x_i = \sqrt{\rho}\, X + \sqrt{1-\rho}\, \varepsilon_i$$3	$$x_i = \sqrt{\rho}\, X + \sqrt{1-\rho}\, \varepsilon_i$$4

The classic Revenue Equivalence Theorem fails for $$x_i = \sqrt{\rho}\, X + \sqrt{1-\rho}\, \varepsilon_i$$5 (searchers' values are affiliated), breaking symmetry between formats. The Milgrom-Weber linkage principle holds: formats revealing more information (English/SPSB) extract greater revenue than opaque ones (FPSB/Dutch), with an empirical linkage gap in the 14–28% range for moderate affiliation and up to 30% for low $$x_i = \sqrt{\rho}\, X + \sqrt{1-\rho}\, \varepsilon_i$$6. Empirically observed bribe data for MEV auctions on Ethereum confirms substantial lost revenue from non-optimal format selection (Adadurov et al., 17 Mar 2026).

2. Proportional MEV Tax: Design and Equilibrium Effects

A direct auction-theoretic MEV tax is implemented by imposing a proportional tax $$x_i = \sqrt{\rho}\, X + \sqrt{1-\rho}\, \varepsilon_i$$7 on the winning bid (e.g., in FPSB). The winner pays $$x_i = \sqrt{\rho}\, X + \sqrt{1-\rho}\, \varepsilon_i$$8 to the builder and $$x_i = \sqrt{\rho}\, X + \sqrt{1-\rho}\, \varepsilon_i$$9 to the protocol (or DAO). The modified equilibrium in FPSB is given by the solution to

$X, \varepsilon_i \sim \mathcal{N}(0,1)$0

The expected tax revenue is

$X, \varepsilon_i \sim \mathcal{N}(0,1)$1

with optimal $X, \varepsilon_i \sim \mathcal{N}(0,1)$2 determined numerically by maximizing $X, \varepsilon_i \sim \mathcal{N}(0,1)$3 (i.e., $X, \varepsilon_i \sim \mathcal{N}(0,1)$4). As $X, \varepsilon_i \sim \mathcal{N}(0,1)$5 increases, strategic bid-shading by searchers suppresses equilibrium bids; thus, "Laffer curve" dynamics arise and prohibit arbitrarily high tax rates. Pilot calibrations suggest $X, \varepsilon_i \sim \mathcal{N}(0,1)$6–$X, \varepsilon_i \sim \mathcal{N}(0,1)$7 for moderate $X, \varepsilon_i \sim \mathcal{N}(0,1)$8 and $X, \varepsilon_i \sim \mathcal{N}(0,1)$9 (Adadurov et al., 17 Mar 2026).

Trade-offs include:

• Higher $\rho \in [0,1]$0 induces greater bid shading and may deter low-value auctions by tightening participation constraints.
• Overly aggressive taxation can suppress both builder and protocol revenues.
• Implementation may require on-chain integration or trusted off-chain enforcement.

Protocols must monitor realized MEV tax revenues, recalibrating $\rho \in [0,1]$1 as the competitive landscape evolves.

3. MEV Tax in Layer-2 Priority Auctions: The Timeboost Mechanism

Layer-2 protocols facing high-frequency MEV extraction often experience transaction spam, as agents submit many near-identical copies in first-come, first-served (FCFS) environments. The Timeboost mechanism, as implemented on Arbitrum, transforms the latency race into a sealed-bid, second-price auction for a fixed time advantage $\rho \in [0,1]$2 (Zhu, 10 Dec 2025).

Key mechanics:

• Bidders compete for an “express lane”; highest bid wins, losers’ transactions are artificially delayed by $\rho \in [0,1]$3.
• In equilibrium, the expected incremental value of the timing edge ($\rho \in [0,1]$4) defines the symmetric bid in the sealed-bid auction.
• The total protocol (sequencer/DAO) revenue under Timeboost is $\rho \in [0,1]$5, typically exceeding the FCFS equilibrium revenue $\rho \in [0,1]$6 as the protocol captures up-front bids rather than dissipating rents as revert fees.

The effective MEV tax rate is $\rho \in [0,1]$7, which dominates the FCFS tax rate and approaches full rent extraction as $\rho \in [0,1]$8 increases. Empirical studies confirm reduced spam (–0.70 SD log RepTXs) and increased sequencer revenue (+0.71 SD) post-adoption, validating theoretical predictions (Zhu, 10 Dec 2025).

4. MEV Tax via Order Flow Auctions under Proposer-Builder Separation

The order-flow auction (OFA), especially within Proposer-Builder Separation (PBS), implements a two-stage auction system for MEV extraction (Ma et al., 17 Feb 2025):

• OFAs assign a fraction $\rho \in [0,1]$9 of each winning builder’s bid as direct rebates to users, with the remainder $V_i = \exp(\mu + \sigma x_i)$0 accruing to proposers as block rewards.
• Builders and proposers thus compete in linked auctions, with builder $V_i = \exp(\mu + \sigma x_i)$1’s expected payoff given by

$V_i = \exp(\mu + \sigma x_i)$2

where $V_i = \exp(\mu + \sigma x_i)$3, and $V_i = \exp(\mu + \sigma x_i)$4 are intrinsic flow and auctioned order values.

At Nash equilibrium, derived via quartic equations, the system taxes builder rents at rate $V_i = \exp(\mu + \sigma x_i)$5, rebating that share to users by construction. Larger $V_i = \exp(\mu + \sigma x_i)$6 increases welfare reallocations but lowers builder payment incentives; builder-side centralization is enhanced when top builders "escape" the tax, while validator shares remain stochastically decentralized due to the martingale property of proportional reward updates.

Proper parameterization of $V_i = \exp(\mu + \sigma x_i)$7 is essential to balance user welfare, network security, and competitive builder participation (Ma et al., 17 Feb 2025).

5. Prior-Free MEV-Tax Mechanisms: Rebates, Shapley Values, and Sybil-Proofness

Auction-theoretic MEV tax designs can be generalized beyond parametric or distributional assumptions by leveraging prior-free, permissionless rebate mechanisms (Mazorra et al., 2023). Here, the protocol sets aside a fraction $V_i = \exp(\mu + \sigma x_i)$8 of extracted MEV as a tax pool, distributing it among included users as rebates:

• Users submit sealed bids for block inclusion; builder solves a welfare-maximizing allocation $V_i = \exp(\mu + \sigma x_i)$9 where $n$0 is joint MEV.
• Rebates to users in $n$1 are determined via a value-division operator (e.g., Shapley value or a Sybil-proof alternative).
• The builder’s net revenue is $n$2.

Strong incentive constraints apply:

• Sybil-proofness impossibility: No operator is simultaneously efficient, symmetric, additive, and fully Sybil-proof; thus, approximate operators (e.g., $n$3) are constructed to guarantee a worst-case user welfare share ($n$4 for block size $n$5).
• Implementation is feasible thanks to small bundle size in practice and tractable computation of threshold payments and rebates.

This approach provides maximal flexibility for chain-level governance, enabling on-chain adjustment of the tax rate $n$6 and supporting modular integration with diverse MEV management architectures (Mazorra et al., 2023).

6. Synthesis: Optimal Design, Trade-offs, and Practical Recommendations

Empirical and theoretical analyses converge on the following design and deployment principles for auction-theoretic MEV taxes:

• Truthful (SPSB/English) auction formats maximize gross protocol revenue for any $n$7; linkage gaps (relative to FPSB/Dutch) yield $n$8–$n$9 revenue improvements in observed parameter regimes, with format choice critical for high-stakes MEV events (Adadurov et al., 17 Mar 2026).
• Protocol-level MEV taxes can be calibrated by optimizing expected tax revenue curves, with $\rho$0 typically in the $\rho$1–$\rho$2 range for moderate $\rho$3 and $\rho$4.
• Layer-2 implementations, such as Timeboost, eliminate inefficiencies due to revert fee spam and convert dissipated rents into explicit DAO revenue; the auction for transaction priority functions as a canonical MEV tax (Zhu, 10 Dec 2025).
• Under OFA/PBS architectures, parameter $\rho$5 tunes the explicit tax/rebate rate, directly addressing welfare allocation and centralization trade-offs. Governance of this lever is essential for robust protocol operation (Ma et al., 17 Feb 2025).
• Finally, prior-free, combinatorial approaches via Sybil-proof rebate operators generalize MEV taxation, achieving budget balance, incentive compatibility, and resistance to false-name attacks with worst-case welfare guarantees (Mazorra et al., 2023).

Practical implementation requires:

1. Empirical estimation of key parameters: $\rho$6 from transaction logs; $\rho$7 by matching statistical MEV regularities.
2. Periodic recalibration based on realized revenues and auction outcomes.
3. Mechanism segmentation: deploying high-revenue, high-complexity formats (SPSB/English, OFA, Timeboost) for low-$\rho$8, medium-$\rho$9 events, and operationally simpler formats (FPSB/Dutch) for high-$\beta(v)$0, high-$\beta(v)$1 contexts.
4. Ongoing monitoring for equilibrium breakdowns or shifts in market structure that might call for parameter adjustment or mechanism redesign.

Auction-theoretic MEV tax frameworks enlarge the protocol designer’s arsenal, enabling fine-grained extraction and distribution of MEV consistent with both system efficiency and welfare objectives.