Incentive-Compatible Collusion-Resistance via Posted Prices

Matheus V.X. Ferreira; Max Resnick; Yotam Gafni

REVIEW 3 major objections 4 minor 1 cited by

Incentive-Compatible Collusion-Resistance via Posted Prices

T0 review · 3 major / 4 minor · reviewed 2026-08-10 · deepseek-v4-flash

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Pith's one-line read For a single bidder with a regular value distribution, the collusion-safe fee mechanisms are exactly posted prices with a burn, at prices no higher than the revenue-maximizing price for that burn.

desk verdict Interesting and likely fixable, but the main theorem is false as stated because the collusion definitions allow trivial do-nothing collusions. read the letter →

arxiv 2412.20853 v1 pith:YCXTQBVZ submitted 2024-12-30 cs.GT econ.TH

Matheus V.X. Ferreira , Yotam Gafni , Max Resnick This is my paper · ORCID

classification cs.GTecon.TH MSC 91B0391B26

keywords transactionfeemechanismscollusionresistanceposted-priceauctionsincentivecompatibilityindividualrationalityvirtualvaluesblockchainmechanismdesignwelfare-revenuetrade-off

verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper argues that the standard definitions of collusion resistance in transaction fee mechanisms are too demanding because they let colluding parties trust one another completely, and it proposes a refinement: a collusion counts as a real threat only if it is itself incentive-compatible and individually rational for every participant. In the single-bidder case, the paper characterizes all deterministic dominant-strategy incentive-compatible (DSIC) mechanisms that resist such IC+IR collusions: for regular value distributions these are exactly posted-price auctions with a constant burn $b^*$ and a price $v^*$ satisfying $b^* \le v^* \le \mu(b^*)$, where $\mu(b^*)$ is the price that maximizes miner revenue given the burn. This shows that a non-trivial range of simple fee mechanisms, from zero miner revenue to optimal miner revenue, can be safe against collusion that is itself well-designed. The paper also derives welfare and revenue consequences of the characterization, including a welfare lower bound for monotone-hazard-rate distributions and a logarithmic lower bound on the best possible welfare-revenue trade-off.

What carries the argument

The load-bearing object is the burn-adjusted virtual value $\phi_\beta(v) = v - \frac{1-F(v)}{f(v)} - \beta$ and its associated revenue-maximizing price $\mu(\beta) = \arg\max_{\rho} E_{v\sim F}[1\{v \ge \rho\}(\rho-\beta)]$. In the single-bidder world every DSIC auction is a posted price with some burn, so a collusion can only act by transforming one posted price into another posted price. The monotonicity of $\phi_\beta$ for regular distributions is what makes the interval $[\beta, \mu(\beta)]$ exact: raising the price above $\mu(\beta)$ gives both parties room to collude downward, while below $\mu(\beta)$ any downward move lowers the miner's expected revenue and so fails individual rationality for the miner. The constant burn is the second essential piece: it is the only burning rule that survives IC-collusion resistance.

What would settle it

Take the uniform distribution on $[0,1]$ with burn $\beta=0.2$ and enumerate, over a fine grid of prices $v^*$, all single-bidder posted-price mechanisms with burn $0.2$; Theorem 3.5 predicts collusion-freeness exactly for $v^*\in[0.2,0.6]$. A brute-force search for any collusion $(c,t)$ satisfying the paper's IC conditions and ex-ante IR conditions that strictly improves both agents' expected utility at a price inside the interval---or fails to exist at a price above $0.6$---would refute the characterization. For non-regular distributions, computing the integral $\int_{v'}^{v^*} \phi_\beta(v) f(v)\,dv$ for each lower price $v'$ with $\phi_\beta(v')=0$ and checking whether the paper's excluded intervals in Example 3.3 match the sign of that integral would settle the non-regular claim.

Watch

Extended reading notes

Core claim

On the paper's own terms, the central discovery is a tight structural theorem. For a single bidder whose value distribution is regular (its virtual value function is nondecreasing), a deterministic transaction fee mechanism is DSIC and resistant to every incentive-compatible, individually rational collusion exactly when it is a posted price $v^*$ with a constant burn $b^*$, with $b^* \le v^* \le \mu(b^*)$. The upper bound $\mu(b^*)$ is the revenue-maximizing posted price for that burn, the analogue of the reserve price in a setting where the seller pays the burn. If the value distribution is not regular, the same interval description holds with an extra condition: prices $v^*$ are excluded whenever there is a lower price $v'$ at which the burn-adjusted virtual value is zero and the expected virtual surplus between $v'$ and $v^*$ is positive. Thus the safe mechanisms are exactly the posted-price-and-burn rules along a one-dimensional interval, with possible gaps in the non-regular case.

Load-bearing premise

The characterization assumes that the protocol includes no transaction whenever more than one bidder appears; the collusion-incentive condition quantifies over all bid vectors, so if multi-bidder behavior differed, the set of collusion-resistant mechanisms could change and the clean posted-price interval would need to be re-derived.

Editorial extensions

If this is right

For regular value distributions, every deterministic DSIC mechanism that resists incentive-compatible, individually rational collusion is exactly a posted price $v^*$ with constant burn $b^*$ and $b^* \le v^* \le \mu(b^*)$, so the designer's choice reduces to a one-dimensional interval.
The interval spans the full efficiency-revenue frontier in the single-bidder case: at the lower endpoint all miner revenue is burned away, at the upper endpoint the miner extracts the optimal revenue for that burn, and every point in between is achievable without opening a collusion hole.
Because collusion-free prices are bounded above by the revenue-maximizing price, they inherit a welfare guarantee: with monotone-hazard-rate distributions they achieve at least a $1/e$ fraction of optimal welfare.
The welfare guarantee cannot be improved in general: there are regular distributions where every collusion-free price loses a $\Omega(\log M)$ fraction of welfare, and the best simultaneous welfare-revenue approximation is $\Omega(\sqrt{\log M})$ for general distributions.
The non-regular case allows only a subset of that interval; prices in intervals where lowering the price increases the miner's ironed virtual surplus are colludable.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

The one-dimensional interval $[b^*, \mu(b^*)]$ suggests a practical tuning rule for protocols: set the burn to encode a revenue target and the price anywhere below the revenue-maximizing level to favor inclusion, without needing to audit complex allocation rules; this is an extension because the paper only characterizes the single-bidder case.
The IC+IR refinement may be portable to multi-bidder TFMs; the paper's off-path convention is a placeholder, and the real test is whether the posted-price interval survives when the auction must handle multiple real transactions.
The non-regular discontinuity result implies that empirical fee-setting should check whether the value distribution is regular before relying on the simple interval; small perturbations of a non-regular distribution can move a chosen price from safe to colludable.
The welfare lower bound says that for monotone-hazard-rate distributions, choosing any collusion-free price sacrifices at most a factor $e$ of welfare, which gives a quantitative argument for preferring posted-price-plus-burn fee markets over more complex designs.

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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Desk Editor's Note

read the letter

The first thing you should know: Theorem 3.5, the main characterization, is false under the paper's own formal definitions. The stress-test note is correct. Definitions 2.10-2.12 allow any pair (c,t) as a collusion, with IC and IR both using weak inequalities and no strict-benefit requirement. Take the posted-price mechanism with price v* and burn b* satisfying b* ≤ v* ≤ μ(b*). Define c to map only v*-1 to v*-2 and keep everything else fixed, with t ≡ 0. This changes a losing bid into another losing bid: the bidder is indifferent, the miner is indifferent, IR holds with equality, and DSIC of the original auction takes care of IC. So it is an IC+IR collusion against the mechanism, contradicting the theorem's "exactly" claim. The sufficiency proof says "it increases her utility," silently importing a strict-improvement assumption that the definitions do not contain.

What is genuinely good here: the conceptual point — that collusion should itself be incentive-compatible and individually rational — is a real step beyond the trusted-colluder assumptions in OCA and SCP. The single-bidder posted-price characterization with constant burn, once you patch the strictness issue, is a clean and non-obvious result, and the welfare/revenue trade-off analysis is a nice bonus. The paper engages seriously with prior work.

The soft spots are in proportion: the definitional gap is load-bearing and must be fixed before anything else. The fix is probably simple — require strict improvement for at least one participant, or Pareto-improvement — and then the proof's logic likely goes through, but that needs to be written out. Theorem 3.6 (non-regular) is stated without proof; Theorem 3.10's continuous conversion is hand-waved in a remark; Example 3.3 is found by trial and error; and the text is full of typos and incomplete sentences. None of these are fatal to the underlying idea, but they make the current version unsuitable for publication.

This paper deserves a serious referee — the contribution is substantive enough that an editor should not desk-reject it. But my recommendation is major revision, with the definitions tightened and the proofs completed. I'd bring it to a reading group to discuss the definitional bug and the fix, not because the result is settled.

Referee Report

3 major / 4 minor

Summary. The paper refines the notion of collusion resistance in transaction fee mechanisms (TFMs) by requiring that a collusion be itself incentive-compatible (IC) and individually rational (IR) for its participants. The main results characterize, for a single bidder, the deterministic DSIC and (IC+IR)-collusion-resistant auctions. Theorem 3.5 claims that for regular value distributions this class is exactly the posted-price mechanisms with a constant burn b* satisfying b* ≤ v* ≤ μ(b*), where μ(b*) is the revenue-maximizing price given the burn; Theorem 3.6 gives an analogous non-regular characterization with an additional integral condition. The paper also studies welfare and revenue trade-offs, including a lower bound on the welfare-revenue approximation factor (Theorem 3.10) and constructions for regular and non-regular distributions. The conceptual idea is interesting, but the formal definitions do not support the main characterization as stated.

Significance. If the definitions are repaired, the paper makes a useful conceptual point: requiring collusions to be self-enforcing (IC and IR) can rescue a nontrivial class of TFMs from the impossibility results for OCA-proofness and SCP. The interval characterization for regular distributions is elegant, and the explicit non-regular example and the log-approximation construction in Appendix B are valuable working examples. The paper does not ship machine-checked proofs or code, but it does give parameter-free structural derivations and concrete falsifiable predictions about which posted-price mechanisms survive the refined collusion notion. However, the central theorem is false under the definitions exactly as written, because outcome-preserving trivial collusions are not excluded; this is a load-bearing flaw that must be fixed before the results can be accepted.

major comments (3)

[Definitions 2.10–2.14 and Theorem 3.5] The formal definitions never require a collusion to be strictly profitable: Definition 2.12 uses weak inequalities for IR, and Definition 2.11 imposes the IC constraint only for bid vectors on which c is not the identity or t is not zero. As a result, an outcome-preserving change of bids is an IC+IR collusion. For any posted-price mechanism with v* > 0, choose two losing bids b_L < b_H < v*, define c(b_H) = b_L, c(b) = b otherwise, and t ≡ 0. At the only input where c differs from the identity, the bidder's utility under the collusion and under any deviation is 0, the miner's utility is 0 (including under fake-bid deviations, by the no-transaction multi-bidder convention), and IR holds with equality for both parties. The v* = 0 case is handled similarly by mapping any two positive bids to each other. Thus every posted-price mechanism admits an IC+IR n-collusion, contradicting the 'exactly' statement of Theorem 3.5 and the analogous claim in Theorem 3.6. The proof of Theorem 3.5 uses the phrase 'it increases her utility' when arguing IR, but Definition 2.12 does not require any strict increase. The definitions should be amended to require weak improvement for all participants and strict improvement for at least one participant (or an equivalent profitability condition), and the theorem statements and Example 3.3 should be re-verified under the amended definition.
[Theorem 3.6] The non-regular characterization is stated without proof. The text says it 'generally follows the same lines' and points to Example 3.3, but the additional integral condition (no v' < v* with φ_{b*}(v') = 0 and ∫_{v'}^{v*} φ_{b*}(v)f(v)dv > 0) is precisely where the regular distribution's monotonicity argument fails. Since Theorem 3.6 is one of the two main characterization theorems, a proof or a precise reduction to Proposition 3.2 is required; as written, the result is unverified and load-bearing for the paper's non-regular claims.
[Theorem 3.10 and Remark 3.11] The lower bound CGeneral(M) ∈ Ω(sqrt(log M)) is proved only for a discrete distribution with point masses, while the rest of the paper works with continuous distributions. Remark 3.11 concedes that the translation of the discrete regular example to a continuous regular distribution is not immediate and only offers a continuous non-regular conversion. Therefore the lower bound is not established for the continuous setting in which CGeneral appears to be defined, and Corollary 3.8's regular-distribution log M gap (supported by Appendix B) does not repair this. The theorem should either be stated for discrete distributions, the continuous conversion should be proved, or the claims should be adjusted accordingly.

minor comments (4)

[Proposition 3.3] The statement ends mid-sentence: 'When F is not regular, this is maximized when the posted price is set'. Please complete the sentence and justify the ironing argument for the non-regular case.
[References to appendices] The text refers to 'Appendix 3' before Example 3.3 and again near Corollary 3.8, but the appendices are labeled A, B, and C; these references should be corrected to Appendix A and Appendix B respectively.
[Definition 2.8] The DSIC definition includes the clause 'and there is such b_{-i} so that the inequality is strict', which is nonstandard and potentially ambiguous. If the strict clause is intended to rule out degenerate mechanisms, it should be stated separately, because as written it mixes the universal dominance condition with an existential non-triviality condition.
[Lemma 3.1] The proof uses notation such as a_i(c(b)) and SW_colluders without defining them, and the displayed derivation does not transparently show how summing the individual IR inequalities yields the claimed joint-welfare inequality. Please define the notation and expand the derivation.

Circularity Check

0 steps flagged · score 2.0 of 10

No significant circularity; the characterization is a consequence of the paper's own definitions applied to Myerson's standard single-bidder machinery, with one co-authored prior lemma used as independent support for an intermediate class.

full rationale

The paper does not fit any parameter and then rename it as a prediction. The single-bidder DSIC characterization (Prop 3.1) is the textbook Myerson/critical-bid argument with no burn constraints. Lemma 3.2 composes an IC collusion with a DSIC auction and observes that the result is DSIC; this is a direct transformation, not an assumption of the conclusion. Prop 3.3 is Myerson's virtual-value identity applied to miner revenue with a constant burn; the shift by beta is derived, not postulated as the characterization. The IC+IR collusion conditions (Defs 2.10-2.12) are new modeling postulates, and Theorems 3.5-3.6 solve the resulting mathematical problem. That is legitimate modeling, not circularity. The only self-citation that is load-bearing is the sufficiency direction of Prop 3.2, which cites Lemma 3.6 of Gafni-Yaish [7], a paper sharing an author, to show that posted-burn auctions are DSIC+1-OCA-proof. This is a prior, independent characterization theorem with its own proof; it is not a restatement of, or an input to, the present collusion definitions, and it is parameter-free with stated economic assumptions. Under the instructions, such a cited result counts as real evidence and does not raise the circularity score. The subsequent use of Prop 3.2 in Theorem 3.5 is therefore not a self-referential loop. Two non-circularity concerns should be noted separately. First, Section 3 explicitly assumes 'the protocol does not include any transaction in the multi-bidder case'; this is load-bearing for the miner side of the IC collusion condition, but it is an overt modeling assumption rather than a hidden reduction. Second, the reviewer's objection that Definitions 2.11-2.12 use weak inequalities and admit outcome-preserving collusions, so that 'no collusion' is not what the proof of Theorem 3.5 establishes, is a substantive correctness concern about the definitions; it does not make the derivation circular.

Assumptions & free parameters 4 free parameters · 6 assumptions · 0 invented entities

The central characterization rests on three pillars: standard Myerson machinery (axioms 1-2), the TFM modeling conventions inherited from the literature (axiom 3), and the paper's own definitional choices (axioms 4-6). Axiom 4 is particularly load-bearing: the single-bidder result depends on assuming away multi-bidder outcomes, and the paper does not test robustness to this choice. The hand-chosen example distributions are free parameters that illustrate, but do not prove, the general theorems.

free parameters (4)

Example 3.3 distribution coefficients = a1 ≈ 2.81, a2 ≈ 3.333, a3 ≈ 1.405 in F(v) = a1 v - a2 v^2 + a3 v^3
Hand-chosen (Appendix A: 'trial and error') to produce a non-regular distribution whose virtual value has the required sign pattern; no data or derivation justifies these values.
Example 3.3 support endpoint M = 1.20018
Chosen so that F(M) = 1 and the virtual value roots land at the desired collusion-free boundary. Ad hoc to the example.
Theorem 3.10 discrete distribution points and masses = v_i = 2^{i-1}, w_i = (1/2)^i for i < n; v_n = √n 2^{n-2}, w_n = (1/2)^{n-1}
Constructed to give each price i < n revenue 1 and price n revenue √n/2, producing the Ω(√log M) gap. Purely an example-specific construction.
Appendix B log-approximation distribution parameters T and epsilon = T ≥ epsilon (e.g., T = 2, epsilon = 1/2 in the figure)
Chosen so that the monopolistic price is T and the welfare gap is log T; the condition T ≥ epsilon is sufficient for T to be revenue-maximizing. Ad hoc.

assumptions (6)

standard math Myerson's characterization of dominant-strategy incentive-compatible auctions (monotone allocation, critical payments)
Used in Proposition 3.1 to reduce single-bidder DSIC to posted prices; foundational and cited [12].
standard math Regularity and ironing of virtual values for non-regular distributions
Used in Lemma 3.4, Propositions 3.3-3.4 and Theorems 3.5-3.6 to analyze revenue as a function of posted price.
domain assumption The transaction-fee-mechanism model: single item (block size 1), anonymous allocation/payment/burn rules, miner strategy functions that omit real bids and add fake bids (MMIC)
Adopted from the TFM literature (Roughgarden, Chung-Shi, Gafni-Yaish); all results are stated within this model.
ad hoc to paper The protocol's multi-bidder behavior is 'no transaction'
Stated in Section 3: 'the straight-forward assumption is that the protocol does not include any transaction in the multi-bidder case.' This off-path specification enters the IC collusion condition (Definition 2.11), which quantifies over all bid vectors.
ad hoc to paper The IC+IR collusion definitions (Definitions 2.10-2.12) are the appropriate refinement of collusion resistance
The paper's central modeling choice. The characterization is a consequence of these specific definitions; a different formalization could yield a different class.
ad hoc to paper Ex-post individual rationality for transfers within the collusion (Definition 2.10)
Requires each colluding bidder's utility to be non-negative after transfers in every realization; this bounds the collusion's ability to tax bidders and is part of the new definition.

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Cite this review

Pith. "Pith review of Incentive-Compatible Collusion-Resistance via Posted Prices." pith.science (2026). https://pith.science/paper/YCXTQBVZ

@misc{pith2026241220853,
  author       = {Pith},
  title        = {Pith review of: Incentive-Compatible Collusion-Resistance via Posted Prices},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/YCXTQBVZ}},
  note         = {Machine review of arXiv:2412.20853}
}

read the original abstract

We consider a refinement to the notions of collusion-resistance in transaction fee mechanisms. In particular, we require that the collusion is by itself incentive-compatible and individually rational to all of its participants. We then study the structural properties of these notions, and importantly, characterize the class of collusion-resistant and incentive-compatible transaction fee mechanisms in the single bidder case, and show that this is exactly the class of posted-price where the price is not too prohibitive. We analyze welfare and revenue implications, as well as the shape of the solution space, for both regular and non-regular distributions.

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Forward citations

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Works this paper leans on

19 extracted references · 6 canonical work pages · cited by 1 Pith paper

[1]

Core in a sim- ple coalition formation game

Suryapratim Banerjee, Hideo Konishi, and Tayfun Sönmez. Core in a sim- ple coalition formation game. Social Choice and Welfare , 18(1):135–153, 2001. doi:10.1007/s003550000067

doi:10.1007/s003550000067 2001
[2]

Bayesian mechanism design for blockchain transaction fee allocation, 2023.arXiv:2209.13099

Xi Chen, David Simchi-Levi, Zishuo Zhao, and Yuan Zhou. Bayesian mechanism design for blockchain transaction fee allocation, 2023.arXiv:2209.13099

arXiv 2023
[3]

Collusion-resilience in transaction fee mechanism design, 2024.arXiv:2402.09321

Hao Chung, Tim Roughgarden, and Elaine Shi. Collusion-resilience in transaction fee mechanism design, 2024.arXiv:2402.09321

arXiv 2024
[4]

Foundations of Transaction Fee Mechanism Design

Hao Chung and Elaine Shi. Foundations of transaction fee mechanism design, 2022. arXiv:2111.03151

work page Pith review arXiv 2022
[5]

Foundations of Transaction Fee Mechanism De- sign, pages 3856–3899

Hao Chung and Elaine Shi. Foundations of Transaction Fee Mechanism De- sign, pages 3856–3899. Society for Industrial and Applied Mathematics, 2023. URL: https://epubs.siam.org/doi/abs/10.1137/1.9781611977554.ch150, arXiv:https://epubs.siam.org/doi/pdf/10.1137/1.9781611977554.ch150, doi:10.1137/1.9781611977554.ch150

doi:10.1137/1.9781611977554.ch150 2023
[6]

Censorship resistance in on-chain auc- tions, 2023

Elijah Fox, Mallesh Pai, and Max Resnick. Censorship resistance in on-chain auc- tions, 2023. arXiv:2301.13321

arXiv 2023
[7]

Barriers to collusion-resistant transaction fee mech- anisms, 2024

Yotam Gafni and Aviv Yaish. Barriers to collusion-resistant transaction fee mech- anisms, 2024. arXiv:2402.08564

arXiv 2024
[8]

Matthew Weinberg

Aadityan Ganesh, Clayton Thomas, and S. Matthew Weinberg. Revisiting the primitives of transaction fee mechanism design. In Proceedings of the 25th ACM Conference on Economics and Computation , EC ’24, page 703, New York, NY, USA, 2024. Association for Computing Machinery. doi:10.1145/3670865. 3673621. Incentive-compatible Collusion-resistance via Posted ...

doi:10.1145/3670865 2024

Show all 19 references

[9]

Mechanism design and approximation

Jason D Hartline. Mechanism design and approximation. Book draft. October , 122(1), 2013

2013
[10]

Redesigning bitcoin’s fee market

Ron Lavi, Or Sattath, and Aviv Zohar. Redesigning bitcoin’s fee market. InThe World Wide Web Conference , WWW ’19, page 2950–2956, New York, NY, USA,
[11]

Non-regular distributions, virtual values and monopoly problems (preliminary version

Paolo Riccardo Morganti. Non-regular distributions, virtual values and monopoly problems (preliminary version. please do not circulate), 01 2022.doi:10.13140/ RG.2.2.34235.28964

2022
[12]

Optimal auction design

Roger B Myerson. Optimal auction design. Mathematics of operations research , 6(1):58–73, 1981. doi:10.1287/moor.6.1.58

1981 doi
[13]

Transaction fee mechanism design for the ethereum blockchain: An economic analysis of EIP-1559

Tim Roughgarden. Transaction fee mechanism design for the ethereum blockchain: An economic analysis of EIP-1559. CoRR, abs/2012.00854, 2020. URL: https: //arxiv.org/abs/2012.00854, arXiv:2012.00854

2012 arXiv
[14]

Transaction fee mechanism design, 2021.arXiv:2106.01340

Tim Roughgarden. Transaction fee mechanism design, 2021.arXiv:2106.01340

2021 arXiv
[15]

What can cryptography do for decentralized mechanism design, 2023.arXiv:2209.14462

Elaine Shi, Hao Chung, and Ke Wu. What can cryptography do for decentralized mechanism design, 2023.arXiv:2209.14462

2023 arXiv
[16]

Elaine Shi, Hao Chung, and Ke Wu. What can cryptography do for decentral- ized mechanism design? In Yael Tauman Kalai, editor,14th Innovations in The- oretical Computer Science Conference, ITCS 2023, January 10-13, 2023, MIT, Cambridge, Massachusetts, USA , volume 251 of LIPIc...

2023 doi
[17]

George J. Stigler. A theory of oligopoly.Journal of Political Economy, 72(1):44–61,
[1964]

A Constructing a Non-Regular Example for Collusion-free Prices In our Example 3.3 we wished to provide an explicit (and continuous) construc- tion

URL: http://www.jstor.org/stable/1828791. A Constructing a Non-Regular Example for Collusion-free Prices In our Example 3.3 we wished to provide an explicit (and continuous) construc- tion. It turns out that this is not a straight-forward task. One reason is that many of the k...
[2019]

Association for Computing Machinery.doi:10.1145/3308558.3313454

Pith tools

Reviewed August 10, 2026 · model on record in the stance chip above.

[1] [1]

Core in a sim- ple coalition formation game

Suryapratim Banerjee, Hideo Konishi, and Tayfun Sönmez. Core in a sim- ple coalition formation game. Social Choice and Welfare , 18(1):135–153, 2001. doi:10.1007/s003550000067

doi:10.1007/s003550000067 2001

[2] [2]

Bayesian mechanism design for blockchain transaction fee allocation, 2023.arXiv:2209.13099

Xi Chen, David Simchi-Levi, Zishuo Zhao, and Yuan Zhou. Bayesian mechanism design for blockchain transaction fee allocation, 2023.arXiv:2209.13099

arXiv 2023

[3] [3]

Collusion-resilience in transaction fee mechanism design, 2024.arXiv:2402.09321

Hao Chung, Tim Roughgarden, and Elaine Shi. Collusion-resilience in transaction fee mechanism design, 2024.arXiv:2402.09321

arXiv 2024

[4] [4]

Foundations of Transaction Fee Mechanism Design

Hao Chung and Elaine Shi. Foundations of transaction fee mechanism design, 2022. arXiv:2111.03151

work page Pith review arXiv 2022

[5] [5]

Foundations of Transaction Fee Mechanism De- sign, pages 3856–3899

Hao Chung and Elaine Shi. Foundations of Transaction Fee Mechanism De- sign, pages 3856–3899. Society for Industrial and Applied Mathematics, 2023. URL: https://epubs.siam.org/doi/abs/10.1137/1.9781611977554.ch150, arXiv:https://epubs.siam.org/doi/pdf/10.1137/1.9781611977554.ch150, doi:10.1137/1.9781611977554.ch150

doi:10.1137/1.9781611977554.ch150 2023

[6] [6]

Censorship resistance in on-chain auc- tions, 2023

Elijah Fox, Mallesh Pai, and Max Resnick. Censorship resistance in on-chain auc- tions, 2023. arXiv:2301.13321

arXiv 2023

[7] [7]

Barriers to collusion-resistant transaction fee mech- anisms, 2024

Yotam Gafni and Aviv Yaish. Barriers to collusion-resistant transaction fee mech- anisms, 2024. arXiv:2402.08564

arXiv 2024

[8] [8]

Matthew Weinberg

Aadityan Ganesh, Clayton Thomas, and S. Matthew Weinberg. Revisiting the primitives of transaction fee mechanism design. In Proceedings of the 25th ACM Conference on Economics and Computation , EC ’24, page 703, New York, NY, USA, 2024. Association for Computing Machinery. doi:10.1145/3670865. 3673621. Incentive-compatible Collusion-resistance via Posted ...

doi:10.1145/3670865 2024