This paper investigates which alternative benefits from vote delegation in binary collective decisions within blockchains. We begin by examining two extreme cases of voting weight distributions: Equal-Weight (EW), where each voter has equal voting weight, and Dominant-Weight (DW), where a single voter holds a majority of the voting weights before any delegation occurs. We show that vote delegation tends to benefit the ex-ante minority under EW, i.e., the alternative with a lower initial probability of winning. The converse holds under DW distribution. Through numerical simulations, we extend our findings to arbitrary voting weight distributions, showing that vote delegation benefits the ex-ante majority when it leads to a more balanced distribution of voting weights. Finally, in large communities where all agents have equal voting weight, vote delegation has a negligible impact on the outcome. These insights provide practical guidance for governance decisions in blockchains.
本文研究了在区块链的二元集体决策中，哪种选择能从投票授权中获益。我们首先研究了投票权重分布的两种极端情况：等权重（EW），即每个投票者拥有相等的投票权重；多权重（DW），即在任何委托发生之前，单个投票者拥有多数投票权重。我们的研究表明，在 EW 分配下，投票委托往往有利于事前的少数派，即初始获胜概率较低的备选方案。反之，在 DW 分布下则成立。通过数值模拟，我们将研究结果扩展到了任意投票权重分布上，结果表明，当投票权重分布更均衡时，投票委托会使事前多数人受益。最后，在所有代理人投票权重相等的大型社区中，投票委托对结果的影响可以忽略不计。这些见解为区块链的治理决策提供了实际指导。
{"title":"Effects of Vote Delegation in Blockchains: Who Wins?","authors":"Hans Gersbach, Manvir Schneider, Parnian Shahkar","doi":"arxiv-2408.05410","DOIUrl":"https://doi.org/arxiv-2408.05410","url":null,"abstract":"This paper investigates which alternative benefits from vote delegation in\u0000binary collective decisions within blockchains. We begin by examining two\u0000extreme cases of voting weight distributions: Equal-Weight (EW), where each\u0000voter has equal voting weight, and Dominant-Weight (DW), where a single voter\u0000holds a majority of the voting weights before any delegation occurs. We show\u0000that vote delegation tends to benefit the ex-ante minority under EW, i.e., the\u0000alternative with a lower initial probability of winning. The converse holds\u0000under DW distribution. Through numerical simulations, we extend our findings to\u0000arbitrary voting weight distributions, showing that vote delegation benefits\u0000the ex-ante majority when it leads to a more balanced distribution of voting\u0000weights. Finally, in large communities where all agents have equal voting\u0000weight, vote delegation has a negligible impact on the outcome. These insights\u0000provide practical guidance for governance decisions in blockchains.","PeriodicalId":501188,"journal":{"name":"arXiv - ECON - Theoretical Economics","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142197143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes a geometric approach for estimating the $alpha$ value in Q learning. We establish a systematic framework that optimizes the {alpha} parameter, thereby enhancing learning efficiency and stability. Our results show that there is a relationship between the learning rate and the angle between a vector T (total time steps in each episode of learning) and R (the reward vector for each episode). The concept of angular bisector between vectors T and R and Nash Equilibrium provide insight into estimating $alpha$ such that the algorithm minimizes losses arising from exploration-exploitation trade-off.
本文提出了一种在 Q 学习中估计 $alpha$ 值的几何方法。我们建立了一个系统框架来优化{alpha}参数，从而提高学习效率和稳定性。我们的研究结果表明，学习率与向量 T（每集学习的总时间步数）和 R（每集的前进向量）之间的夹角有一定的关系。向量 T 和 R 之间的角平分线概念以及纳什均衡为估计 $alpha$ 提供了启示，从而使算法最大限度地减少探索-开发-权衡所造成的损失。
{"title":"A Geometric Nash Approach in Tuning the Learning Rate in Q-Learning Algorithm","authors":"Kwadwo Osei Bonsu","doi":"arxiv-2408.04911","DOIUrl":"https://doi.org/arxiv-2408.04911","url":null,"abstract":"This paper proposes a geometric approach for estimating the $alpha$ value in\u0000Q learning. We establish a systematic framework that optimizes the {alpha}\u0000parameter, thereby enhancing learning efficiency and stability. Our results\u0000show that there is a relationship between the learning rate and the angle\u0000between a vector T (total time steps in each episode of learning) and R (the\u0000reward vector for each episode). The concept of angular bisector between\u0000vectors T and R and Nash Equilibrium provide insight into estimating $alpha$\u0000such that the algorithm minimizes losses arising from exploration-exploitation\u0000trade-off.","PeriodicalId":501188,"journal":{"name":"arXiv - ECON - Theoretical Economics","volume":"48 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141968813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Imagine that a large increment can be given to an individual in a society. We ask: what is the maximal sacrifice that can be imposed on another individual according to an evaluator for the sake of this increment? We show that the answer can reveal how inequality averse an evaluator is. In particular, all Kolm-Pollak evaluators would sacrifice the full income of the sacrificed individual if their income was low enough and a declining fraction of their income otherwise. Kolm-Atkinson evaluators would sacrifice the full income of the sacrificed individual, for all income levels, if their inequality aversion was no greater than one, and sacrifice a constant fraction of their income otherwise. Motivated by these findings, we propose a class of social preferences that, starting from a baseline level of protection, protect a higher fraction of the sacrificed individual's income the lower their income. In addition to relating levels of protected income to coefficients of inequality, we also characterize the classes of additively separable social welfare functions that guarantee specific (absolute or relative) levels of protection.
{"title":"Protected Income and Inequality Aversion","authors":"Marc Fleurbaey, Eduardo Zambrano","doi":"arxiv-2408.04814","DOIUrl":"https://doi.org/arxiv-2408.04814","url":null,"abstract":"Imagine that a large increment can be given to an individual in a society. We\u0000ask: what is the maximal sacrifice that can be imposed on another individual\u0000according to an evaluator for the sake of this increment? We show that the\u0000answer can reveal how inequality averse an evaluator is. In particular, all\u0000Kolm-Pollak evaluators would sacrifice the full income of the sacrificed\u0000individual if their income was low enough and a declining fraction of their\u0000income otherwise. Kolm-Atkinson evaluators would sacrifice the full income of\u0000the sacrificed individual, for all income levels, if their inequality aversion\u0000was no greater than one, and sacrifice a constant fraction of their income\u0000otherwise. Motivated by these findings, we propose a class of social\u0000preferences that, starting from a baseline level of protection, protect a\u0000higher fraction of the sacrificed individual's income the lower their income.\u0000In addition to relating levels of protected income to coefficients of\u0000inequality, we also characterize the classes of additively separable social\u0000welfare functions that guarantee specific (absolute or relative) levels of\u0000protection.","PeriodicalId":501188,"journal":{"name":"arXiv - ECON - Theoretical Economics","volume":"71 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141968814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Throughout history, many countries have repeatedly experienced large swings in asset prices, which are usually accompanied by large fluctuations in macroeconomic activity. One of the characteristics of the period before major economic fluctuations is the emergence of new financial products; the situation prior to the 2008 financial crisis is a prominent example of this. During that period, a variety of structured bonds, including securitized products, appeared. Because of the high returns on such financial products, many economic agents were involved in them for speculative purposes, even if they were riskier, producing macro-scale effects. With this motivation, we present a simple macroeconomic model with financial speculation. Our model illustrates two points. First, stochastic fluctuations in asset prices and macroeconomic activity are driven by the repeated appearance and disappearance of risky financial assets, rather than expansions and contractions in credit availability. Second, in an economy with sufficient borrowing and lending, the appearance of risky financial assets leads to decreased productive capital, while in an economy with severely limited borrowing and lending, it leads to increased productive capital.
{"title":"Recurrent Stochastic Fluctuations with Financial Speculation","authors":"Tomohiro Hirano","doi":"arxiv-2408.05047","DOIUrl":"https://doi.org/arxiv-2408.05047","url":null,"abstract":"Throughout history, many countries have repeatedly experienced large swings\u0000in asset prices, which are usually accompanied by large fluctuations in\u0000macroeconomic activity. One of the characteristics of the period before major\u0000economic fluctuations is the emergence of new financial products; the situation\u0000prior to the 2008 financial crisis is a prominent example of this. During that\u0000period, a variety of structured bonds, including securitized products,\u0000appeared. Because of the high returns on such financial products, many economic\u0000agents were involved in them for speculative purposes, even if they were\u0000riskier, producing macro-scale effects. With this motivation, we present a simple macroeconomic model with financial\u0000speculation. Our model illustrates two points. First, stochastic fluctuations\u0000in asset prices and macroeconomic activity are driven by the repeated\u0000appearance and disappearance of risky financial assets, rather than expansions\u0000and contractions in credit availability. Second, in an economy with sufficient\u0000borrowing and lending, the appearance of risky financial assets leads to\u0000decreased productive capital, while in an economy with severely limited\u0000borrowing and lending, it leads to increased productive capital.","PeriodicalId":501188,"journal":{"name":"arXiv - ECON - Theoretical Economics","volume":"193 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141933569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We introduce a framework where the announcements of a clearinghouse about the allocation process are opaque in the sense that there can be more than one outcome compatible with a realization of type reports. We ask whether desirable properties can be ensured under opacity in a robust sense. A property can be guaranteed under an opaque announcement if every mechanism compatible with it satisfies the property. We find an impossibility result: strategy-proofness cannot be guaranteed under any level of opacity. In contrast, in some environments, weak Maskin monotonicity and non-bossiness can be guaranteed under opacity.
{"title":"Robust Market Design with Opaque Announcements","authors":"Aram Grigoryan, Markus Möller","doi":"arxiv-2408.04509","DOIUrl":"https://doi.org/arxiv-2408.04509","url":null,"abstract":"We introduce a framework where the announcements of a clearinghouse about the\u0000allocation process are opaque in the sense that there can be more than one\u0000outcome compatible with a realization of type reports. We ask whether desirable\u0000properties can be ensured under opacity in a robust sense. A property can be\u0000guaranteed under an opaque announcement if every mechanism compatible with it\u0000satisfies the property. We find an impossibility result: strategy-proofness\u0000cannot be guaranteed under any level of opacity. In contrast, in some\u0000environments, weak Maskin monotonicity and non-bossiness can be guaranteed\u0000under opacity.","PeriodicalId":501188,"journal":{"name":"arXiv - ECON - Theoretical Economics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141933624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Simon Dima, Simon Fischer, Jobst Heitzig, Joss Oliver
In dynamic programming and reinforcement learning, the policy for the sequential decision making of an agent in a stochastic environment is usually determined by expressing the goal as a scalar reward function and seeking a policy that maximizes the expected total reward. However, many goals that humans care about naturally concern multiple aspects of the world, and it may not be obvious how to condense those into a single reward function. Furthermore, maximization suffers from specification gaming, where the obtained policy achieves a high expected total reward in an unintended way, often taking extreme or nonsensical actions. Here we consider finite acyclic Markov Decision Processes with multiple distinct evaluation metrics, which do not necessarily represent quantities that the user wants to be maximized. We assume the task of the agent is to ensure that the vector of expected totals of the evaluation metrics falls into some given convex set, called the aspiration set. Our algorithm guarantees that this task is fulfilled by using simplices to approximate feasibility sets and propagate aspirations forward while ensuring they remain feasible. It has complexity linear in the number of possible state-action-successor triples and polynomial in the number of evaluation metrics. Moreover, the explicitly non-maximizing nature of the chosen policy and goals yields additional degrees of freedom, which can be used to apply heuristic safety criteria to the choice of actions. We discuss several such safety criteria that aim to steer the agent towards more conservative behavior.
{"title":"Non-maximizing policies that fulfill multi-criterion aspirations in expectation","authors":"Simon Dima, Simon Fischer, Jobst Heitzig, Joss Oliver","doi":"arxiv-2408.04385","DOIUrl":"https://doi.org/arxiv-2408.04385","url":null,"abstract":"In dynamic programming and reinforcement learning, the policy for the\u0000sequential decision making of an agent in a stochastic environment is usually\u0000determined by expressing the goal as a scalar reward function and seeking a\u0000policy that maximizes the expected total reward. However, many goals that\u0000humans care about naturally concern multiple aspects of the world, and it may\u0000not be obvious how to condense those into a single reward function.\u0000Furthermore, maximization suffers from specification gaming, where the obtained\u0000policy achieves a high expected total reward in an unintended way, often taking\u0000extreme or nonsensical actions. Here we consider finite acyclic Markov Decision Processes with multiple\u0000distinct evaluation metrics, which do not necessarily represent quantities that\u0000the user wants to be maximized. We assume the task of the agent is to ensure\u0000that the vector of expected totals of the evaluation metrics falls into some\u0000given convex set, called the aspiration set. Our algorithm guarantees that this\u0000task is fulfilled by using simplices to approximate feasibility sets and\u0000propagate aspirations forward while ensuring they remain feasible. It has\u0000complexity linear in the number of possible state-action-successor triples and\u0000polynomial in the number of evaluation metrics. Moreover, the explicitly\u0000non-maximizing nature of the chosen policy and goals yields additional degrees\u0000of freedom, which can be used to apply heuristic safety criteria to the choice\u0000of actions. We discuss several such safety criteria that aim to steer the agent\u0000towards more conservative behavior.","PeriodicalId":501188,"journal":{"name":"arXiv - ECON - Theoretical Economics","volume":"370 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141933527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We consider the problem of rationalizing choice data by a preference satisfying an arbitrary collection of invariance axioms. Examples of such axioms include quasilinearity, homotheticity, independence-type axioms for mixture spaces, constant relative/absolute risk and ambiguity aversion axioms, stationarity for dated rewards or consumption streams, separability, and many others. We provide necessary and sufficient conditions for invariant rationalizability via a novel approach which relies on tools from the theoretical computer science literature on automated theorem proving. We also establish a generalization of the Dushnik-Miller theorem, which we use to give a complete description of the out-of-sample predictions generated by the data under any such collection of axioms.
{"title":"Revealed Invariant Preference","authors":"Peter Caradonna, Christopher P. Chambers","doi":"arxiv-2408.04573","DOIUrl":"https://doi.org/arxiv-2408.04573","url":null,"abstract":"We consider the problem of rationalizing choice data by a preference\u0000satisfying an arbitrary collection of invariance axioms. Examples of such\u0000axioms include quasilinearity, homotheticity, independence-type axioms for\u0000mixture spaces, constant relative/absolute risk and ambiguity aversion axioms,\u0000stationarity for dated rewards or consumption streams, separability, and many\u0000others. We provide necessary and sufficient conditions for invariant\u0000rationalizability via a novel approach which relies on tools from the\u0000theoretical computer science literature on automated theorem proving. We also\u0000establish a generalization of the Dushnik-Miller theorem, which we use to give\u0000a complete description of the out-of-sample predictions generated by the data\u0000under any such collection of axioms.","PeriodicalId":501188,"journal":{"name":"arXiv - ECON - Theoretical Economics","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141933513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A sender has a privately known preference over the action chosen by a receiver. The sender would like to influence the receiver's decision by providing information, in the form of a statistical experiment or test. The technology for information production is controlled by a monopolist intermediary, who offers a menu of tests and prices to screen the sender's type, possibly including a "threat" test to punish nonparticipation. We characterize the intermediary's optimal screening menu and the associated distortions, which we show may benefit the receiver. We compare the sale of persuasive information with other forms of influence -- overt bribery and controlling access.
{"title":"The Design and Price of Influence","authors":"Raphael Boleslavsky, Aaron Kolb","doi":"arxiv-2408.03689","DOIUrl":"https://doi.org/arxiv-2408.03689","url":null,"abstract":"A sender has a privately known preference over the action chosen by a\u0000receiver. The sender would like to influence the receiver's decision by\u0000providing information, in the form of a statistical experiment or test. The\u0000technology for information production is controlled by a monopolist\u0000intermediary, who offers a menu of tests and prices to screen the sender's\u0000type, possibly including a \"threat\" test to punish nonparticipation. We\u0000characterize the intermediary's optimal screening menu and the associated\u0000distortions, which we show may benefit the receiver. We compare the sale of\u0000persuasive information with other forms of influence -- overt bribery and\u0000controlling access.","PeriodicalId":501188,"journal":{"name":"arXiv - ECON - Theoretical Economics","volume":"74 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141933570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
These lecture notes are derived from a graduate-level course in dynamic optimization, offering an introduction to techniques and models extensively used in management science, economics, operations research, engineering, and computer science. The course emphasizes the theoretical underpinnings of discrete-time dynamic programming models and advanced algorithmic strategies for solving these models. Unlike typical treatments, it provides a proof for the principle of optimality for upper semi-continuous dynamic programming, a middle ground between the simpler countable state space case cite{bertsekas2012dynamic}, and the involved universally measurable case cite{bertsekas1996stochastic}. This approach is sufficiently rigorous to include important examples such as dynamic pricing, consumption-savings, and inventory management models. The course also delves into the properties of value and policy functions, leveraging classical results cite{topkis1998supermodularity} and recent developments. Additionally, it offers an introduction to reinforcement learning, including a formal proof of the convergence of Q-learning algorithms. Furthermore, the notes delve into policy gradient methods for the average reward case, presenting a convergence result for the tabular case in this context. This result is simple and similar to the discounted case but appears to be new.
{"title":"A Course in Dynamic Optimization","authors":"Bar Light","doi":"arxiv-2408.03034","DOIUrl":"https://doi.org/arxiv-2408.03034","url":null,"abstract":"These lecture notes are derived from a graduate-level course in dynamic\u0000optimization, offering an introduction to techniques and models extensively\u0000used in management science, economics, operations research, engineering, and\u0000computer science. The course emphasizes the theoretical underpinnings of\u0000discrete-time dynamic programming models and advanced algorithmic strategies\u0000for solving these models. Unlike typical treatments, it provides a proof for\u0000the principle of optimality for upper semi-continuous dynamic programming, a\u0000middle ground between the simpler countable state space case\u0000cite{bertsekas2012dynamic}, and the involved universally measurable case\u0000cite{bertsekas1996stochastic}. This approach is sufficiently rigorous to\u0000include important examples such as dynamic pricing, consumption-savings, and\u0000inventory management models. The course also delves into the properties of\u0000value and policy functions, leveraging classical results\u0000cite{topkis1998supermodularity} and recent developments. Additionally, it\u0000offers an introduction to reinforcement learning, including a formal proof of\u0000the convergence of Q-learning algorithms. Furthermore, the notes delve into\u0000policy gradient methods for the average reward case, presenting a convergence\u0000result for the tabular case in this context. This result is simple and similar\u0000to the discounted case but appears to be new.","PeriodicalId":501188,"journal":{"name":"arXiv - ECON - Theoretical Economics","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141933574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We show that Execution Tickets and Execution Auctions dramatically increase centralization in the market for block proposals, even without multi-block MEV concerns. Previous analyses have insufficiently or incorrectly modeled the interaction between ahead-of-time auctions and just-in-time (JIT) auctions. We study a model where bidders compete in an execution auction ahead of time, and then the winner holds a JIT auction to resell the proposal rights when the slot arrives. During the execution auction, bidders only know the distribution of their valuations. Bidders then draw values from their distributions and compete in the JIT auction. We show that a bidder who wins the execution auction is substantially advantaged in the JIT auction since they can set a reserve price higher than their own realized value for the slot to increase their revenue. As a result, there is a strong centralizing force in the execution auction, which allows the ex-ante strongest bidder to win the execution auction every time, and similarly gives them the strongest incentive to buy up all the tickets. Similar results trivially apply if the resale market is imperfect, since that only reinforces the advantages of the ex-ante strong buyer. To reiterate, these results do not require the bidders to employ multi-block MEV strategies, although if they did, it would likely amplify the centralizing effects.
{"title":"Centralization in Attester-Proposer Separation","authors":"Mallesh Pai, Max Resnick","doi":"arxiv-2408.03116","DOIUrl":"https://doi.org/arxiv-2408.03116","url":null,"abstract":"We show that Execution Tickets and Execution Auctions dramatically increase\u0000centralization in the market for block proposals, even without multi-block MEV\u0000concerns. Previous analyses have insufficiently or incorrectly modeled the\u0000interaction between ahead-of-time auctions and just-in-time (JIT) auctions. We\u0000study a model where bidders compete in an execution auction ahead of time, and\u0000then the winner holds a JIT auction to resell the proposal rights when the slot\u0000arrives. During the execution auction, bidders only know the distribution of\u0000their valuations. Bidders then draw values from their distributions and compete\u0000in the JIT auction. We show that a bidder who wins the execution auction is\u0000substantially advantaged in the JIT auction since they can set a reserve price\u0000higher than their own realized value for the slot to increase their revenue. As\u0000a result, there is a strong centralizing force in the execution auction, which\u0000allows the ex-ante strongest bidder to win the execution auction every time,\u0000and similarly gives them the strongest incentive to buy up all the tickets.\u0000Similar results trivially apply if the resale market is imperfect, since that\u0000only reinforces the advantages of the ex-ante strong buyer. To reiterate, these\u0000results do not require the bidders to employ multi-block MEV strategies,\u0000although if they did, it would likely amplify the centralizing effects.","PeriodicalId":501188,"journal":{"name":"arXiv - ECON - Theoretical Economics","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141968816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：