The Economic Limits of Bitcoin and Anonymous, Decentralized Trust on the Blockchain
Quarterly Journal of Economics, Reject-and-Resubmit. [PDF][av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
Satoshi Nakamoto invented a new form of trust. This paper presents a three equation argument that Nakamoto’s new form of trust, while undeniably ingenious, is extremely expensive: the recurring, ‘flow’ payments to the anonymous, decentralized compute power that maintains the trust must be large relative to the one-off, ‘stock’ benefits of attacking the trust. This result also implies that the cost of securing the trust grows linearly with the potential value of attack — e.g., securing against a $1 billion attack is 1000 times more expensive than securing against a $1 million attack. A way out of this flow-stock argument is if both (i) the compute power used to maintain the trust is non-repurposable, and (ii) a successful attack would cause the economic value of the trust to collapse. However, vulnerability to economic collapse is itself a serious problem, and the model points to specific collapse scenarios. The analysis thus suggests a ‘pick your poison’ economic critique of Bitcoin and its novel form of trust: it is either extremely expensive relative to its economic usefulness or vulnerable to sabotage and collapse.
[av_heading heading='Earlier Version' tag='h3' icon_padding='10' ][/av_heading]June 2018 version, NBER Working Paper No. 24717
National Bureau of Economic Research Working Paper Series, No. 24717, 2018.[PDF] [All Related Material]
[av_heading heading='Press Coverage' tag='h3' icon_padding='10' ][/av_heading]
How Costly is Trust in the Blockchain?
Marginal Revolution, Tyler Cowen, Jul 26, 2022 [PDF]Bitcoin Holders Have No Choice but to Trust in Chinese Crypto Miners
MarketWatch, Mark Hulbert, May 28, 2021 [PDF]Think GameStop Is Wild? Meet Dogecoin, the Meme-Inspired Digital Currency That Began As a Joke and Is Now Worth Billions
Chicago Tribune, John Keilman, Feb 04, 2021 [PDF]Bitcoin Is Less Secure Than Most People Think
Marginal Revolution, Alex Tabarrok, Jan 07, 2019 [PDF]Why Bitcoin Will Never Replace Gold
Barron's, Mark Hulbert, Jul 31, 2018 [PDF]Rental Attacks Mean That Blockchains Must Evolve or Die
Techcrunch, Abe Othman, Jul 22, 2018 [PDF]Bitcoin Looks More Like Gold Than a Currency
Bloomberg, Noah Smith, Jul 11, 2018 [PDF]Bitcoin’s Inherent Economics Could Keep It from Ever Being Very Important
MIT Technology Review, Mike Orcutt, Jul 06, 2018 [PDF][av_heading heading='Public Talk' tag='h3' icon_padding='10' ][/av_heading]
The Economic Limits of Cryptocurrencies and Anonymous, Decentralized Trust on the Blockchain (April 2023)
Booth All-Faculty Seminar, April 18, 2023.Harvard Harris Lecture: The Economics of Cryptocurrencies (November 2022)
Harris Lecture at Harvard University, November 9, 2022.The Economics of Cryptocurrencies (April 2022)
Oxford University Economics Department, April 6, 2022. [av_heading heading='Slides' tag='h3' icon_padding='10' ][/av_heading]Slides, 2022 Northwestern University Conference
[PDF]Presentation on Bitcoin Research at the May 2019 Atlanta Fed Financial Markets Conference
Atlanta Fed Financial Markets Conference, May 19, 2019. [PDF] [av_heading heading='Video' tag='h3' icon_padding='10' ][/av_heading]Virtual MD Seminar Presentation, March 2021
Virtual MD Seminar Series, March 15, 2021.AFA panel “Blockchain: Myth and Reality”
The American Finance Association, January 4, 2019.
Flow Trading
Coauthors: Peter Cramton, Albert S Kyle, Jeongmin Lee, and David MalecAmerican Economic Review, Revise-and-Resubmit. [PDF]
[av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
We propose a new market design for trading financial assets. The design allows traders to directly trade any user-defined linear combination of assets. Orders for such portfolios are expressed as downward-sloping piecewise-linear demand curves with quantities as flows (shares/second). Batch auctions clear all asset markets jointly in discrete time. Market-clearing prices and quantities are shown to exist, despite the wide variety of preferences that can be expressed. Calculating prices and quantities is shown to be computationally feasible. Microfoundations are provided to show that traders can implement optimal strategies using portfolio orders. The proposal has several advantages over the status quo.
[av_heading heading='Slides' tag='h3' icon_padding='10' ][/av_heading]Flow Trading
[PDF]
A Theory of Stock Exchange Competition and Innovation: Will the Market Fix the Market?
Coauthors: Robin Lee and John ShimJournal of Political Economy, forthcoming. [PDF]
[av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
This paper builds a new model of financial exchange competition, tailored to the institutional details of the modern US stock market. In equilibrium, exchange trading fees are competitive but exchanges are able to earn economic profits from the sale of speed technology. We document stylized facts consistent with these results. We then use the model to analyze incentives for market design innovation. The novel tension between private and social innovation incentives is incumbents’ rents from speed technology in the status quo. This creates a disincentive to adopt new market designs that eliminate latency arbitrage and the high-frequency trading arms race.
[av_heading heading='Appendices' tag='h3' icon_padding='10' ][/av_heading]Appendix, Theory of Stock Exchange
[PDF] [av_heading heading='Policy Discussion' tag='h3' icon_padding='10' ][/av_heading]SEC Feb. 2020 Proposal re: Market Data Infrastructure
Market Data Infrastructure, Proposed Rule, Securities and Exchange Commission, 2020. [PDF]SEC Commissioner Jackson
Statement on Reforming Stock Exchange Governance, Public Statement, Commissioner Robert J. Jackson Jr., 2020.. [PDF] [av_heading heading='Press Coverage' tag='h3' icon_padding='10' ][/av_heading]The Trades Are Free, the Data Will Cost You
Matt Levine, Matt Levine, May 21, 2019 [PDF]SEC Commissioner Calls for Regulators to Bolster Market Oversight
Wall Street Journal, Gretchen Morgenson, Sep 18, 2018 [PDF][av_heading heading='Public Talk' tag='h3' icon_padding='10' ][/av_heading]
Transcript, Will the Market Fix the Market?
AEA / AFA Joint Luncheon Talk, January 6, 2017, Chicago. [av_heading heading='Slides' tag='h3' icon_padding='10' ][/av_heading]Slides, Will the Market Fix the Market?
[PDF]AEA Presentation (Jan 2022)
[PDF] [av_heading heading='Video' tag='h3' icon_padding='10' ][/av_heading]AEA/AFA Joint Luncheon Address, Will the Market Fix the Market?
AEA / AFA Joint Luncheon Talk, Chicago, January 6, 2017.
An Economic Framework for Vaccine Prioritization
Coauthors: Mohammad Akbarpour, Piotr Dworczak, and Scott Duke KominersThe Quarterly Journal of Economics, forthcoming. [PDF]
[av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
We propose an economic framework for determining the optimal allocation of a scarce supply of vaccines that become gradually available during a public health crisis, such as the Covid-19 pandemic. Agents differ in observable and unobservable characteristics, and the designer maximizes a social welfare function over all feasible mechanisms—accounting for agents’ characteristics, as well as their endogenous behavior in the face of the pandemic. The framework emphasizes the role of externalities and incorporates equity as well as efficiency concerns. Our results provide an economic justification for providing vaccines immediately and for free to some groups of agents, while at the same time showing that a carefully constructed pricing mechanism can improve outcomes by screening for individuals with the highest private and social benefits of receiving the vaccine. The solution casts light on the classic question of
whether prices or priorities should be used to allocate scarce public resources under externalities and equity concerns.
Slides, An Economic Framework for Vaccine Prioritization
[PDF]
Primary-Market Auctions for Event Tickets: Eliminating the Rents of “Bob the Broker”?
Coauthors: Aditya BhaveAmerican Economic Journal: Microeconomics, (2023): 15, No. 1, 142-170. [PDF]
[av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
Economists have long been puzzled by event-ticket underpricing: underpricing both reduces revenue and encourages socially wasteful rent-seeking by ticket brokers. This paper studies the introduction of auctions into this market by Ticketmaster. We first show theoretically that Ticketmaster’s auction design, a novel variant of position auctions, has attractive efficiency, revenue and no-arbitrage properties. Then, by combining primary-market auction data from Ticketmaster with secondary-market resale value data from eBay, we show that the auctions “worked” in practice: on average, they eliminated the arbitrage profits associated with underpriced tickets. We conclude by discussing why, nevertheless, the auctions have failed to take off.
[av_heading heading='Appendices' tag='h3' icon_padding='10' ][/av_heading]Appendix, Primary Market Auctions
[PDF] [av_heading heading='Code' tag='h3' icon_padding='10' ][/av_heading]Replication Package
[av_heading heading='Podcast' tag='h3' icon_padding='10' ][/av_heading]Freakonomics Podcast, Why Is the Live-Event Ticket Market So Screwed Up?
Stephen J. DubnerFreakonomics Podcast, December 2017. [PDF] [av_heading heading='Slides' tag='h3' icon_padding='10' ][/av_heading]
Primary-Market Auctions for Event Tickets
[PDF]Slides as PDF
FTC Workshop, That's the Ticket on Consumer Protection Issues in the Ticket Market, June 11, 2019. [PDF] [av_heading heading='Video' tag='h3' icon_padding='10' ][/av_heading]FTC Keynote Talk, How to Fix the Market for Event Tickets
FTC "That's the Ticket" Workshop on Consumer Protection Issues into the Event Tickets Market, June 11 2019.
Can Market Participants Report their Preferences Accurately (Enough)?
Coauthors: Judd B KesslerManagement Science, (2022): 68, no. 2, 1107–1130. [PDF]
[av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
In mechanism design theory it is common to assume that agents can perfectly report their preferences, even in complex settings where this assumption strains reality. We experimentally test whether real market participants can report their real preferences for course schedules “accurately enough” for a novel course allocation mechanism, approximate competitive equilibrium from equal incomes (A-CEEI), to realize its theoretical benefits. To use market participants’ real preferences (i.e., rather than artificial “induced preferences” as is typical in market design experiments), we developed a new experimental method. Our method, the “elicited preferences” approach, generates preference data from subjects through a series of binary choices. These binary choices revealed that subjects preferred their schedules constructed under A-CEEI to their schedules constructed under the incumbent mechanism, a bidding points auction, and that A-CEEI reduced envy, suggesting subjects were able to report their preferences accurately enough to realize the efficiency and fairness benefits of A-CEEI. However, preference reporting mistakes did meaningfully harm mechanism performance. One identifiable pattern of mistakes was that subjects had relatively more difficulty reporting cardinal as opposed to ordinal preference information. The experiment helped to persuade the Wharton School to adopt the new mechanism and helped guide aspects of its practical implementation, especially around preference reporting.
[av_heading heading='Slides' tag='h3' icon_padding='10' ][/av_heading]Seminar Slides, UPenn (Aug 2017)
[PDF]
Quantifying the High-Frequency Trading “Arms Race”
Coauthors: Matteo Aquilina and Peter O'NeillThe Quarterly Journal of Economics, (2022): 137, no. 1, 493-564. [PDF]
[av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
We use stock exchange message data to quantify the negative aspect of high-frequency trading, known as “latency arbitrage.” The key difference between message data and widely-familiar limit order book data is that message data contain attempts to trade or cancel that fail. This allows the researcher to observe both winners and losers in a race, whereas in limit order book data you cannot see the losers, so you cannot directly see the races. We find that latency-arbitrage races are very frequent (about one per minute per symbol for FTSE 100 stocks), extremely fast (the modal race lasts 5-10 millionths of a second), and account for a large portion of overall trading volume (about 20%). Race participation is concentrated, with the top 6 firms accounting for over 80% of all race wins and losses. Most races (about 90%) are won by an aggressive order as opposed to a cancel attempt; market participants outside the top 6 firms disproportionately provide the liquidity that gets taken in races (about 60%). Our main estimates suggest that eliminating latency arbitrage would reduce the market’s cost of liquidity by 17% and that the total sums at stake are on the order of $5 billion annually in global equity markets.
[av_heading heading='Awards' tag='h3' icon_padding='10' ][/av_heading]Winner — WFA 2020 Two Sigma Award for Best Paper on Investment Management
[av_heading heading='Appendices' tag='h3' icon_padding='10' ][/av_heading]Data and Code Appendix
Matteo Aquilina and Peter O'NeillThe Quarterly Journal of Economics, [PDF] [av_heading heading='Code' tag='h3' icon_padding='10' ][/av_heading]
Exchange Message Data Codebook
Code and Detailed Guidebook for researchers, academics and regulators to conduct their own studies using exchange message data. [av_heading heading='Earlier Version' tag='h3' icon_padding='10' ][/av_heading]FCA Occasional Paper landing page with brief summary and links
Coauthors: Matteo Aquilina and Peter O'NeillFinancial Conduct Authority, Occasional Paper No. 50: Quantifying the High-Frequency Trading 'Arms Race'.
[PDF] [All Related Material]
FCA Insight Brief Description of “Quantifying the High-Frequency Trading ‘Arms Race'”
Coauthors: Matteo Aquilina and Peter O'NeillInsight, Big Bucks from Small Change, January 2020.
[PDF] [All Related Material]
UK Financial Conduct Authority Occasional Paper 50
Coauthors: Matteo Aquilina and Peter O'NeillFinancial Conduct Authority, "Quantifying the High-Frequency Trading Arms Race".
[PDF] [All Related Material]
[av_heading heading='Press Coverage' tag='h3' icon_padding='10' ][/av_heading]
Money Stuff: Latency Arbitrage
Bloomberg, Matt Levine, Jan 28, 2020 [PDF]FCA Researchers Outline $5bn ‘Tax’ Imposed by High-Speed Trading
Financial Times, Philip Stafford, Jan 27, 2020 [PDF]Ultrafast Trading Costs Stock Investory Nearly $5 Billion a Year, Study Says
Wall Street Journal, Alexander Osipovich, Jan 27, 2020 [PDF][av_heading heading='Slides' tag='h3' icon_padding='10' ][/av_heading]
Seminar slides
[PDF] [av_heading heading='Video' tag='h3' icon_padding='10' ][/av_heading]Quantifying the High-Frequency Trading ‘Arms Race’: A new methodology and estimates
Matteo Aquilina and Peter O'NeillThe Microstructure Exchange, June 16, 2020.
Why Are Bots Buying Sneakers?
Coauthors: Seth StevensonSlate, What Next: TBD Podcast, October 2021. [PDF]
You Could Be Competing With Bots to Buy Gifts This Christmas
Coauthors: Joshua HuntBloomberg Businessweek, . [PDF]
Market Design
Coauthors: Nikhil AgarwalHandbook of Industrial Organization, 5, Issue 1, 2021, Pages 1-79. [PDF]
[av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
This Handbook chapter seeks to introduce students and researchers of industrial organization (IO) to the field of market design. We emphasize two important points of connection between the IO and market design fields: a focus on market failures— both understanding sources of market failure and analyzing how to fix them—and an appreciation of institutional detail.
Section II reviews theory, focusing on introducing the theory of matching and assignment mechanisms to a broad audience. It introduces a novel “taxonomy” of market design problems, covers the key mechanisms and their properties, and emphasizes several points of connection to traditional economic theory involving prices and competitive equilibrium.
Section III reviews structural empirical methods that build on this theory. We describe how to estimate a workhorse random utility model under various data environments, ranging from data on reported preference data such as rank-order lists to data only on observed matches. These methods enable a quantification of trade-offs in designing markets and the effects of new market designs.
Section IV discusses a wide variety of applications. We organize this discussion into three broad aims of market design research: (i) diagnosing market failures; (ii) evaluating and comparing various market designs; (iii) proposing new, improved designs. A point of emphasis is that theoretical and empirical analysis have been highly complementary in this research.
Measuring the 15-Microsecond Dash with Professor Eric “Batch” Budish
Coauthors: Ronan Ryan and John RamsayIEX Boxes and Lines Podcast, July 2021.
Preparing for a Pandemic: Accelerating Vaccine Availability
Coauthors: Amrita Ahuja, Susan Athey, Arthur Baker, Juan Camilo Castillo, Rachel Glennerster, Scott Duke Kominers, Michael Kremer, Jean Lee, Canice Prendergast, Christopher M Snyder, Alex Tabarrok, Brandon Joel Tan, and Witold WięcekAEA Papers and Proceedings, (2021): 111, 331-335. [PDF]
[av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
Vaccinating the world’s population quickly in a pandemic has enormous health and economic benefits. We analyze the problem faced by governments in determining the scale and structure of procurement for vaccines. We analyze alternative approaches to procurement, arguing that buyers should directly fund manufacturing capacity and shoulder most of the risk of failure while maintaining some direct incentives for speed. We analyzed the optimal portfolio of vaccine investments for countries with different characteristics as well as the implications for international cooperation. Our analysis, considered in light of the experience of 2020, suggests lessons for future pandemics.
[av_heading heading='Slides' tag='h3' icon_padding='10' ][/av_heading]Preparing for a Pandemic: Accelerating Vaccine Availability
[PDF]
Bigger Is Better When It Comes to Vaccine Production
Coauthors: Christopher SnyderWall Street Journal, March 2021. [PDF]
[av_heading heading='Video' tag='h3' icon_padding='10' ][/av_heading]
Market Design for Covid-19 vaccine supply
Booth Alumni Event, Hosted by the Chicago Booth Alumni Club of Singapore, August 18, 2021.
Market Design to Accelerate Covid-19 Vaccine Supply
Coauthors: Juan Camilo Castillo, Amrita Ahuja, Susan Athey, Arthur Baker, Tasneem Chipty, Rachel Glennerster, Scott Duke Kominers, Michael Kremer, Greg Larson, Jean Lee, Canice Prendergast, Christopher M Snyder, Alex Tabarrok, Brandon Joel Tan, and Witold WięcekScience, (2021): 68, no.2, 1107-1109. [PDF]
[av_heading heading='Policy Writing' tag='h3' icon_padding='10' ][/av_heading]
Bigger Is Better When It Comes to Vaccine Production
Coauthors: Christopher SnyderWall Street Journal, March 2021.
[PDF] [All Related Material]
[av_heading heading='Press Coverage' tag='h3' icon_padding='10' ][/av_heading]
We Can Sustainably End the Pandemic with 7.2 Billion Vaccine Courses a Year: Chicago Booth’s Eric Budish
The Economic Times, Srijana Mitra Das, ET Bureau, Jun 19, 2021 [PDF]How Can More Covid-19 Vaccines be Made Available?
The Economist, May 15, 2021 [PDF]The Big Pharma CEO Who’s Helping to Put an End to COVID-19
Newsweek, Lee Habeeb, Apr 26, 2021 [PDF][av_heading heading='Panel Discussion' tag='h3' icon_padding='10' ][/av_heading]
Management Conference ’21: Perspectives on COVID-19
Chicago Booth Management Conference Panel, June 2021. [av_heading heading='Related Works' tag='h3' icon_padding='10' ][/av_heading]Distributing a Billion Vaccines: COVAX Successes, Challenges, and Opportunities
Hannah Kettler, Scott Duke Kominers, Erik Osland, Canice Prendergast, and Andrew A TorkelsonOxford Review of Economic Policy, (2022): 38, no. 4, 941-974. [PDF]
Abstract
By January 2022, the COVAX international vaccine collaboration had allocated over a billion vaccines to over 140 countries. We describe and review the allocation process chosen, which reflected both an objective of equitably distributing vaccines across the world and the need to fund that mission. We show how vaccine supply limitations and constraints on some countries’ absorptive capacity have affected overall allocative outcomes. We also discuss market design approaches that were considered but not implemented, including the use of an exchange mechanism to better match countries’ vaccine allocations to their preferences, as well as a vaccine brokerage under which countries could sell excess vaccines to countries with ongoing need. Our analysis addresses some criticisms of COVAX, and offers suggestions for agencies organizing global vaccine cooperation for future pandemics.
Market Design for Covid-19 vaccine supply
Booth Alumni Event, Hosted by the Chicago Booth Alumni Club of Singapore, August 18, 2021.
Maximize Utility Subject to R ≤ 1: A Simple Price-Theory Approach to Covid-19 Lockdown and Reopening Policy
NBER Working Paper No. w28093. Latest Draft: November 2020. [PDF][av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
This note suggests that we view R < 1 as an economic constraint, allowing social welfare in the traditional sense (economic activity, societal well-being) to be the policy objective. This formulation highlights two key questions at the intersection of health and economics research in response to the Covid-19 crisis. First, what activities maximize social welfare subject to the constraint that disease-transmission is contained, i.e., R < 1. Second, what are ways to “expand the frontier” of how much social welfare we can achieve while keeping disease-transmission contained. For example, could widespread use of masks and gloves, society-wide campaigns to “wash your hands,” “stay home if sick,” and “don’t touch your face,” and aggressive testing, together allow us to meaningfully increase the level of economic activity and societal well-being that is possible while keeping R < 1 ?
[av_heading heading='Earlier Version' tag='h3' icon_padding='10' ][/av_heading]April 2020 draft: “R<1 as an Economic Constraint: Can we 'Expand the Frontier' in the Fight Against Covid-19?"
University of Chicago, Becker Friedman Institute for Economics Working Paper.[PDF] [All Related Material]
[av_heading heading='Press Coverage' tag='h3' icon_padding='10' ][/av_heading]
William Watson: Carrots, Sticks and Sledgehammers
Financial Post, William Watson, Dec 01, 2020 [PDF][av_heading heading='Slides' tag='h3' icon_padding='10' ][/av_heading]
Updated Slides for Talks in January 2021
Maximize Utility subject to R≤1, January 2021 Presentations. [PDF]Slides, May 2020
Stigler Center Conference on Covid-19, May 7, 2020. [PDF]Slides, April 2020
IGM Conference on the Covid-19 Crisis, April 7, 2020. [PDF] [av_heading heading='Video' tag='h3' icon_padding='10' ][/av_heading]R<1 as an Economic Constraint (May 2020)
Stigler Center Conference on Covid-19, May 7, 2020.R<1 as an Economic Constraint (April 2020)
IGM Conference on the Covid-19 Crisis, April 9, 2020.
An Improved Bound for the Shapley-Folkman Theorem
Coauthors: Philip J RenyJournal of Mathematical Economics, (2020): 89, 48-52. [PDF]
[av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
We provide an up to 30% improvement in the Shapley-Folkman theorem error-bound, and briefly discuss its consequences for the course allocation problem.
Three Pillars of the Economic Policy Response to the Covid-19 Crisis
Coauthors: Anil Kashyap, Ralph Koijen, and Brent NeimanWorking Paper, March 2020. [PDF]
[av_heading heading='Related Works' tag='h3' icon_padding='10' ][/av_heading]
IGM Covid-19 Research Page
Chicago Booth Initiative on Global Markets..
FCA Insight Brief Description of “Quantifying the High-Frequency Trading ‘Arms Race'”
Coauthors: Matteo Aquilina and Peter O'NeillInsight, Big Bucks from Small Change, January 2020. [PDF]
Strategy-proofness in the Large
Coauthors: Eduardo M AzevedoReview of Economic Studies, (2019): 86, no. 1, 81-116. [PDF]
[av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
We propose a criterion of approximate incentive compatibility, strategy-proofness in the large (SP-L), and argue that it is a useful second-best to exact strategy-proofness (SP) for market design. Conceptually, SP-L requires that an agent who regards a mechanism’s “prices” as exogenous to her report—be they traditional prices as in an auction mechanism, or price-like statistics in an assignment or matching mechanism—has a dominant strategy to report truthfully. Mathematically, SP-L weakens SP in two ways: (1) truth-telling is required to be approximately optimal (within epsilon in a large enough market) rather than exactly optimal, and (2) incentive compatibility is evaluated ex interim, with respect to all full-support i.i.d. probability distributions of play, rather than ex post with respect to all possible realizations of play. This places SP-L in between the traditional notion of approximate SP, which evaluates incentives to manipulate ex post and as a result is too strong to obtain our main results in support of SP-L, and the traditional notion of approximate Bayes-Nash incentive compatibility, which, like SP-L, evaluates incentives to manipulate ex interim, but which imposes common knowledge and strategic sophistication assumptions that are often viewed as unrealistic.
[av_heading heading='Appendices' tag='h3' icon_padding='10' ][/av_heading]Appendix, Strategy Proofness in the Large
[PDF] [av_heading heading='Earlier Version' tag='h3' icon_padding='10' ][/av_heading]2016 Working Paper Version
with Eduardo M. Azevedo..[PDF] [All Related Material]
[av_heading heading='Slides' tag='h3' icon_padding='10' ][/av_heading]
ACM EC Panel Discussion Slides (June 2018)
[PDF]Seminar Slides (Nov 2012)
University of Pennsylvania Theory Seminar, November 2012. [PDF]
Course Match: A Large-Scale Implementation of Approximate Competitive Equilibrium from Equal Incomes for Combinatorial Allocation
Coauthors: Gerard Cachon, Judd B Kessler, Abraham OthmanOperations Research, (2017): 65, no. 2, 314-336. [PDF]
[av_heading heading='Press Coverage' tag='h3' icon_padding='10' ][/av_heading]
Technology Brings Choice to MBA Students
Financial Times, Della Bradshaw, Nov 23, 2014 [PDF]Gaming Wharton’s Course Scheduling System Just Got Tougher
Bloomberg Businessweek, Louis Lavelle, Sep 19, 2013 [PDF][av_heading heading='Related Works' tag='h3' icon_padding='10' ][/av_heading]
Cognomos
Wharton “Course Match” website
The Wharton School, University of Pennsylvania.
Transcript, Will the Market Fix the Market?
AEA / AFA Joint Luncheon Talk, January 6, 2017, Chicago.[av_heading heading='Video' tag='h3' icon_padding='10' ][/av_heading]
AEA/AFA Joint Luncheon Address, Will the Market Fix the Market?
AEA / AFA Joint Luncheon Talk, Chicago, January 6, 2017.
Patents and Research Investments: Assessing the Empirical Evidence
Coauthors: Benjamin J Roin and Heidi WilliamsAmerican Economic Review: Papers & Proceedings, (2016): 106, no. 5, 183-187. [PDF]
[av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
A well-developed theoretical literature–dating back at least to Nordhaus (1969)–has analyzed optimal patent policy design. We re-present the core trade-off of the Nordhaus model and highlight an empirical question which emerges from the Nordhaus framework as a key input into optimal patent policy design: namely, what is the elasticity of R&D investment with respect to the patent term? We then review the–surprisingly small–body of empirical evidence that has been developed on this question over the nearly half century since the publication of Nordhaus’s book.
[av_heading heading='Appendices' tag='h3' icon_padding='10' ][/av_heading]Appendix, Patents and Research Investments
[PDF]
The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response
Coauthors: Peter Cramton and John ShimThe Quarterly Journal of Economics, (2015): 130, no. 4, 1547-1621. [PDF]
[av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
The high-frequency trading arms race is a symptom of flawed market design. Instead of the continuous limit order book market design that is currently predominant, we argue that financial exchanges should use frequent batch auctions: uniform price double auctions conducted, for example, every tenth of a second. That is, time should be treated as discrete instead of continuous, and orders should be processed in a batch auction instead of serially. Our argument has three parts. First, we use millisecond-level direct-feed data from exchanges to document a series of stylized facts about how the continuous market works at high-frequency time horizons: (i) correlations completely break down; which (ii) leads to obvious mechanical arbitrage opportunities; and (iii) competition has not affected the size or frequency of the arbitrage opportunities, it has only raised the bar for how fast one has to be to capture them. Second, we introduce a simple theory model which is motivated by and helps explain the empirical facts. The key insight is that obvious mechanical arbitrage opportunities, like those observed in the data, are built into the market design—continuous-time serial-processing implies that even symmetrically observed public information creates arbitrage rents. These rents harm liquidity provision and induce a never-ending socially wasteful arms race for speed. Last, we show that frequent batch auctions directly address the flaws of the continuous limit order book. Discrete time reduces the value of tiny speed advantages, and the auction transforms competition on speed into competition on price. Consequently, frequent batch auctions eliminate the mechanical arbitrage rents, enhance liquidity for investors, and stop the high-frequency trading arms race.
[av_heading heading='Awards' tag='h3' icon_padding='10' ][/av_heading]Winner- 2014 AQR Insight Award
Winner- 2015 Utah WFC Best Paper Award
Appendix, High-Frequency Trading Arms Race
[PDF] [av_heading heading='Policy Discussion' tag='h3' icon_padding='10' ][/av_heading]SEC Chair White Speech
Enhancing Our Equity Market Structure, Speech, SEC Chair Mary Jo White, June 5, 2014. [PDF]New York Attorney General Speech
Remarks on High-Frequency Trading & Insider Trading 2.0, New York Law School Panel on “Insider Trading 2.0 — A New Initiative to Crack Down on Predatory Practices,” March 18, 2014. [PDF] [av_heading heading='Policy Writing' tag='h3' icon_padding='10' ][/av_heading]Response to ESMA’s Call for Evidence re Periodic Auctions
Response to ESMA’s Call for Evidence: “Periodic Auctions for Equity Instruments” (ESMA70-156-785), January 2019.[PDF] [All Related Material]
Response to RFI on the Evolution of the U.S. Treasury Market Structure
Response to RFI on the Evolution of the U.S. Treasury Market Structure, Re: Notice Seeking Public Comment on the Evolution of the Treasury Market Structure (Docket No. TREAS-DO-2015-0013), April 2016.[PDF] [All Related Material]
Comment Letter on Proposed Commission Interpretation of One Millisecond as De Minimis
Re: Proposed Commission Interpretation Regarding Automated Quotations Under Regulation NMS (Release No. 34-77407; File No. S7-03-16), April 2016.[PDF] [All Related Material]
IEX Comment Letter
Re: Investors’ Exchange LLC Form 1 Application (Release No. 34-75925; File No. 10-222), February 2016.[PDF] [All Related Material]
CFTC Comment Letter
Re: CFTC Concept Release — Risk Controls and System Safeguards for Automated Trading Environments, RIN 3038-AD52, February 2014.[PDF] [All Related Material]
[av_heading heading='Press Coverage' tag='h3' icon_padding='10' ][/av_heading]
Slowing Down the Stock Market
Bloomberg Editorial, Editorial Board, Jun 18, 2014 [PDF]Everything You Need to Know About High-Frequency Trading
The Atlantic, Matthew O’Brien, Apr 11, 2014 [PDF]Professor Proposes Slowing Down Automated Trading
Chicago Tribune, Ameet Sachdev, Mar 30, 2014 [PDF]Declawing Speed Traders Is Goal of Stock Market Revamp Proposal
Bloomberg, Sam Mamudi, Feb 19, 2014 [PDF]The Need for Less Speed
Financial Times, Tim Harford, Jul 06, 2013 [PDF][av_heading heading='Panel Discussion' tag='h3' icon_padding='10' ][/av_heading]
CFTC’s Technology Advisory Committee Meeting
Commody Futures Trading Commission, February 2014.Is high frequency trading good for financial markets?
Chicago Booth Review, October 2013. [av_heading heading='Related Works' tag='h3' icon_padding='10' ][/av_heading]Implementation Details for Frequent Batch Auctions: Slowing Down Markets to the Blink of an Eye
Peter Cramton and John ShimAmerican Economic Review: Papers & Proceedings, (2014): 104, no. 5, 418-424. [PDF]
Abstract
Our recent research (Budish, Cramton, and Shim 2013) proposes frequent batch auctions—uniform-price sealed-bid double auctions conducted at frequent but discrete time intervals—as a market design alternative to continuous-time trading in financial markets. This short paper discusses the implementation details of frequent batch auctions. We outline the process flow for frequent batch auctions, discuss a modification to the market design that accommodates market fragmentation and Reg NMS, and discuss the engineering and economic considerations relevant for determining the batch interval. Open questions are discussed throughout.
Policy Audience Slides (FCA, Feb 2016)
[PDF]Seminar Slides (Sept 2015)
Seminar Slides, with Peter Cramton and John Shim. September 2015. [PDF]
Do Firms Underinvest in Long-Term Research? Evidence from Cancer Clinical Trials
Coauthors: Benjamin J Roin and Heidi WilliamsAmerican Economic Review, (2015): 105, no. 7, 2044-2085. [PDF]
[av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
We investigate whether private research investments are distorted away from long-term projects. Our theoretical model highlights two potential sources of this distortion: short-termism and the fixed patent term. Our empirical context is cancer research, where clinical trials — and hence, project durations — are shorter for late-stage cancer treatments relative to early-stage treatments or cancer prevention. Using newly constructed data, we document several sources of evidence that together show private research investments are distorted away from long-term projects. The value of life-years at stake appears large. We analyze three potential policy responses: surrogate (non-mortality) clinical-trial endpoints, targeted R&D subsidies, and patent design.
[av_heading heading='Awards' tag='h3' icon_padding='10' ][/av_heading]Winner- the Kauffman/iHEA Award for Health Care Entrepreneurship and Innovation Research
Winner- the Arrow Award for “best paper published in health economics” in 2015
Why Preventing Cancer Is Not the Priority in Drug Development
New York Times, Austin Frakt, Dec 28, 2015 [PDF]What Cures Are We Missing Out On?
Bloomberg, John Tozzi, Sep 30, 2015 [PDF]Patents That Kill
The Economist, A.T., Aug 08, 2014 [PDF]Why Aren’t There More Cancer Vaccines?
Slate, Ray Fisman, Aug 26, 2013 [PDF][av_heading heading='Slides' tag='h3' icon_padding='10' ][/av_heading]
Slides, Do Firms Underinvest in Long-Term Research?
Ben Roin and Heidi WilliamsSeminar Slides, April 2015. [PDF]
Implementation Details for Frequent Batch Auctions: Slowing Down Markets to the Blink of an Eye
Coauthors: Peter Cramton and John ShimAmerican Economic Review: Papers & Proceedings, (2014): 104, no. 5, 418-424. [PDF]
[av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
Our recent research (Budish, Cramton, and Shim 2013) proposes frequent batch auctions—uniform-price sealed-bid double auctions conducted at frequent but discrete time intervals—as a market design alternative to continuous-time trading in financial markets. This short paper discusses the implementation details of frequent batch auctions. We outline the process flow for frequent batch auctions, discuss a modification to the market design that accommodates market fragmentation and Reg NMS, and discuss the engineering and economic considerations relevant for determining the batch interval. Open questions are discussed throughout.
Designing Random Allocation Mechanisms: Theory and Applications
Coauthors: Yeon-Koo Che, Fuhito Kojima, and Paul MilgromAmerican Economic Review, (2013): 103, no. 2, 585-623. [PDF]
[av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
Randomization is commonplace in everyday resource allocation. We generalize the theory of randomized assignment to accommodate multi-unit allocations and various real-world constraints, such as group-specific quotas (“controlled choice”) in school choice and house allocation, and scheduling and curriculum constraints in course allocation. We develop new mechanisms that are ex ante efficient and fair in these environments, and that incorporate certain non-additive substitutable preferences. We also develop a “utility guarantee” technique that limits ex post unfairness in random allocations, supplementing the ex ante fairness promoted by randomization. This can be applied to multi-unit assignment problems and certain two-sided matching problems.
[av_heading heading='Appendices' tag='h3' icon_padding='10' ][/av_heading]Appendix, Designing Random Allocation Mechanisms
[PDF] [av_heading heading='Slides' tag='h3' icon_padding='10' ][/av_heading]Designing Random Allocation Mechanisms Seminar Slides (Oct 2010)
[PDF]
Matching “Versus” Mechanism Design
ACM SIGecom Exchanges, (2012): 11, no. 2, 4-15. [PDF][av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
In a typical mechanism design paper the goal is to find a mechanism that maximizes the designer’s objective (e.g., social welfare) subject to technology and incentive constraints. In a typical applied matching paper, by contrast, the goal is to find a mechanism that satisfies various “good properties” (e.g., efficiency and fairness). This essay discusses the relationship and tradeoffs between these two approaches. An introductory example, school choice, represents a simple win for the good properties approach. The main example, course allocation, paints a more complicated picture.
[av_heading heading='Slides' tag='h3' icon_padding='10' ][/av_heading]Slides, Matching in Practice Conference
Matching in Practice Conference, ULB, May 2013. [PDF]
The Multi-Unit Assignment Problem: Theory and Evidence from Course Allocation at Harvard
Coauthors: Estelle CantillonAmerican Economic Review, (2012): 102, no. 5, 2237-2271. [PDF]
[av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
We use theory and field data to study the draft mechanism used to allocate courses at Harvard Business School. We show that the draft is manipulable in theory, manipulated in practice, and that these manipulations cause significant welfare loss. Nevertheless, we find that welfare is higher than under its widely studied strategyproof alternative. We identify a new link between fairness and welfare that explains why the draft performs well despite the costs of strategic behavior, and then design a new draft that reduces these costs. We draw several broader lessons for market design, regarding Pareto efficiency, fairness, and strategyproofness.
[av_heading heading='Slides' tag='h3' icon_padding='10' ][/av_heading]Slides, Jerusalem Summer School (Summer 2014)
[PDF]Slides, Columbia Seminar (Nov 2009)
[PDF]
The Combinatorial Assignment Problem: Approximate Competitive Equilibrium from Equal Incomes
Journal of Political Economy, (2011): 119, no. 6, 1061-1103. [PDF][av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
This paper proposes a new mechanism for combinatorial assignment—for example, assigning schedules of courses to students—based on an approximation to competitive equilibrium from equal incomes (CEEI) in which incomes are unequal but arbitrarily close together. The main technical result is an existence theorem for approximate CEEI. The mechanism is approximately efficient, satisfies two new criteria of outcome fairness, and is strategyproof in large markets. Its performance is explored on real data, and it is compared to alternatives from theory and practice: all other known mechanisms are either unfair ex post or manipulable even in large markets, and most are both manipulable and unfair.
[av_heading heading='Earlier Version' tag='h3' icon_padding='10' ][/av_heading]2010 Working Paper Version
The Combinatorial Assignment Problem: Approximate Competitive Equilibrium from Equal Incomes.[PDF] [All Related Material]
[av_heading heading='Related Works' tag='h3' icon_padding='10' ][/av_heading]
Cognomos
Wikipedia entry: A-CEEI
Wikipedia entry: EF1
Wikipedia entry: Maximin share
Implementation at Wharton
The Wharton School, University of Pennsylvania.. [av_heading heading='Slides' tag='h3' icon_padding='10' ][/av_heading]Slides, Jerusalem Summer School (Summer 2014)
[PDF]Slides, Economic Theory Seminar
May 13, 2010. [PDF]Job Market Talk Slides (Feb 2009)
[PDF]
Finding Approximate Competitive Equilibria: Efficient and Fair Course Allocation
Coauthors: Abraham Othman and Tuomas SandholmProc. of 9th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2010), (2010): 1, 873-880. [PDF]
[av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
In the course allocation problem, a university administrator seeks to efficiently and fairly allocate schedules of over-demanded courses to students with heterogeneous preferences. We investigate how to computationally implement a recently-proposed theoretical solution to this problem (Budish, 2009) which uses approximate competitive equilibria to balance notions of efficiency, fairness, and incentives. Despite the apparent similarity to the well-known combinatorial auction problem we show that no polynomial-size mixed-integer program (MIP) can solve our problem. Instead, we develop a two-level search process: at the master level, the center uses tabu search over the union of two distinct neighborhoods to suggest prices; at the agent level, we use MIPs to solve for student demands in parallel at the current prices. Our method scales near-optimally in the number of processors used and is able to solve realistic-size problems fast enough to be usable in practice.
Buy Prices in Online Auctions: Irrationality on the Internet?
Coauthors: Lisa TakeyamaEconomics Letters, (2001): 73, no. 3, 325-333. [PDF]
[av_heading heading='Abstract' tag='h3' icon_padding='10' ][/av_heading]
Buy prices are puzzling: it makes sense for a seller at auction to set a minimum bidding level (i.e., a reserve price), surely, but a maximum? We explore the use of maximum bidding levels (buy prices) in online auctions and provide a rational explanation for this seemingly irrational auction mechanism. We show that augmenting an English auction with a buy price can improve the seller’s profits by partially insuring (and therefore increasing the expected payment from) some risk-averse bidders. Perhaps more surprising is that the English auction augmented with a buy price can also be superior even to the first-price sealed-bid and Dutch auctions when bidders are risk averse.
