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Thursday, January 4, 2024

Topics in Market Design: Econ 287/365: Winter quarter, Itai Ashlagi

Itai Ashlagi will be teaching Econ 287 this quarter, on topics in market design. It's highly recommended.

He writes that the syllabus below is very tentative, and will depend in part on how many of the enrolled students took Econ 285 (Ostrovsky and Roth) in the Fall (back in 2023:-)

Topics in Market Design 2024, Itai Ashlagi

Market design is a field that links the rules of the of the marketplace to understand frictions, externalities and more generally economic outcomes. The course will provide theoretical foundations on assignment and matching mechanisms as well as mechanism design. There will be emphasis on theories at the intersection of economics, CS and operations as well as applications that arise in labor markets, organ allocation, platforms.

The class will further expose students to timely market design challenges and will we will host a few guest lectures. The class offers an opportunity to begin a research project. Students will reading critique papers, present papers and write a final paper.

Lectures: Monday 10:30am-1:20pm Shriram 052

Course requirements: (i) reading and writing critiques about papers, (ii), presenting papers in class, and (iii) a term paper.

Instructor: Itai Ashlagi. iashlagi@stanford.edu

Some potential papers for presenting:

Equity and Efficiency in Dynamic Matching: Extreme Waitlist Policies, Nikzad and Strack.

Eliminating Waste in Cadaveric Organ Allocation, Shi and Yin

Pick-an-object mechanisms, Bo and Hakimov

Monopoly without a monopolist, Huberman, Leshno and Moallemi

The College Portfolio Problem, Ali and Shorrer

Equal Pay for Similar Work, Passaro, Kojima, and Pakzad-Hurson

Auctions with Withdrawal Rights: A Foundation for Uniform Price, Haberman and Jagadessan.

Optimal matchmaking strategy in two-sided marketplaces, Shi

Practical algorithms and experimentally validated incentives for equilibrium-based fair division (ACEEI),

Budish, Gao, Othman, Rubinstein

Congestion pricing, carpooling, and commuter welfare, Ostrovsky and Schwarz

Artificial intelligence and auction design, Banchio and Skrzypacz

Selling to a no-regret buyer, Braverman et al.

Dynamic matching in overloaded waiting lists, Leshno

The regulation of queue size by levying tolls, Naor

Optimal search for the best alternative, Weitzman

Whether or not to open Pandora’s box, Doval

Descending price optimally coordinates search, Kleinberg, Waggoner, Weyl

Market Failure in Kidney Exchange? Nikhil Agarwal, Itai Ashlagi, Eduardo Azevedo, Clayton Featherstone and Omer Karaduman

Choice Screen Auctions, Michael Ostrovsky

Incentive Compatibility of Large Centralized Matching Markets, Lee

Tentative schedule:

Week 1: Two-sided matching, stability and large markets.

Week 2: One-sided matching, duality, optimization and constraints.

Week 3: Multi-item auctions, auction design, revenue equivalence, optimal auctions, interdependent

valuations.

Week 4: Congestion, dynamic matching.

Week 5: Waitlists, search and learning.

Week 6: Foundations of mechanism design.

Week 7: Robustness in implementation

Weeks 8-10: Projects

We will host several guest lectures. Presentations of papers will take place throughout the course.

Background references

1. List of (mostly applied) papers are given in a separate document.

2. Books

Roth, Alvin E.and Marilda A. Oliveira Sotomayor, Two-sided matching: A study in game-theoretic modeling and analysis. No. 18. Cambridge University Press, 1992.

Vijay Krishna, Auction Theory, 2010.

Tilman Borgers, An Introduction to Mechanism Design by Tilman Borgers.

Milgrom, Paul, Putting Auction Theory to Work, 2004.

3. Papers

(a) Introduction

Roth, Alvin E. The Economist as Engineer: Game Theory, Experimentation, and Computation as Tools for Design Economics. Econometrica, 70(4), 2002. 1341-1378.

Klemperer, Paul, What Really Matters in Auction Design?, Journal of Economic Perspectives, 16(1): 169-189, 2002.

Weitzman, Martin, Is the Price System or Rationing More Effective in Getting a Commodity to Those Who Need it Most?, The Bell Journal of Economics, 8, 517-524, 1977.

(b) Stable matching and assignment

Gale, David and Lloyd Shapley, College Admissions and the Stability of Marriage, American Mathematical Monthly, 69: 9-15,1962.

Roth and Sotomayor, Chapters 2-5.

Hylland, Aanund, and Richard Zeckhauser. The efficient allocation of individuals to positions, The Journal of Political Economy, 293-314,1979.

Roth, Alvin E., The Evolution of the Labor Market for Medical Interns and Residents: A Case Study in Game Theory. Journal of Political Economy, 92: 991-1016, 1984.

Kojimam, Fuhito and Parag A. Pathak. Incentives and stability in large two-sided matching markets. American Economic Review, 99:608-627, 2009

Abdulkadiroglu, Atila and Tayfun Sonmez. School choice: A mechanism design approach. American Economic Review, 93:729-747, 2003.

Abdulkadiroglu, Atila , Parag A. Pathak, and Alvin E. Roth. The New York City high school match. American Economic Review, 95:364-367, 2005.

Ashlagi, Itai, Yash Kanoria, and Jacob D. Leshno. Unbalanced random matching markets: The stark effect of competition, Journal of Political Economy,

Ashlagi, Itai and Peng Shi. Optimal allocation without money: An engineering approach. Management Science, 2015.

Peng Shi and Nick Arnosti. Design of Lotteries and Waitlists for Affordable Housing Allocation, Management Science, 2019.

Peng Shi, Assortment Planning in School Choice, 2019.

Ashlagi, Itai, and Afshin Nikzad. What matters in tie-breaking rules? how competition guides design, 2015.

Myerson, Roger Auction Design, Mathematics of Operations Research, 1981.

Milgrom, Paul. Putting Auction Theory to Work. Chapter 2-3.

W. Vickrey, Counterspeculation, auctions, and competitive sealed tenders, The Journal of Finance, 16(1) 8–37, 1961.

R. Myerson, Optimal auction design, Mathematics of Operations research, 1981.

J. Bulow and J. Roberts, The simple economics of optimal auctions, Journal of Political Economy, 1989.

J. Bulow and P. Klemperer, Auctions vs negotiations, American Economic Review, 1996.

P.R. McAfee and J. McMillan, Auctions and bidding, Journal of Economic Literature 1987.

P. Milgrom and R. Weber, A theory of auctions and competitive bidding, Econometrica, 1982.

Roth, A. E. and A. Ockenfels, Late-Minute Bidding and the Rules for Ending Second-Price Auctions: Evidence from eBay and Amazon.” American Economic Review, 92(4): 1093-1103, 2002.

(d) Mechanism design

Vickrey, William (1961): Counterspeculation, Auctions and Competitive Sealed Tenders. Journal of Finance, 16(1): 8-37.

Ausubel, Larry and Paul Milgrom, The Lovely but Lonely Vickrey Auction. in Cramton et. al Combinatorial Auctions, 2005.

J.C. Rochet, A necessary and sufficient condition for rationalizability in a quasi-linear context”, 1987.

K. Roberts, The characterization of implementable choice rules”, 1979.

F. Gul and E. Stacchetti, Walrasian equilibrium with gross substitutes, Journal of Economic Theory, 1999.

I. Ashlagi, M. Braverman, A,. Hassidim and D. Monderer, Monotonicity and implementability, Econometrica, 2011.

(e) Dynamic mechanism design and dynamic pricing

G. Gallego and G. Van Ryzin, Optimal dynamic pricing of inventories with stochastic demand over finite horizons. Management science, 40(8), 999-1020, 1994.

S. Board and A. Skrzypacz, Revenue management with forward-looking buyers, Unpublished manuscript, Stanford University,2010.

A. Gershkov, B. Moldovanu, P. Strack, Revenue Maximizing Mechanisms with Strategic Customers and Unknown, Markovian Demand

D. Bergemann and J. Valimaki, The dynamic pivot mechanism, Econometrica, 2010.

A. Gershkov and B. Moldovanu, Dynamic Revenue Maximization with Heterogeneous Objects: A Mechanism Design Approach, 168-198, 2009.

F. Gul, H. Sonnenschein, R. Wilson, Foundations of dynamic monopoly and the Coase conjecture, J. of Economic Theory, 1986.

D. Besanko and W. L. Whinston, Optimal price skimming by a monopolist facing rational consumers, Management Science, 1990.

(f) Dynamic matching

Itai Ashlagi and Alvin E. Roth. New challenges in multihospital kidney exchange. American Economic Review, 102:354-359, 2012

Nikhil Agarwal, Itai Ashlagi, Eduardo Azevedo, Clayton Featherston and Omer Karaduman. Market Failure in Kidney Exchange, 2018.

Anderson, R., Ashlagi, I., Gamarnik, D. and Kanoria, Efficient Dynamic Barter Exchange, Operations Research, 2015.

Mohammad Akbarpour, Shengwu Li, and Shayan Oveis Gharan. Dynamic matching market design. JPE, 2019.

Baccara, Mariagiovanna, SangMok Lee, and Leeat Yariv, Optimal dynamic matching, 2015.

Jacob Leshno, Dynamic Matching in Overloaded Waiting Lists, 2017.

Saturday, September 16, 2023

NBER Market Design Working Group Meeting, Fall 2023, Cambridge MA

Market Design Working Group Meeting, Fall 2023

Friday, October 27

8:30 am

Continental Breakfast

Session 1: Equity

9:00 am

Equal Pay for Similar Work

Diego Gentile Passaro, Brown University

Fuhito Kojima, Stanford University

Bobak Pakzad-Hurson, Brown University

9:45 am

Market Design for Social Justice: A Case Study on A Constitutional Crisis in India

Tayfun Sönmez, Boston College

M. Utku Ünver, Boston College

10:30 am

Break

Session 2: Artificial Intelligence

10:45 am

Artificial Intelligence and Statistical Collusion

Martino Banchio, Google Research

Giacomo Mantegazza, Stanford University

11:30 am

Combining Human Expertise with Artificial Intelligence: Experimental Evidence from Radiology

Nikhil Agarwal, Massachusetts Institute of Technology and NBER

Alex Moehring, Massachusetts Institute of Technology

Pranav Rajpurkar, Harvard University

Tobias Salz, Massachusetts Institute of Technology and NBER

12:15 pm

Lunch

Session 3: Auctions

1:30 pm

Auctions with Withdrawal Rights: A Foundation for Uniform Price

Alexander Haberman, Stanford University

Ravi Jagadeesan, Stanford University

2:15 pm

Unobserved Auctions

Hao Li, University of British Columbia

Michael Peters, University of British Columbia

3:00 pm

Entry and Exit in Treasury Auctions

Jason Allen, Bank of Canada

Ali Hortaçsu, University of Chicago and NBER

Eric Richert, University of Chicago

Milena Wittwer, Boston College

3:45 pm

Break

Session 4: Mechanism Design for Social Good

4:15 pm

Test-Optional Admissions

Wouter Dessein, Columbia University

Alexander P. Frankel, University of Chicago

Navin Kartik, Columbia University

5:00 pm

Maximizing the Effect of Altruism

Nicholas T. Wu, Yale University

Nicole Immorlica, Microsoft Research

Brendan Lucier, Microsoft Research

5:45 pm

Adjourn

6:30 pm

Group Dinner at Bambara (across the street from the Royal Sonesta)

Saturday, October 28

8:30 am

Continental Breakfast

Session 5: Distributed Ledgers

9:00 am

The Economic Limits of Bitcoin and Anonymous, Decentralized Trust on the Blockchain

Eric Budish, University of Chicago and NBER

9:45 am

Can Open Decentralized Ledgers be Economically Secure?

Jacob D. Leshno, University of Chicago

Rafael Pass, Cornell University

Elaine Shi, Carnegie Mellon University

10:30 am

Break

Session 6: School Choice

11:00 am

Leveraging Uncertainties to Infer Preferences: Robust Analysis of School Choice

Yeon-Koo Che, Columbia University

Dong Woo Hahm, University of Southern California

YingHua He, Rice University

11:45 am

Search and Biased Beliefs in Education Markets

Patrick Agte, Princeton University

Claudia Allende, Stanford University and NBER

Adam Kapor, Princeton University and NBER

Christopher Neilson, Yale University and NBER

12:30 pm

Lunch

Session 7: Signalling and Screening

1:30 pm

Comparison of Screening Devices

Frank Yang, Stanford University

Piotr Dworczak, Northwestern University

Mohammad Akbarpour, Stanford University

2:15 pm

Privacy Preserving Signals

Philipp Strack, Yale University

Kai Hao Yang, Yale University

3:00 pm

Adjourn

Monday, May 29, 2023

Further progress on course allocation, by Budish, Gao, Othman, Rubinstein and Zhang

Here are some new developments in the course allocation mechanism used initially in Wharton and now elsewhere. It turns out that strategy-proofness in the (very) large doesn't imply strategyproofness in samples of realistic size, but this seems to be fixable (and profitable manipulations were not easy to find). The paper concludes with some far ranging thoughts on the econ-cs interface.

Practical algorithms and experimentally validated incentives for equilibrium-based fair division (A-CEEI) by ERIC BUDISH, RUIQUAN GAO, ABRAHAM OTHMAN AVIAD RUBINSTEIN, and QIANFAN ZHANG

Abstract: "Approximate Competitive Equilibrium from Equal Incomes (A-CEEI) is an equilibrium-based solution concept for fair division of discrete items to agents with combinatorial demands. In theory, it is known that in asymptotically large markets:

•For incentives, the A-CEEI mechanism is Envy-Free-but-for-Tie-Breaking (EF-TB), which implies that it is Strategyproof-in-the-Large (SP-L).

•From a computational perspective, computing the equilibrium solution is unfortunately a computationally intractable problem (in the worst-case, assuming PPAD≠FP).

We develop a new heuristic algorithm that outperforms the previous state-of-the-art by multiple orders of magnitude. This new, faster algorithm lets us perform experiments on real-world inputs for the first time. We discover that with real-world preferences, even in a realistic implementation that satisfies the EF-TB and SP-L properties, agents may have surprisingly simple and plausible deviations from truthful reporting of preferences. To this end, we propose a novel strengthening of EF-TB, which dramatically reduces the potential for strategic deviations from truthful reporting in our experiments. A (variant of ) our algorithm is now in production: on real course allocation problems it is much faster, has zero clearing error, and has stronger incentive properties than the prior state-of-the-art implementation"

Here's an intriguing passage:

"In Section 6 we use our manipulation-finding algorithm in combination with our fast A-CEEI finding algorithm to explore the plausibility of effective manipulations for students bidding in ACEEI. Originally, we had expected that since our mechanism satisfies the EF-TB and SP-L properties, it would at least be practically strategyproof — if even we don’t really understand the way our algorithm chooses among the many possible equilibria, how can a student with limited information learn to strategically bid in such a complex environment?

"Indeed, in 2 out of 3 schools that we tested, our manipulation-finding algorithms finds very few or no statistically significant manipulations at all. However, when analyzing the 3rd school, we stumbled upon a simple and effective manipulation for (the first iteration of) our mechanism. We emphasize that although the manipulation is simple in hindsight, in over a year of working on this project we failed to predict it by analyzing the algorithm — the manipulation was discovered by the algorithm.

"Inspired by this manipulation, we propose a natural strengthening of envy-free (discussed below), which we call contested-envy free. We encode the analogous contested EF-TB as a new constraint in our algorithm (specifically, the integer program for finding optimal budget perturbations). Fortunately, our algorithm is still very fast even with this more elaborate constraint. And, when we re-run our manipulation-finding experiments, we observe that contested EF-TB significantly reduces the potential for manipulations in practice."

...

"Conclusion: In this work, we give a significantly faster algorithm for computing A-CEEI. Kamal Jain’s famous formulation “if your laptop cannot find it then neither can the market” [Papadimitriou 2007] was originally intended as a negative result, casting doubt on the practical implications of many famous economic concepts because of their worst-case computational complexity results. Even for course allocation, where a heuristic algorithm existed and worked in practice, Jain’s formulation seemed to still bind, as solving A-CEEI involved an intense day-long process with a fleet of high-powered cloud servers operating in parallel. The work detailed in this paper has significantly progressed what laptops can find: even the largest and most challenging real course allocation problems we have access to can now be solved in under an hour on a commodity laptop.

"This significant practical improvement suggests that the relationship between prices and demand for the course allocation problem—and potentially other problems of economic interest with complex agent preferences and heterogeneous goods—may be much simpler than has been previously believed and may be far more tractable in practice than the worst-case theoretical bounds. Recalling Jain’s dictum, perhaps many more market equilibria can be found by laptops—or, perhaps, Walras’s original and seemingly naive description of how prices iterate in the real world may in fact typically produce approximate equilibria.

"Our fast algorithm also opens the door for empirical research on A-CEEI, because we can now solve many instances and see how the solution changes for different inputs. We took it in one direction: empirically investigating the incentives properties of A-CEEI for the first time. For course allocation specifically, this faster algorithm opens up new avenues for improving student outcomes through experimentation. For instance, university administrators often want to subsidize some 6 group of students (e.g., second-year MBA students over first-year MBA students), but are unsure how large of a budget subsidy to grant those students to balance equity against their expectations. Being able to run more assignments with different subsidies can help to resolve this issue."

*************

Earlier related posts:

Thursday, April 23, 2009

Course allocation, by Eric Budish

Sunday, October 4, 2009

Course allocation by Budish, updated

Thursday, May 30, 2013

Wharton's new Course Match for MBA students to choose their classes: market design in action

Monday, August 3, 2015

Course allocation at Wharton: looking under the hood

Tuesday, June 9, 2020

Cognomos--course allocation software by Eric Budish et al.

Wednesday, May 10, 2023

New Directions in Market Design, NBER conference May 11-12, 2023 in Washington DC (and on YouTube)

I'm on my way to this conference, celebrating a quarter of a century of practical market design by economists.

New Directions in Market Design, NBER conference May 11-12, 2023 (US Eastern Time)

LOCATION Convene, 600 14th St NW in Washington, DC. and livestreamed on YouTube

ORGANIZERS Irene Y. Lo, Michael Ostrovsky, and Parag A. Pathak

NBER conferences are by invitation. All participants are expected to comply with the NBER's Conference Code of Conduct.

Supported by Schmidt Futures

Thursday, May 11

8:30 am Continental Breakfast

9:00 am Opening Talk: Alvin Roth, Stanford University and NBER ("Market Design and Maintenance")

9:30 am Break

9:45 am Electricity and Renewable Energy Market Design

Overview: Mar Reguant, Northwestern University and NBER

Viewpoint 1: Martin Bichler, Technical University of Munich

Viewpoint 2: Richard O’Neill, Federal Energy Regulatory Commission

11:05 am Market Design for the Environment

Overview: Estelle Cantillon, ULB

Viewpoint 1: Rachel Glennerster, University of Chicago and NBER

Viewpoint 2: Nathan Keohane, Environmental Defense Fund

12:25 pm Lunch discussions

2:00 pm Market Design in Healthcare

Overview: Benjamin Handel, University of California at Berkeley and NBER

Viewpoint 1: Mark Miller, Arnold Ventures

Viewpoint 2: Fanyin Zheng, Columbia University

3:20 pm Market Design for Organ Transplantation

Overview: Tayfun Sonmez, Boston College

Viewpoint 1: Nikhil Agarwal, Massachusetts Institute of Technology and NBER

Viewpoint 2: Jennifer Erickson, Organize

4:40 pm Break

5:00 pm Market Design for Education

Overview: Parag Pathak, Massachusetts Institute of Technology and NBER

Viewpoint 1: Derek Neal, University of Chicago and NBER

Viewpoint 2: Irene Lo, Stanford University

6:20 pm Adjourn

6:45 pm Group Dinner - JW Marriott

Friday, May 12

8:00 am Continental Breakfast

8:30 am Market Design for Public Housing

Overview: Nathan Hendren, Harvard University and NBER

Viewpoint 1: Winnie van Dijk, Harvard University and NBER

Viewpoint 2: Mary Cunningham, Urban Institute

9:50 am Market Design in Transportation

Overview: Michael Ostrovsky, Stanford University and NBER

Viewpoint 1: David Shmoys, Cornell University

Viewpoint 2: Wai Yan Leong, Singapore Land Transport Authority

11:10 am Break

11:30 am Market Design in Financial Markets

Overview: Haoxiang Zhu, Massachusetts Institute of Technology and NBER

Viewpoint 1: Eric Budish, University of Chicago and NBER

Viewpoint 2: Scott Mixon, CFTC

12:50 pm

Lunch discussions

2:20 pm Market Design Tools in the Regulation of Online Marketplaces

Overview: Susan Athey, Stanford University and NBER

Viewpoint 1: Preston McAfee, Google

Viewpoint 2: Michael Schwarz, Microsoft

3:40 pm Artificial Intelligence and Market Design

Overview: Kevin Leyton-Brown, University of British Columbia

Viewpoint 1: Hal Varian, Google

Viewpoint 2: Nikhil Devanur, Amazon

5:00 pm Break

5:20 pm Closing Talk: Paul Milgrom, Stanford University

5:50 pm Adjourn

6:30 pm Group Dinner - JW Marriott

Thursday, February 9, 2023

Ticketmaster and the secondary market for tickets, by Budish and Bhave

Here's a still-timely paper that was a work in progress for quite a while.

Primary-Market Auctions for Event Tickets: Eliminating the Rents of “Bob the Broker”? By Eric Budish and Aditya Bhave, American Economic Journal: Microeconomics 2023, 15(1): 142–170 https://doi.org/10.1257/mic.20180230

Abstract: "Economists have long been puzzled by event-ticket underpricing: underpricing reduces revenue for the performer and encourages socially wasteful rent-seeking by ticket brokers. What about using an auction? This paper studies the introduction of auctions into this market by Ticketmaster in the mid-2000s. By combining primary-market auction data from Ticketmaster with secondary-market resale value data from eBay, we show that Ticketmaster’s auctions “worked”: they substantially improved price discovery, roughly doubled performer revenues, and, on average, nearly eliminated the potential arbitrage profits associated with underpriced tickets. We conclude by discussing why, nevertheless, the auctions failed to take off."

From the conclusions:

"over the decade that has passed since the time of the data, rather than coming into more widespread use, primary-market auctions for event tickets instead disappeared. LexisNexis searches suggest that TM auctions were in use from their introduction in 2003 through around 2011, with a peak in around 2005–2008 but that with limited exceptions, they have not been used since.33

"We conclude by speculating as to why the auctions failed to take off. As discussed in the introduction, economic theory suggests that there are two basic choices for how to eliminate the rents of and rent-seeking by Bob the Broker: ban resale or set a market-clearing price. While auctions are no longer in use, what has at least partly taken off is using available data, including historical resale values, to set fixed prices in the primary market that more accurately approximate market clearing.

...

"We conjecture that the popularity of this practice relative to auctions partly reflects the simplicity and convenience for fans of posted prices relative to auctions, as has been documented more widely by Einav et al. (2018) and partly reflects a harder-to-model “repugnance” cost of ticket auctions (Roth 2007).

...

"Setting market-clearing prices and banning resale are two ways to modify the primary market to eliminate Bob the Broker’s rents. TM has also aggressively expanded into the secondary market, acquiring TicketsNow for $265 million in 2008 (as well as UK-based Get Me In! for an undisclosed amount); entering into secondary-market partnerships with the National Basketball Association, National Hockey League, and National Football League (Major League Baseball has a partnership with StubHub); and most recently launching a secondary market within ticketmaster.com called Fan-to-Fan Resale that lists available primary-market tickets alongside secondary-market tickets.38 This business exploits TM’s unique ability, for events where it manages the primary market, to verify the authenticity of tickets in the secondary market. With transaction fees of about 30–40 percent in the largest secondary-market venues (Budish 2019)—of the full resale value, not of just the markup versus the fixed price—perhaps eliminating the rents of Bob the Broker is less profitable than taking a cut."

Monday, December 19, 2022

Leveling the stock market playing field: SEC proposals

The WSJ has the story:

SEC Proposes Rules That Would Squeeze Stock-Market Middlemen. Agency is formally considering biggest overhaul of stock-market structure since mid-2000s By Paul Kiernan and Alexander Osipovich

"The Securities and Exchange Commission voted Wednesday to advance the biggest changes to U.S. stock-market rules since the mid-2000s, aiming to give small investors better prices on their trades and reduce some advantages enjoyed by high-speed trading firms.... Voting to advance the rules opens them to public comment until at least March 31 before the agency can decide whether to finalize them.

...

"The broad idea motivating the proposals is to use greater competition for investors’ orders to deliver better prices, while stepping up regulations of the firms that profit from handling retail stock trades.

...

"The centerpiece of the SEC’s plans is a proposal for brokers to send many small-investor stock orders into auctions. This would enable a mix of high-speed traders and institutional investors such as hedge funds or pension funds to compete to fill the orders, with the idea that investors would get better prices as a result—higher prices if they are selling shares, or lower prices if they are buying.

"The auctions would apply to so-called marketable orders—in which investors buy or sell stocks at the currently available price—less than $200,000 in size and placed by investors who average fewer than 40 trades a day. They would be required to last between one-tenth and three-tenths of a second, roughly the duration of a blink of an eye, and would likely be run by exchanges.

Requiring such auctions would be a big change. The SEC says brokers send more than 90% of marketable orders to wholesalers. Unlike exchanges, which display price quotes publicly and allow a variety of market players to attempt to fill orders, wholesalers trade directly against the incoming retail flow, an arrangement that effectively prevents other market players such as institutional investors from interacting with individual investors’ orders."

HT: Eric Budish

Saturday, December 17, 2022

Economics of pandemic vaccination in Oxford Review of Economic Policy

Vaccine development and distribution during the Covid pandemic has had some notable successes and some significant shortcomings.

Here's the latest issue of the Oxford Review of Economic Policy, which has collected articles by economists concerning some of those successes and failures and their lessons for future pandemics.