Stanford celebrates Paul Milgrom and the Incentive Auction "Dream Team"

New on the SIEPR webpage, by Krysten Crawford: To secure a mobile future, Stanford expert creates an auction like no other (the url is more informative than the headline: http://siepr.stanford.edu/highlights/secure-mobile-future-stanford-expert-paul-milgrom-creates-auction).

"More than two decades ago, Stanford economist Paul Milgrom played a key role in the design of the first wireless spectrum auction. Since then, the framework he helped create has been used in more than 80 auctions in the United States, generated billions of dollars in government licensing fees — and been replicated around the world.

"So it made sense for the Federal Communications Commission to tap Milgrom in 2011 when the agency needed a new way to free up more broadband for mobile devices. It took him and a small band of fellow economists and computer scientists 18 months to design the auction, which finally opened last month after years of regulatory procedures, software development and presentations to potential bidders.

"When the auction ends later this year, the country’s wireless landscape will never look the same.
...
"For help, Milgrom pulled together an interdisciplinary “dream team” of top experts in economics and computer science: Jonathan Levin, also a SIEPR senior fellow and faculty member in economics; Ilya Segal, a professor of economics at Stanford; and Kevin Leyton-Brown, a computer scientist at the University of British Columbia who earned his PhD from Stanford."

SITE 2023 Session 2: Market Design Thu, Aug 3 2023, 9:00am - Fri, Aug 4 2023, 5:00pm PDT

 SITE 2023  Session 2: Market Design  Thu, Aug 3 2023, 9:00am - Fri, Aug 4 2023, 5:00pm PDT

Landau Economics Building, 579 Jane Stanford Way, Stanford, CA 94305

ORGANIZED BY  Mohammad Akbarpour, Stanford University, Piotr Dworczak, Northwestern University, Ravi Jagadeesan, Stanford University, Shengwu Li, Harvard University, Ellen Muir, Harvard University

This session seeks to bring together researchers in economics, computer science, and operations research working on market design.  We’re aiming for a roughly even split between theory papers and empirical and experimental papers.  In addition to faculty members, we also invite graduate students on the job market to submit their paper for shorter graduate student talks.

Thursday, August 3, 2023 8:30 AM - 9:00 AM PDT Check-in & Breakfast

9:00 AM - 9:45 AM PDT

The Combinatorial Multi-Round Ascending Auction

Presented by: Bernhard Kasberger (Heinrich Heine University Düsseldorf). Co-author(s): Alexander Teytelboym (University of Oxford)

The Combinatorial Multi-Round Auction (CMRA) is a new auction format which has already been used in several recent European spectrum auctions. We characterize equilibria in the CMRA that feature auction-specific forms of truthful bidding, demand expansion, and demand reduction for settings in which bidders have either decreasing or non-decreasing marginal values. In particular, we establish sufficient conditions for riskless collusion. Overall, our results suggest that the CMRA might be an attractive auction design in the presence of highly complementary goods on sale. We discuss to what extent our theory is consistent with outcomes data in Danish spectrum auctions and how our predictions can be tested using bidding data.

AUG 3  9:45 AM - 10:15 AM PDT  Break

AUG 3  10:15 AM - 11:00 AM PDT

Entry and Exit in Treasury Auctions 

Presented by: Milena Wittwer (Boston College)   Co-author(s): Jason Allen (Bank of Canada), Ali Hortaçsu (University of Chicago), and Eric Richert (Princeton University)

Regulated banks—dealers—have traditionally dominated Treasury markets. More recently, less regulated institutions, such as hedge funds, have entered these markets. Understanding this phenomenon and its consequences is challenging because there is limited data on how hedge funds trade. We document steady dealer exit and rising, yet volatile hedge fund participation in the Canadian primary market. To understand hedge fund entry and to trade-off the benefits of greater competition against the costs of higher market volatility, we introduce and estimate a model with multi-unit auctions and endogenous entry. A counterfactual analysis suggests that hedge fund entry was largely driven by dealer exit, and that competition benefits are large compared to volatility costs. This trade-off is likely present in other markets with regular and irregular participants, which can be studied in our framework.

AUG 3  11:00 AM - 11:30 AM PDT Break

AUG 3 11:30 AM - 12:15 PM PDT

Principal Trading Arrangements: Optimality under Temporary and Permanent Price Impact

Presented by: Markus Baldauf (University of British Columbia)

Co-author(s): Christoph Frei (University of Alberta) and Joshua Mollner (Northwestern University)

We study the optimal execution problem in a principal-agent setting. A client (e.g., a pension fund, endowment, or other institution) contracts to purchase a large position from a dealer at a future point in time. In the interim, the dealer acquires the position from the market, choosing how to divide his trading across time. Price impact may have temporary and permanent components. There is hidden action in that the client cannot directly dictate the dealer’s trades. Rather, she chooses a contract with the goal of minimizing her expected payment, given the price process and an understanding of the dealer’s incentives. Many contracts used in practice prescribe a payment equal to some weighted average of the market prices within the execution window. We explicitly characterize the optimal such weights: they are symmetric and generally U-shaped over time. This U-shape is strengthened by permanent price impact and weakened by both temporary price impact and dealer risk aversion. In contrast, the first-best solution (which reduces to a classical optimal execution problem) is invariant to these parameters. Back-of-the-envelope calculations suggest that switching to our optimal contract could save clients billions of dollars per year.

AUG 3  12:15 PM - 1:45 PM PDT Lunch

AUG 3 1:45 PM - 2:05 PM PDT

Principal-Agent Problems with Costly Contractibility: A Foundation for Incomplete Contracts

Presented by: Roberto Corrao (Massachusetts Institute of Technology)

Co-author(s): Joel P. Flynn (Massachusetts Institute of Technology) and Karthik A. Sastry (Harvard University)

We study implementable and optimal mechanisms in principal-agent problems when agents’ actions are partially contractible. Fixing the extent of contractibility, we characterize implementable and optimal contracts. We provide conditions under which optimal mechanisms specify discontinuous payments for agents’ actions that take the form of “fines” or “bonuses.” When the principal can choose the extent of contractibility and additional contractibility has strictly positive marginal cost, we show that any optimal contract features a finite menu. This provides a foundation for the optimal incompleteness of contracts: even under arbitrarily small costs of contracting, optimal contracts specify finitely many contingencies. We apply these results to study optimal regulation of imperfectly contractible pollution, optimal incentive contracts when employees work from home, and the optimal pricing and remuneration of content creation.

AUG 3 2:05 PM - 2:25 PM PDT

The Simple Economics of Optimal Bundling

Presented by: Frank Yang (Stanford University)

We study optimal bundling when consumers differ in one dimension. We introduce a partial order on the set of bundles defined by (i) set inclusion and (ii) sales volumes (if sold alone and priced optimally). We show that if the undominated bundles with respect to this partial order are nested, then nested bundling (tiered pricing) is optimal. We characterize which nested menu is optimal: Selling a given menu of nested bundles is optimal if a smaller bundle in (out of) the menu sells more (less) than a bigger bundle in the menu. We present three applications of these insights: the first two connect optimal bundling and quality design to price elasticities and cost structures; the last one establishes a necessary and sufficient condition for costly screening to be optimal when a principal can use both price and nonprice screening instruments.

AUG 3 2:25 PM - 2:45 PM PDT

Incentive Compatibility in the Auto-bidding World

Presented by: Yeganeh Alimohammadi (Stanford University)

Co-author(s): Aranyak Mehta (Google Research) and Andres Perlroth (Google Research)

Auto-bidding has recently become a popular feature in ad auctions. This feature enables advertisers to simply provide high-level constraints and goals to an automated agent, which optimizes their auction bids on their behalf. These auto-bidding intermediaries interact in a decentralized manner in the underlying auctions, leading to new interesting practical and theoretical questions on auction design, for example, in understanding the bidding equilibrium properties between auto-bidder intermediaries for different auctions. In this paper, we examine the effect of different auctions on the incentives of advertisers to report their constraints to the auto-bidder intermediaries. More precisely, we study whether canonical auctions such as first price auction (FPA) and second price auction (SPA) are auto-bidding incentive compatible (AIC): whether an advertiser can gain by misreporting their constraints to the autobidder.

AUG 3 2:45 PM - 3:05 PM PDT

An Empirical Framework for Waitlists with Endogenous Priority: Evaluating the Heart Transplant Waitlist

Presented by: Kurt Sweat (Stanford University)

Waitlists that prioritize specific agents to achieve certain policy goals are common in practice, but policy makers often use endogenous characteristics of agents to assign waitlist priority. I study the heart transplant waitlist in the United States where the treatment that a patient receives is used to assign waitlist priority. Policy makers recently changed the prioritization in an attempt to reduce waitlist mortality by assigning higher priority to patients receiving specific treatments associated with high waitlist mortality. First, I document a significant response to waitlist incentives as usage of these treatments tripled once they were assigned higher priority, while usage of other treatments declined. Then, I estimate a dynamic discrete choice model of the treatment and transplant decision for patients on the waitlist to evaluate the effect of the change on the distribution of patient outcomes. Counterfactual outcomes estimated from the model demonstrate that the current design results in healthier patients receiving high priority treatments and better long-run outcomes. This is contrary to the policy makers goals of transplanting sicker patients and suggests that patients should be targeted using characteristics other than treatments.

AUG 3  3:05 PM - 3:45 PM PDT  Break

AUG 3 3:45 PM - 4:30 PM PDT

Trading with a Group

Presented by: Elliot Lipnowski (Columbia University)

Co-author(s): Nima Haghpanah (Pennsylvania State University) and Aditya Kuvalekar (University of Essex)

A buyer trades with a group of sellers whose heterogeneous willingness to trade is private information. She must trade with all sellers or none, and is required to offer sellers identical terms of trade. We characterize the optimal mechanism: trade occurs if and only if the buyer's benefit of trade exceeds a weighted average of sellers' virtual values. These weights are endogenous, with sellers who are less ex-ante inclined to trade being given greater influence. This mechanism uses sellers' private information in a continuous way, and always outperforms posted price mechanisms. In an extension, we characterize the entire Pareto frontier.

AUG 3  4:30 PM - 5:00 PM PDT Break

AUG 3 5:00 PM - 5:45 PM PDT Matching with Costly Interviews: The Benefits of Asynchronous Offers

Presented by: Akhil Vohra (University of Georgia)

Co-author(s): Nathan Yoda (University of Georgia)

In many matching markets, matches are formed after costly interviews. We analyze the welfare implications of costly interviewing in a model of worker-firm matching. We use our model to understand the trade-offs between a centralized matching system and a decentralized one, where matches can occur at any time. Centralized matching with a common offer date leads to coordination issues in the interview stage. Each firm must incorporate the externality imposed by the interview decisions of the firms ranked above it when deciding on its interview list. As a result, low-ranked firms often fail to interview some candidates that ex-ante have high match quality. A decentralized setting with exploding offers generates, at a minimum, the same welfare as the centralized setting, though the set of candidates who receive interviews is different. Total welfare is generally maximized with a system that ensures firms interview and match in sequence, clearing the market for the next firm. Such asynchronicity reduces interview congestion. This system can be implemented by encouraging top firms to interview and match early and allowing candidates to renege on offers.

AUG 3 6:30 PM - 8:30 PM PDT  Dinner

Friday, August 4, 2023

8:30 AM - 9:00 AM PDT Check-in and Breakfast

AUG 4  9:00 AM - 9:45 AM PDT

Describing Deferred Acceptance to Participants: Experimental Analysis

Presented by: Ori Heffetz (Cornell University and Hebrew University)

Co-author(s): Yannai Gonczarowski (Harvard University), Guy Ishai (The Hebrew University of Jerusalem), and Clayton Thomas (Princeton University)

Designed markets often relies on carefully crafted descriptions of mechanisms. By and large, these descriptions implicitly attempt to convey as directly as possible how outcomes are calculated. Are there principled, alternative theories of how to construct descriptions to expose different properties of mechanisms? Recently-proposed menu descriptions aim to provide such a theory towards exposing the strategyproofness of real-world mechanisms such as Deferred Acceptance. We design an incentivized experiment to test the ability of a menu description (compared to a traditional description) to affect participant behavior and their understanding of strategyproofness. We also design treatments conveying the property of strategyproofness itself rather than the full details of the mechanism, with one treatment inspired by traditional definitions and one inspired by menu descriptions.

AUG 4  9:45 AM - 10:15 AM PDT Break

AUG 4 10:15 AM - 11:00 AM PDT

An Experimental Evaluation of Deferred Acceptance

Presented by: Jonathan Davis (University of Oregon)

Co-author(s): Kyle Greenberg (West Point) and Damon Jones (University of Chicago)

We present evidence from a randomized trial of the impact of matching workers to jobs using the deferred acceptance (DA) algorithm. Our setting is the U.S. Army’s annual many-to-one marketplace that matches over 14,000 officers to units. Officers and jobs are partitioned into over 100 distinct markets, our unit of randomization. Matching with DA reduced officers’ attrition in their first year in their new match by 16.9 percent, but these gains disappear in the second year. We can rule out a 1.5 pp reduction in attrition within two years. Matching with DA had no impact on performance evaluations or promotions. Although matching with DA increased truthful preference reporting by a statistically significant 10 percent, many officers matched by DA misreport their true preferences. We present new evidence suggesting that communication and coordination of preferences may limit the benefits of strategyproofness in matching markets where each side actively ranks the other.

AUG 4  11:00 AM - 11:30 AM PDT Break

AUG 4 11:30 AM - 12:15 PM PDT

Design on Matroids: Diversity vs Meritocracy

Presented by: M. Bumin Yenmez (Boston College)

Co-author(s): Isa E. Hafalir (University of Technology Sydney), Fuhito Kojima (University of Tokyo), and Koji Yokote (University of Tokyo)

We provide optimal solutions to an institution that has dual goals of diversity and meritocracy when choosing from a set of applications. For example, in college admissions, administrators may want to admit a diverse set in addition to choosing students with the highest qualifications. We provide a class of choice rules that maximize merit subject to attaining a diversity level. Using this class, we find all subsets of applications on the diversity-merit Pareto frontier. In addition, we provide two novel characterizations of matroids.

AUG 4  12:15 PM - 1:45 PM PDT Lunch

AUG 4  1:45 PM - 2:30 PM PDT

Pareto Improvements in the Contest for College Admissions

Presented by: Ron Siegel (Pennsylvania State University)

Co-author(s): Kala Krishma (Pennsylvania State University), Sergey Lychagin (Central European University), Wojciech Olszewski (Northwestern University), and Chloe Tergiman (Pennsylvania State University)

College admissions in many countries are based on a centrally administered test. Applicants invest a great deal of resources to improve their performance on the test, and there is growing concern about the large costs associated with these activities. We consider modifying such tests by introducing performance-disclosure policies that pool intervals of performance rankings, and investigate how such policies can improve students’ welfare in a Pareto sense. Pooling affects the equilibrium allocation of students.

AUG 4 2:30 PM - 3:00 PM PDT  Break

AUG 4 3:00 PM - 3:45 PM PDT

Test-Optional Admissions 

Presented by: Alex Frankel (University of Chicago)

Co-author(s): Wouter Dessein (Columbia University) and Navin Kartik (Columbia University)

The Covid-19 pandemic has accelerated the trend of many colleges moving to test-optional, and in some cases test-blind, admissions policies. A frequent claim is that by not seeing standardized test scores, a college is able to admit a student body that it prefers, such as one with more diversity. But how can observing less information allow a college to improve its decisions? We argue that test-optional policies may be driven by social pressure on colleges’ admission decisions. We propose a model of college admissions in which a college disagrees with society on which students should be admitted. We show how the college can use a test-optional policy to reduce its “disagreement cost” with society, regardless of whether this results in a preferred student pool. We discuss which students either benefit from or are harmed by a test-optional policy. In an application, we study how a ban on using race in admissions may result in more colleges going test optional or test blind.

AUG 4  3:45 PM - 4:15 PM PDT Break

AUG 4  4:15 PM - 5:00 PM PDT

Equal Pay for Similar Work

Presented by: Bobby Pakzad-Hurson (Brown University)

Co-author(s): Diego Gentile Passaro (Brown University) and Fuhito Kojima (University of Tokyo)

Equal pay laws increasingly require that workers doing “similar” work are paid equal wages within a firm. We study such “equal pay for similar work” (EPSW) policies theoretically and empirically. In our model, we show that when EPSW restricts firms by protected class (e.g. no woman can be paid less than any similar man, and vice versa) firms segregate their workforce by gender in equilibrium. This endogenously lowers competition for workers, as it becomes costly for firms to poach from one another–doing so exposes them to the bite of the policy. When there are more men than women, EPSW leads to an increase in the equilibrium gender wage gap. For a sufficiently high ratio of men to women, there exist equilibria with arbitrarily low wages for women, leading to a particularly large wage gap. By contrast, EPSW that is not based on protected class can decrease the equilibrium wage gap. We test our model predictions using a difference-in-difference approach to analyze a gender-based EPSW enacted in Chile in 2009. We find that the EPSW increases the share of employees working at gender-segregated firms by 3% and increases the gender wage gap by 3%.

Some economics of providing cloud computing, by Microsoft economists Hummel and Schwarz

 Here's a paper on an aspect of cloud computing by two Microsoft economists. (Microsoft's cloud service is called Microsoft Azure.)  In addition to the capacity question the paper models, it presents a brief, clear overview of the market for cloud computing.

Efficient Capacity Provisioning for Firms with Multiple Locations: The Case of the Public Cloud  by Patrick Hummel∗ and Michael Schwarz*   March 26, 2021

Abstract: This paper presents a model in which a firm with multiple locations strategically chooses capacity and prices in each location to maximize efficiency. We find that the firm provisions capacity in such a way that the probability an individual customer will be unable to purchase the goods the customer desires is lower in locations with greater expected demand. The firm also sets lower prices in larger locations. Finally, we illustrate that if a customer is indifferent between multiple locations, then it is more efficient to place this customer in a location with greater expected demand. These theoretical results are consistent with empirical evidence that we present from a major public cloud provider.

"2.1 Industry Overview

"The cloud computing industry is young, large, and rapidly growing. Although some of the concepts behind the public cloud were developed as early as the 1960s, all modern public clouds first emerged in the 21st century (Foote 2017). Today annual world cloud revenues exceed $250 billion and are expected to grow by another 20% in 2021 (Graham et al. 2020a).

"The public cloud consists of a wide range of services including infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). SaaS involves providing applications such as web-based email and productivity software to a consumer that can be accessed via the Internet. PaaS provides a platform for deploying consumer created applications using the provider’s programming languages, libraries, and tools.

"And IaaS provisions fundamental computing resources such as processing, storage, and network to a consumer that can be used to deploy and run arbitrary software (Mell and Grance 2011)."

...

"2.5 Why Auctions are Not Used

...

"Since cloud providers provision enough capacity to almost always be able to meet demand, if a cloud provider used an auction to sell compute to customers, the final price at the auction would almost always be equal to the reserve price. However, since cloud customers typically have a value per unit of compute that is orders of magnitude higher than the corresponding capacity costs, in the rare event that there was not enough capacity to meet all demand, the final price in an auction would be dramatically higher

than the cloud provider’s costs. Thus, if a cloud provider used an auction to sell compute to customers, there would be a very high probability that all customers could obtain all the compute they wanted at a low price and a low probability that the final price would

be very high.

"There are two problems with this pricing that would make auctions unsuitable in practice. First, using an auction results in a very high amount of uncertainty about the final realized prices. Thus, if either the cloud provider or the cloud customers are at all risk averse, using an auction to set prices will not meet either the cloud provider’s or the cloud customers’ needs.

"Second, under an auction a cloud provider has a far stronger incentive to underinvest in capacity than under a fixed price mechanism. Under a fixed price mechanism, the cloud provider’s revenue can only go down as a result of underinvesting in capacity, as the cloud provider will not be able to service as much demand. But under an auction, underinvesting in capacity will significantly increase a cloud provider’s revenue by increasing the probability that there will not be enough capacity to meet demand, thereby increasing the probability that the final price in the auction will be very high. Thus, using a fixed price mechanism also enables a cloud provider to more credibly commit to provision the efficient amount of capacity. We illustrate these points formally in Appendix A in the

paper."

Incentives in Computer Science--Tim Roughgarden

There was a time when only economists worried about incentives, but as this great looking computer science course by Tim Roughgarden shows, that time is long past...

CS 269I: Incentives in Computer Science

Instructor:

• Tim Roughgarden (Office hours (note new time): Mondays 12:15-1:15 PM, Gates 474. Email: tim@cs.stanford.edu.)

Prerequisites: Mathematical maturity at the level of undergraduate algorithms (CS161). Programming maturity at the level of 106B/X.
Course Description: Many 21st-century computer science applications require the design of software or systems that interact with multiple self-interested participants. This course will provide students with the vocabulary and modeling tools to reason about such design problems. Emphasis will be on understanding basic economic and game theoretic concepts that are relevant across many application domains, and on case studies that demonstrate how to apply these concepts to real-world design problems. Topics include auction and contest design, equilibrium analysis, cryptocurrencies, design of networks and network protocols, matching markets, reputation systems, and social choice. Possible case studies include BGP routing, Bitcoin, eBay's reputation system, Facebook's advertising mechanism, Mechanical Turk, and dynamic pricing in Uber/Lyft.
General references: Twenty Lectures on Algorithmic Game Theory, Cambridge University Press, 2016. See also the Amazon page.

• This textbook is based on the course CS364A. The overlap with 269I will be roughly 20-25%. Though if you enjoy this course, you're likely to also enjoy many of the topics in this book.

The following collection is older and targeted more to researchers than to students, but is still useful for several topics.

• Algorithmic Game Theory, Cambridge University Press, 2007. Read the entire book online by clicking here (look under the "Resources" tab).

We will also draw on the following books for some of the lectures.

• Parkes and Seuken, Economics and Computation (draft), 2016. (Stanford access only.)
• Easley and Kleinberg, Networks, Crowds, and Markets, 2010.

Lecture notes

• Lecture 1 (The Draw/College Admissions) [beta version]
• Lecture 2 (Stable Matching) [beta version]
• Lecture 3 (Strategic Voting) [beta version]
• Lecture 4 (Voting Rules as MLE/Knapsack Voting) [beta version]
• Lecture 5 (Incentives in P2P Networks) [beta version]
• Lecture 6 (Incentivizing Participation) [beta version]
• Lecture 7 (Selfish Routing) [beta version]
• Lecture 8 (Incentives in BGP Routing) [beta version]
• Lecture 9 (Incentives in Bitcoin) [beta version]
• Lecture 10 (Incentives in Crowdsourcing) [beta version]
• Lecture 11 (slides) (Incentives in Societal Networks) [guest lecture by Balaji Prabhakar]
• Lecture 12 (Reputation Systems) [beta version]
• Lecture 13 (Auction Basics) [beta version]
• Lecture 14 (Sponsored Search) [beta version]
• Lecture 15 (VCG Mechanism) [beta version]
• Lecture 16 (Revenue-Optimal Auctions) [beta version]
• Lecture 17 (Incentiving Forecasts and Feedback) [beta version]
• Lecture 18 (Prediction Markets) [beta version]
• Lecture 19 (Time-Inconsistent Planning) [beta version]
• Lecture 20 (Fair Division) [beta version]

Coursework

• Exercise Sets (50%): Exercise sets will be handed out on Wednesdays and will be due one week later. You can work in pairs, if you wish.
  • Here's a LaTeX template that you can use to type up solutions. Here and here are good introductions to LaTeX.
  • Week 1 Exercises
  • Week 2 Exercises
  • Week 3 Exercises
  • Week 4 Exercises
  • No exercises for Week 5!
  • No exercises for Week 6!
  • Week 7 Exercises
  • Week 8 Exercises
  • Week 9 Exercises
• Final Project (50%): For details and some example topics, see here.

Tentative Syllabus (will likely change)

• Week 1: Introduction to incentives through killer examples.
• Week 2: Social choice (voting, Arrow's impossibility theorem, etc.).
• Week 3: Incentives in peer-to-peer and social networks (e.g., incentives in BitTorrent).
• Week 4: Incentives in communication networks (routing, flow control, etc.).
• Week 5: Incentives in cryptocurrencies (like Bitcoin).
• Week 6: Reputation systems. Incentives in crowdsourcing.
• Week 7: Basic auction theory (eBay, sponsored search auctions).
• Week 8: Advanced auction theory and mechanism design (Facebook advertising auctions, contest design).
• Week 9: Scoring rules and prediction markets.
• Week 10: Lessons from behavioral economics (i.e., how do people make decisions, anyway?).

Detailed Lecture Schedule

• Lecture 1 (Mon Sept 26): The incentives of the Draw, past and present. Pareto optimality and strategyproofness. College admissions. One-sided vs. two-sided markets. The National Resident Matching Program (NRMP). Supplementary reading:
  • Check out the changes made to the Draw in 1970, as reported by the Stanford Daily. The other articles make for a fascinating time capsule, as well.
  • The original Gale-Shapley paper (1962). It's very easy to read!
• Lecture 2 (Wed Sept 28): Stable matchings. Properties of the deferred acceptance (Gale-Shapley) mechanism. Could college admissions go through a centralized clearinghouse? Supplementary reading:
  • Biró, Student Admissions in Hungary as Gale and Shapley Envisaged, 2008.
  • Section 2 of Lecture 10 from CS364A (or from the optional textbook).
  • The paper that compares the evolution of different resident-hospital matching algorithms in the U.K. (Roth, 1991).
  • Citation for the 2012 Nobel Prize (Roth and Shapley).
• Lecture 3 (Mon Oct 3): Participatory democracy. Strategic voting. Spoilers and the 2000 US election. Majority, plurality, ranked-choice voting, Borda counts. Gibbard-Satterthwaite and the impossibility of reasonable strategyproof voting rules. Arrow's Impossibility Theorem. Compromises, single-peaked preferences, and the median voting rule. Supplementary reading and resources:
  • Participatory budgeting in general and at Stanford.
  • The rank aggregation problem.
  • Reasonably short proofs of the Gibbard-Satterthwaite and Arrow impossibility theorems are here (see Sections 1.2.3 and 1.2.4).
  • Chapter 23 of the Easley/Kleinberg book (see general references).
• Lecture 4 (Wed Oct 5): Subjective vs. objective interpretations of voting rules. Metaphor: linear regression as the maximum likelihood solution with normally distributed errors. Marquis de Condorcet and majority rule as a maximum likelihood estimator. The Kemeny-Young rule. Knapsack voting and its properties. Supplementary reading and resources:
  • The dramatic life of Marquis de Condorcet.
  • See Pnyx for an implementation of the Kemeny rule.
  • Knapsack voting, by Goel/Krishnaswamy/Sakshuwong (2014).
  • Section 15.2 of the Parkes/Suen book (see general references).
• Lecture 5 (Mon Oct 10): Incentives in peer-to-peer (P2P) networks. History lesson: Napster, Gnutella, etc. Free riding on Gnutella. Prisoner's Dilemma. Repeated Prisoner's Dilemma: the grim trigger and Tit-for-Tat stategies. Tit-for-tat in the BitTorrent reference client. Strategic clients (BitThief and BitTyrant). Supplementary reading:
  • Chapter 5 of the Parkes/Seuken book draft, above.
  • Free Riding on Gnutella (Adar/Huberman, 2000)
  • The Axelrod tournaments: The Evolution of Cooperation (Axelrod/Hamilton, 1981)
  • Incentives Build Robustness in BitTorrent (Cohen, 2003) describes the motivation for the original design.
  • BitThief (Locher/Moor/Schmid/Wattenhofer, 2006)
  • BitTyrant (Piatek/Isdal/Anderson/Krishnamurthy/Venkataramani, 2007)
• Lecture 6 (Wed Oct 12): Coordination games. Technology adoption and network cascades. Individual vs. collective preferences in public good problems. Case study: badge design in Stack Overflow, Coursera, etc. Supplementary reading:
  • See CS 224W for much more on network cascades.
  • Steering User Behavior with Badges (Anderson/Huttenlocher/Kleinberg/Leskovec, 2013)
  • Engaging with Massive Online Courses (same authors, 2014)
• Lecture 7 (Mon Oct 17): Selfish routing and network over-provisioning. Braess's paradox and Pigou's example. The price of anarchy. Modest over-provisioning guarantees near-optimal routing.
  • Demonstration of Braess's paradox.
  • How Bad Is Selfish Routing? (Roughgarden/Tardos, 2000)
  • The Price of Anarchy is Independent of the Network Topology (Roughgarden, 2002)
  • See also Lectures 11 (Sections 1-3) and 12 (Section 1) from CS364A (or from the optional textbook).
• Lecture 8 (Wed Oct 19): The Border Gateway Protocol for Internet routing. Stable routings: non-uniqueness and non-existence. Dispute wheels and the convergence of BGP to a unique solution. Incentive issues. Incentive-compatability with path verification. Supplementary reading:
  • The Stable Paths Problem and Interdomain Routing (Griffin/Shepherd/Wilfong, 2002)
  • Stable Internet Routing Without Global Coordination (Gao/Rexford, 2001)
  • Interdomain Routing and Games (Levin/Schapira/Zohar, 2008)
  • A Survey of Interdomain Routing Policies (Gill/Schapira/Goldberg, 2013)
  • Latest draft of the BGPsec protocol (2016)
• Lecture 9 (Mon Oct 24): Incentives in Bitcoin mining. Transactions and the Bitcoin blockchain protocol. Forks. Incentive issues: the 51% attack, the double-spend attack, and selfish mining. Supplementary reading:
  • General reference: the book Bitcoin and Cryptocurrency Technologies. (Narayanan/Bonneau/Felten/Miller/Goldfeder, 2016)
  • See also Section 22.3 of the Parkes/Suen book (see general references).
  • Majority is not Enough: Bitcoin Mining is Vulnerable (Eyal/Gün Sirer, 2014)
• Lecture 10 (Wed Oct 26): Incentives in crowdsourcing. Bitcoin in a regime with high transaction fees. The DARPA Network Challenge and incentivizing recruitment. Sybil attacks and possible solutions. The "Wisdom of the Crowd": fact or fiction? Herding behavior and information cascades. Supplementary reading:
  • On the Instability of Bitcoin Without the Block Reward (Carlsten/Kalodner/Weinberg/Narayanan, 2016)
  • Time-Critical Social Mobilization (Pickard et al., 2011) describes the MIT group's winning strategy in the DARPA Network Challenge.
  • Less happy times in the 2011 DARPA Shredder Challenge.
  • On Bitcoin and Red Balloons (Babaioff/Dobzinski/Oren/Zohar, 2012)
  • Chapter 16 of the Easley/Kleinberg book (see general references).
• Lecture 11 (Mon Oct 31): Incentives in societal networks (guest lecture by Balaji Prabhakar). "Nudges" for changing behavior. Case studies in Bangalore, Singapore, and at Stanford.
  • Balaji's slides
  • An Incentive Mechanism for Decongesting the Roads: A Pilot Program in Bangalore (Merugu/Prabhakar/Rama, 2009)
  • INSINC: A Platform for Managing Peak Demand in Public Transit (Pluntke/Prabhakar, 2013)
• Lecture 12 (Wed Nov 2): Adverse selection, moral hazard, and reputation systems. The market for lemons. Analogs in health insurance, the labor market, and online platforms. Moral hazard. Reputational effects in the n-person Prisoner's Dilemma. Whitewashing and the pay-your-dues strategy. Sybil attacks. Case study: the evolution of eBay's reputation system. Supplementary reading:
  • Chapter 27 of the AGT book (see general references).
  • Chapter 20 of the Parkes/Suen book (see general references).
  • Sections 22.5-22.9 of the Easley/Kleinberg book (see general references).
  • The Social Cost of Cheap Pseudonyms (Friedman/Resnick, 2001)
  • The evolution of the eBay reputation system: The Limits of Reputation in Platform Markets: An Empirical Analysis and Field Experiment(Nosko/Tadelis, 2015)
• Lecture 13 (Mon Nov 7): Auction design basics. How would you bid in a first-price auction? The Vickrey auction and truthfulness. Welfare maximization. Introduction to sponsored search auctions.
  • This lecture is based on Lecture 2 from CS364A (or from the optional textbook).
  • Optional: The Economics of Internet Search (Varian, 2006)
• Lecture 14 (Wed Nov 9): The theory of first-price auctions. Externalities. VCG: a truthful sponsored search auction. GSP vs. VCG. Supplementary reading:
  • See Section 2.3 of Hartline's book for more about the Bayes-Nash equilibria of first-price auctions.
  • Sponsored search: see AGT book, Sections 28.1-28.3.1 (see general references).
  • Internet Advertising and the Generalized Second Price Auction: Selling Billions of Dollars Worth of Keywords (Edelman/Ostrovsky/Schwarz, 2007)
  • Position Auctions, (Varian, 2007)
  • See also this CS364B course for tons of subtopics and references on sponsored search auctions (circa late 2007).
• Lecture 15 (Mon Nov 14): Revenue equivalence of the GSP and VCG sponsored search auctions. VCG in AdSense and Facebook. The general VCG mechanism and its truthfulness. Practical issues with VCG. Supplementary materials:
  • The VCG Auction in Theory and Practice (Varian/Harris, 2014)
  • On How Machine Learning and Auction Theory Power Facebook Advertising, talk by Eric Sodomka (2015).
• Lecture 16 (Wed Nov 16): Revenue maximization. Bayesian optimal auctions. Monopoly prices. Optimality of Vickrey with a monopoly price reserve. Case study: reserve prices in Yahoo! keyword auctions. Prior-independent auctions and the Bulow-Klemperer theorem. Further reading:
  • For more details and proofs, see Lectures 5 and 6 from CS364A (or the optional textbook).
  • Ostrovsky/Schwarz, Reserve Prices in Internet Advertising Auctions: A Field Experiment, 2009.
• Lecture 17 (Mon Nov 28): Strictly proper scoring rules. Incentivizing honest opinions. Output agreement. Peer prediction. Further reading:
  • Section 27.4 of the AGT book (see general references).
  • Chapter 17 of the Parkes/Suen book (see general references).
• Lecture 18 (Wed Nov 30): Prediction markets. The Iowa Electronic Markets and continuous double auctions. The Policy Analysis Market and the Wisdom of Crowds. Market scoring rules and automated market-makers. Further reading:
  • Chapter 26 of the AGT book (see general references).
  • Chapter 18 of the Parkes/Suen book (see general references).
  • The Policy Analysis Market: A Thwarted Experiment in the Use of Prediction Markets for Public Policy (Hanson, 2007)
• Lecture 19 (Mon Dec 5): Behavioral economics. Time-inconsistent planning: procrastination, choice reduction, and undue obedience. Upper and lower bounds on cost ratios. Naive vs. sophisticated agents. Further reading:
  • Procrastination and Obedience (Akerlof, 1991)
  • Time-Inconsistent Planning (Kleinberg/Oren, 2014)
  • For tighter bounds, see Computational Issues in Time-Inconsistent Planning (Tang/Teng/Wang/Xiao/Xu, 2015)
  • Planning Problems for Sophisticated Agents with Present Bias (Kleinberg/Oren/Raghavan, 2016)
• Lecture 20 (Wed Dec 7): Fair division. The cut and choose protocol and envy-freeness. The Selfridge-Conway envy-free protocol for 3 players. Recent advances for 4 or more players. The rent division problem, and the maxmin envy-free solution. Further reading:
  • Quanta article about recent advances in envy-free cake-cutting (Klarreich, 2016)
  • A Discrete and Bounded Envy-free Cake Cutting Protocol for Any Number of Agents (Aziz/Mackenzie, 2016)
  • Which Is the Fairest (Rent Division) of Them All?, (Gal/Mash/Procaccia/Zick, 2016)
  • Fair division in practice: spliddit

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.

(c) Auctions and revenue equivalence

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.

The FCC's upcoming 2016 Incentive Auction: SIEPR policy brief by Greg Rosston and Addrzej Skrzpacz

Moving from Broadcast Television to Mobile Broadband: The FCC’s 2016 Incentive Auction

Gregory Rosston, Andrzej Skrzypacz

 Download publication PolicyBrief-Dec16.pdf (143.25 KB)

Bob Wilson wins the BBVA Foundation Frontiers of Knowledge Award in Economics

The BBVA Foundation Frontiers of Knowledge Award in Economics, Finance and Management has been granted in this eighth edition to Robert B. Wilson for “pioneering contributions to the analysis of strategic interactions when economic agents have limited and different information about their environment.” In the view of the jury, “his research on auctions, electricity pricing, reputation and dynamic interactions under such informational circumstances was groundbreaking and pervades economic analysis to this day.” 

ROBERT WILSON

The BBVA Foundation Frontiers of Knowledge Award in Economics, Finance and Management has been granted in this eighth edition to Robert B. Wilson for “pioneering contributions to the analysis of strategic interactions when economic agents have limited and different information about their environment.” In the view of the jury, “his research on auctions, electricity pricing, reputation and dynamic interactions under such informational circumstances was groundbreaking and pervades economic analysis to this day.”

For example, one of the big questions in economics is how to convince market participants to cooperate in the presence of asymmetric information, i.e., when some have access to information that others lack. Robert Wilson has spent his career studying how economic interactions unfold in circumstances of informational inequality, and has come up with a solution – that agents aim towards a reputation which facilitates cooperation.

Wilson provides tools and strategies to build reputation under varying scenarios. In two of his best known papers, he explores environments requiring different types of reputation: whereas a monopolist tries to convey an image of toughness to defend its market position and fend off unwanted competition, in situations of multilateral conflict like the “repeated prisoners’ dilemma”, the goal is to pursue a reputation for “cooperative” behavior.

Until the 1960s, the standard wisdom was that market pricing corresponded to a cooperative model in which all players shared the same information. Wilson, however, was among the first to realize that perfect information could not be assumed, and the insights of noncooperative theory must be brought into play.

Robert B. Wilson (Geneva, Nebraska, 1937) graduated in mathematics from the University of Harvard. He went on to complete a master’s degree at Harvard Business School (1961), where he also obtained his PhD with a thesis on sequential quadratic programming (1963).
In 1964 he joined the faculty at Stanford Business School, where he remains to this day. Wilson has applied his mathematical skills and game theory expertise to auction designs and competitive bidding strategies in the oil, communication, and power industries. His book Nonlinear Pricing is a referent in tariff design for public utilities from energy to transport.

Economic engineering

It was in the field known as economic engineering that Wilson put game-theoretic tools to use in improving market mechanisms, devoting most of his energies to public auctions. Among his projects in this area, we can cite the bidding for offshore oil leases along the California coast, as well as others to do with electrical power exchange and pricing.

He was accompanied in his work on auction design by one of his disciples, Paul Milgrom, winner of a BBVA Foundation Frontiers of Knowledge Award in 2012 for his contributions in this and other domains.

In the mid-1990s, California telecom company Pacific Bell was preparing to bid in an auction called by the U.S. Federal Communications Commission. Wilson and Milgrom pointed out errors in the auction design that produced a worse outcome for both organizers and bidders and proposed an alternative method which the FCC agreed to try. Their innovation, known as the simultaneous multiple round auction (SMR), replaced the traditional sealed envelope with an open bidding format, in which each company could observe what the rest were offering, supplemented by rules to prevent monopoly pricing. The auction – of electromagnetic spectrum for what was then the new generation of cell phones and other wireless communication devices – raised the record sum of over seven billion dollars, and testified in the most practical way possible to the value of game theory in strategic decision-making.

Wilson, meantime, was exploring other kinds of economic interaction. And soon concluded that reputation was among the most powerful spurs to cooperation. “Reputation effects are most prominent in bargaining,” he remarked yesterday after hearing of the award. “For example, in labor negotiations when a firm incurs the costs of a strike in order to convince the union that the marginal productivity of labor is not higher than it actually is, it is sending out a credible signal that sustains its reputation.”

Still in the frame of game theory, Wilson, along with David Kreps, came up with the concept of sequential equilibrium, which describes the anticipated sequence of reactions of market participants on discovering that others have deviated from the original plan. “It provides each player with hypotheses about how others will act as events unfold,” he explains. This concept has given rise to a wide range of applications. In industrial organization, for instance, it has enabled more accurate modeling of price wars.

Wilson is still engaged in research at Stanford University. He is currently studying “repeated interactions between two parties who can benefit from sustained cooperation,” a situation, he notes, that may be short-lived, since “not every kind of incentive encourages cooperation on a lasting basis.” 

Author of over a hundred articles in international journals, he has consistently combined the construction of a robust theoretical framework with the search for practical solutions: “The value of theory is its usefulness in addressing practical problems, while, for the theorist, the problems encountered by practitioners provide a wealth of topics.”

This combination is a constant in his professional life, where he has alternated the presidency of the Econometric Society and associate editorship of journals like Economic Theory with advisory work for the United States Department of the Interior, the Electric Power Research Institute, the Federal Communications Commission, the Canadian Competition Bureau and sundry private corporations.

International jury

The jury in this category was chaired by Eric S. Maskin, Adams University Professor at Harvard University (United States) and 2007 Nobel Laureate in Economics, with Manuel Arellano, Professor of Econometrics in the Center for Monetary and Financial Studies (CEMFI) of Banco de España (Spain), acting as secretary. Remaining members were Pinelopi Koujianou Goldberg, William K. Lanman, Jr. Professor of Economics at Yale University (United States); Andreu Mas-Colell, Professor of Economics at Pompeu Fabra University (Spain) and 2009 BBVA Foundation Frontiers of Knowledge Laureate in Economics; Jean Tirole, Chairman of the Foundation Jean-Jacques Laffont at Toulouse School of Economics (France), 2008 BBVA Foundation Frontiers of Knowledge Laureate in Economics and 2014 Nobel Prize in Economics; and Fabrizio Zilibotti, Chair of Macroeconomics and Political Economy in the Department of Economics at the University of Zurich (Switzerland).

****
And here are the BBVA laureates in other subjects.

Incentive auctions for water rights

 Here's a press release from Auctionomics, the consulting firm run by Paul Milgrom and his business partner Silvia Console Battilana. They propose to repurpose water rights in a way that may resemble the recent incentive auctions for repurposing radio spectrum.

From Lawsuits to Solutions: Auctionomics Is Harnessing Efficient Market Design and Deep Tech for a Litigation-Free Solution to the Water Crisis by Auctionomics 

"Earlier this year, Paul co-hosted a conference at Stanford University attended by a group of economists, lawyers, and water experts. The group developed a proposal for a novel policy to fix the Colorado River crisis: the U.S. should redefine and buy back existing water rights, just as it did for misallocated rights to radio airwaves.

Auctionomics led the development of the FCC's Broadband Incentive Auction, converting TV licenses to new valuable uses. The current issues with water rights are similar to those of the radio spectrum, where existing rights holders with solid legal standing were hesitant to change the status quo, despite the clear misallocation of resources.

However, Auctionomics successfully addressed the problem with its innovative auction design, facilitating next-generation telecommunications and raising $19.8 billion while safeguarding existing broadcasters.

The Colorado River proposal aims to address deficiencies in the current water rights allocation system. The existing system hinders mutually beneficial trades between users and prohibits water banking - a means to enable farmers or cities manage current water use more efficiently, leaving more in reservoirs for future dry periods.

While there are historical reasons for these limitations - the uses of river water are diverse, interconnected, and poorly measured. Modifying them can result in severe consequences in a system that guarantees inefficiency and overconsumption. However, the same model employed to redistribute broadband spectrum can incentivize water rights holders to use their water more efficiently.

Auctionomics aims to adapt this model to the Colorado River with practical steps involving a hydrological survey, voluntary redefinition of water rights, and purchasing enough new rights from willing sellers to meet the necessary reductions in total consumption."

FCC incentive auctions

Here's a good way to begin to design an auction: FCC hires top economists

"As the Federal Communications Commission (FCC) moves to implement its new authority to sell valuable radio spectrum via incentive auctions, it is seeking advice from a group of economists with expertise in auction design and competition policy.

"The commission has retained a group of prize-winning economists led by Paul Milgrom, the Ely Professor of Humanities and Sciences at Stanford University. Milgrom, who is considered one of the foremost thinkers in auction theory and design, helped the FCC create its first spectrum auctions — which have served as a blueprint for similar auctions around the world.

"Milgrom will be assisted by Professors Jonathan Levin and Ilya Segal, also of Stanford. Levin chairs the university's economics department, and is a winner of the prestigious John Bates Clark medal, an award for young economists whose winners often go on to win the Nobel Prize in economics. Segal is a recipient of the Compass-Lexecon prize, which is awarded to significant contributors to the understanding and implementation of competition policy.

"The Stanford professors will be joined by Washington, D.C., based Lawrence Ausubel, an auction design expert who teaches at the University of Maryland."

The incentive auction (for radio spectrum) in three videos

These come from the Edelman competition:

Video 1: https://www.youtube.com/watch?v=GKWs5My86fw

Video 2: https://www.youtube.com/watch?v=TMAfacbPZ7Q

Video 3: https://www.youtube.com/watch?v=IeijpJ_6u_U

Earlier post:

Saturday, April 21, 2018

FCC receives Edelman award for incentive spectrum auction

Advancing wireless communication: FCC awarded the 2018 INFORMS Edelman Award, the leading award in analytics and operations research

NBER market design conference Oct 19-20, 2012: preliminary program

NATIONAL BUREAU OF ECONOMIC RESEARCH, INC.

Market Design Working Group Meeting

Susan Athey and Parag Pathak, Organizers

October 19-20, 2012

NBER
2^nd Floor Conference Room1050 Massachusetts Avenue
Cambridge, MA
PROGRAM

Friday, October 19:
8:30 am	Continental Breakfast
9:00 am	Mechanism Design and Congestion William Fuchs, University of California at Berkeley Andrzej Skrzypacz, Stanford University Costs and Benefits of Dynamic Trading in a Lemons Market
	Jacob Leshno, Columbia University Dynamic Matching in Overloaded Systems
10:20 am	Break
10:35 am	Auctions Kenneth Hendricks, University of Wisconsin and NBER Daniel Quint, University of Wisconsin Indicative Bids as Cheap Talk Sergiu Hart, Hebrew University Noam Nisan, Hebrew University The Menu-Size Complexity of Auctions
	Yeon-Koo Che, Columbia University Jinwoo Kim, Yonsei University Fuhito Kojima, Stanford University Efficient Assignment with Interdependent Values
12:35 pm	Lunch
1:15 pm	Organ Exchange
	Itai Ashlagi, MIT Alvin Roth, Stanford University and NBER Kidney Exchange in Time and Space
	Tayfun Sonmez, Boston College M. Utku Unver, Boston College Welfare Consequences of Transplant Organ Allocation Policies
2:40 pm	Break
3:00 pm	FCC Incentive AuctionLawrence Ausubel, University of Maryland Paul Milgrom, Stanford University Ilya Segal, Stanford UniversityThe 'Incentive Auctions' and Mechanism Design Peter Cramton, University of Maryland Title to be announced
5:15 pm	Adjourn Saturday, October 20: 8:30 am Continental Breakfast 9:00 am Empirical Market Design Aditya Bhave, University of Chicago Eric Budish, University of Chicago Primary-Market Auctions for Event Tickets: Eliminating the Rents of "Bob the Broker" Atila Abdulkadiroglu, Duke University Nikhil Agarwal, Harvard University Parag Pathak, MIT and NBER Centralized vs. Decentralized School Assignment: Evidence from NY 10:20 am Break 10:40 am Matching Markets Qingmin Liu, Columbia University Marek Pycia, University of California at Los Angeles Ordinal Efficiency, Fairness and Incentives in Large Markets Scott Duke Kominers, University of Chicago Tayfun Sonmez, Boston College Designing for Diversity in Matching 12:00 pm Lunch 1:00 pm New Frontiers Elisa Celis, University of Washington Gregory Lewis, Harvard University and NBER Markus Mobius, Iowa State University and NBER Hamid Nazerzadeh, University of Southern California Buy-it-Now or Take-a-Chance: Price Discrimination through Randomized Auctions Michael Kearns, University of Pennsylvania Mallesh Pai, University of Pennsylvania Aaron Roth, University of Pennsylvania Jonathan Ullman, Harvard University Mechanism Design in Large Games: Incentives and Privacy David Rothschild, Microsoft Research David Pennock, Microsoft Research The Extent of Price Misalignment in Prediction Markets 3:00 pm Adjourn