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%.
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