Faculty & Research

Jacob Leshno

Jacob Leshno

Assistant Professor of Economics

Address :
5807 South Woodlawn Avenue
Chicago, IL 60637

Jacob Leshno is an Assistant Professor of Economics at the University of Chicago Booth School of Business. Professor Leshno uses game theory, applied mathematics and microeconomic theory to study allocation mechanism and the design of marketplaces. His research looks into the design of school choice procedures that guide the allocation of students to schools, the assignment of patients to nursing homes, and the design of decentralized cryptocurrencies.

Before joining Chicago Booth, Jacob Leshno was an Assistant Professor in the Decision, Risk & Operations group in the Graduate School of Business, Columbia University. He spent a year as a post-doc researcher in Microsoft Research New England, and previously worked at Yahoo! and IBM. Jacob holds a PhD in economics from Harvard University, completed under the supervision of Prof. Alvin Roth. He holds a M.Sc. and B.Sc. in pure math from Tel Aviv University.


2018 - 2019 Course Schedule

Number Name Quarter
42001 Competitive Strategy 2019 (Spring)

REVISION: The Cutoff Structure of Top Trading Cycles in School Choice
Date Posted: Apr  20, 2018
The prominent Top Trading Cycles (TTC) mechanism has attractive properties for school choice, as it is strategy-proof, Pareto efficient, and allows school boards to guide the assignment by specifying priorities. However, the common combinatorial description of TTC does not help explain the relationship between student priorities and their eventual assignment. We show that the TTC assignment can be described by admission cutoffs for each pair of schools. These cutoffs parallel prices in competitive equilibrium, with students' priorities serving the role of endowments. In a continuum model these cutoffs can be computed directly from the distribution of preferences and priorities, providing a framework that can be used to evaluate policy choices. We provide closed form solutions for the assignment under a family of distributions, and derive comparative statics. As an application of the model we solve for the welfare maximizing distribution of school quality, and find that a more ...

New: Efficient Price Discovery and Information in the Decentralized Assignment Game
Date Posted: Oct  24, 2017
We study the dynamics of price discovery in decentralized assignment games. There exist naive mechanisms that converge to the core in which agents' actions depend only on their current payoff. However, we show that for any such mechanism the convergence time can grow exponentially in the population size. We present a natural mechanism in which a player's reservation value provides a summary of her past information, and show that this mechanism converges to the core in polynomial time. In addition, the strategies implied by the mechanism are incentive compatible in a broad class of markets.

REVISION: Monopoly Without a Monopolist: An Economic Analysis of the Bitcoin Payment System
Date Posted: Oct  18, 2017
Owned by nobody and controlled by an almost immutable protocol, the Bitcoin payment system is a platform with two main constituencies: users and profit seeking miners who maintain the system's infrastructure. The paper seeks to understand the economics of the system: How does the system raise revenue to pay for its infrastructure? How are usage fees determined? How much infrastructure is deployed? What are the implications of changing parameters in the protocol? A simplified economic model that captures the system's properties answers these questions. Transaction fees and infrastructure level are determined in an equilibrium of a congestion queueing game derived from the system's limited throughput. The system eliminates dead-weight loss from monopoly, but introduces other inefficiencies and requires congestion to raise revenue and fund infrastructure. We explore the future potential of such systems and provide design suggestions.

REVISION: A Supply and Demand Framework for Two-Sided Matching Markets
Date Posted: Sep  26, 2017
This paper develops a price-theoretic framework for matching markets with heterogeneous preferences. The model departs from the standard Gale and Shapley (1962) model by assuming that a finite number of agents on one side (colleges or firms) are matched to a continuum mass of agents on the other side (students or workers). We show that stable matchings correspond to solutions of supply and demand equations, with the selectivity of each college playing a role similar to prices. We apply the model to an analysis of how competition induced by school choice gives schools incentives to invest in different aspects of quality. As another application, we characterize the asymptotics of school choice mechanisms.

New: Dynamic Matching in Overloaded Waiting Lists
Date Posted: May  13, 2017
This paper studies the problem of a benevolent planner who wishes to allocate stochastically arriving items to agents in an overloaded waiting list. Agents arrive sequentially over time and have privately known preferences. In practice, mechanisms commonly allow agents to choose among items with corresponding expected waiting times, thereby letting expected waiting times serve the role of prices. In these mechanisms, an agent expecting a long wait for his preferred item will choose a mismatched item, allowing for a shorter wait for himself and forcing other agents in the queue to wait longer. This transfer of wait time is individually optimal but socially inefficient. Even if average waiting times for items are equal, the randomness in the system causes fluctuations in the expected waits. When the fluctuations are large enough, agents make socially inefficient choices. This paper uses a dynamic stochastic model to quantify the impact of these fluctuations on welfare and to derive ...