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
||Applied Theory Workshop
REVISION: An Economic Analysis of the Bitcoin Payment System
Unlike traditional payment systems, Bitcoin has no owner and is governed by a computer protocol. This paper models Bitcoin as a platform that intermediates between users and computer servers (“miners”) which operate the Bitcoin payment system (BPS), and studies the novel market design of this owner-less platform. We find that the BPS can eliminate inefficiencies due to market power, but incurs other costs. Having fixed transaction processing capacity, the BPS experiences service delays which motivate users to pay for service priority. Free entry implies that miners cannot profitably affect the level of fees paid by users. The paper derives closed form formulas of the fees and waiting times and studies their properties; compares pricing under the BPS to that under a traditional payment system operated by a profit maximizing firm; and suggests protocol design modification to enhance the platform’s efficiency. The appendix describes and explains the main attributes of Bitcoin and the ...
REVISION: The Importance of Memory for Price Discovery in Decentralized Markets
We study the dynamics of price discovery in decentralized two-sided markets. There exist memoryless dynamics that converge to the core in which agents' actions depend only on their current payoff. However, we show that for any such dynamic the convergence time can grow exponentially in the population size. We present a natural dynamic in which a player's reservation value provides a summary of her past information and show that this dynamic converges to the core in polynomial time. In addition, the strategies implied by the dynamic are incentive compatible in a broad class of markets.
REVISION: The Cutoff Structure of Top Trading Cycles in School Choice
This paper develops a tractable theoretical framework for the Top Trading Cycles (TTC) mechanism for school choice that allows quantifying welfare and optimizing policy decisions. We compute welfare for TTC and Deferred Acceptance (DA) under different priority structures, and find that the choice of priorities can have larger welfare implications than the choice of mechanism. We solve for the welfare-maximizing distributions of school quality for parametrized economies, and find that optimal investment decisions can be very different under TTC and DA.
Our framework relies on a novel characterization of the TTC assignment in terms of a cutoff for each pair of schools. These cutoffs parallel prices in competitive equilibrium, with students' priorities serving the role of endowments. We show that these cutoffs can be computed directly from the distribution of preferences and priorities in a continuum model, and derive closed-form solutions and comparative statics for parameterized ...
REVISION: A Supply and Demand Framework for Two-Sided Matching Markets
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
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 ...