Weijie Zhong

Weijie Zhong

PhD Candidate
Columbia University
Department of Economics

I will be available for interviews at the 2019 ASSA meetings

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Columbia University, Department of Economics
420 West 118 Street
New York, NY, 10025

[email protected]

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Research fields:
Microeconomic Theory

Curriculum Vitae

Job Market Paper

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Yeon-Koo Che
[email protected]

Navin Kartik
[email protected]

Qingmin Liu
[email protected]

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Job Market Paper

Published papers

Working Papers by topics

Dynamic Learning

Information Design

Decentralized Market

  • Indirect Information Measure and Dynamic Learning, Jun 2017, ArXiv:1809.00697

    "Under indirect information measure from sequential cost minimization, Poisson learning is the optimal dynamic learning strategy"

    I study the robust predictions of optimal learning dynamics in information acquisition problems where the measure of signal informativeness is an indirect measure from sequential cost minimization. I first show that an indirect information measure is supported by sequential cost minimization iff it satisfies: 1) monotonicity in Blackwell order, 2) sub-additivity in compound experiments and 3) linearity in mixing with no information. In a dynamic learning problem, if the cost of information depend on an indirect information measure and delay cost is fixed, then the optimal solution involves direct Poisson signals: arrival of signals directly suggest the optimal actions, and non-arrival of signal provides no information.

  • Time Preference and Information Acquisition, Dec 2017, ArXiv:1809.05120

    "Poisson learning creates most dispersed decision time distribution"

    I consider the sequential implementation of a target information structure. I characterize the set of decision time distributions induced by all signal processes that satisfies a per-period learning capacity constraint. The maximal and minimal elements of the set by mean-preserving spread order are deterministic distribution and exponential distribution. The result implies that when time preference is risk loving (e.g. standard or hyperbolic discounting), Poisson signal is optimal since it induces the most risky exponential decision time distribution. When time preference is risk neutral (e.g. constant delay cost), all signal processes are equally optimal.

  • Selling Information, Mar 2016, ArXiv:1809.06770, Slide

    "Monopolistic seller of information should design a rich menu to screen buyers holding private information."

    I consider the monopolistic pricing of informational good. A buyer's willingness to pay for information is from inferring the unknown payoffs of actions in decision making. A monopolistic seller and the buyer each observes a private signal about the payoffs. The seller's signal is binary and she can commit to sell any statistical experiment of her signal to the buyer. Assuming that buyer's decision problem involves rich actions, I characterize the profit maximizing menu. It contains a continuum of experiments, each containing different amount of information. I also find a complementarity between buyer's private information and information provision: when buyer's private signal is more informative, the optimal menu contains more informative experiments.

  • Lemonade from Lemons: Information Design and Adverse Selection (with Navin Kartik), In preparation

    "A characterization of payoffs implementable through information design in a bargaining game."

    Consider a canonical bargaining problem: a buyer makes a take-it-or-leave-it offer to a seller for a single object. The two parties’ values may be interdependent. We study the set of payoff vectors that can be implemented (in sequential equilibria) using joint information design. We establish, in part constructively, that the set is a triangle characterized by simple feasibility and individual-rationality constraints. We also investigate what is implementable only using information structures in which the seller is more informed than the buyer, or more generally, under a “no signaling” equilibrium restriction. We show that there is then no loss in providing the buyer with no information and only varying the seller’s information; i.e., familiar adverse-selection structures emerge. Our model encompasses monopoly pricing, for which our results augment those of Bergemann, Brooks, and Morris (2015) and Roesler and Szentes (2017).

  • Rating Guided Markets (with Yeon-Koo Che and Teddy Kim), In preparation

    "In a decentralized market, rating-guided search involves informational externality and endogenously creates statistical discrimination."

    We consider a decentralized market where buyers search to trade with sellers of unknown quality. Each buyer targets sellers based on their ratings — a coarse summary (e.g. average) of the seller’s quality collected from previous transactions involving these sellers. We study the implication of a novel informational externality in the rating-guided market: the informational content of the sellers’ ratings is endogenous, depending on the frequency of their trading, but buyers make trading decisions not taking into account their informational effects. First, we show that an improvement in the ratings technology may exacerbate the informational externality, and hence can be welfare-worsening. Second, we extend the baseline model to allow for two ex ante identical demographic groups, and show that the informational externality endogenously generates statistical discrimination. In a stable equilibrium, highly-rated sellers (or workers) in the advantaged group receive more attention than highly-rated sellers (or workers) in the disadvantaged group, leading to discrimination against the latter group in a self-fulfilling fashion. Our analysis implies that an affirmative action policy restores equality, but only in the short run, as the non-discriminative equilibrium is unstable.

  • Short Notes

    Some useful technical results & interesting preliminary analyses.


    Download my Curriculum Vitae here.


    Columbia University


    Professor Yeon-Koo Che
    Columbia University
    (212) 854-8276
    [email protected]

    Professor Navin Kartik
    Columbia University
    (212) 854-3296
    [email protected]

    Professor Qingmin Liu
    Columbia University
    (212) 854-2512
    [email protected]

    Tsinghua University


    Download my Curriculum Vitae here.

    Professional Activities


    Conferences & Workshop Presentations

    Research Experiences

    Research Assistantships


    Download my Curriculum Vitae here.

    Teaching Fellow