• Jonathan A. Libgober

    Assistant Professor of Economics, University of Southern California

    Welcome to my website!

    I am a microeconomic theorist studying the acquisition, transmission or dynamics of information. I am particularly focused on the design of optimal policies, and am interested in both pure and applied theory.

    I received my PhD in Economics from Harvard in May 2018. I have been at USC since the start of 2019.

  • Curriculum Vitae

    Contact me for more info.


    (Last update: April 26, 2022)

  • Working Papers

    Comments welcome! Presentation videos linked when available (though may not reflect current versions)

    Coasian Dynamics under Informational Robustness

    with Xiaosheng Mu (Last update: April 2022)

    We propose an approach to study informationally robust dynamic pricing when the seller lacks commitment.

    Learning Underspecified Models 

    with In-Koo Cho (Last update: May 2022)

    A monopolist can ensure an optimal price is used in the long run by designing an algorithm that assumes a linear demand curve, even if demand is quite nonlinear.

    Algorithm Games and Rational Play with Strategic Inference​

    with In-Koo Cho (Last update: November 2021)

    We exhibit an algorithm which ensures that agents play a Bayesian best reply (approximately).

    Learning versus Unlearning: An Experiment on Retractions

    with Duarte Gonçalves and Jack Willis (Last update: October 2021)

    We conduct an experiment on belief updating and document that subjects under-react to information when it is in the form of a retraction.

    Research Registries and the Credibility Crisis: An Empirical and Theoretical Investigation

    with Eliot Abrams and John A. List (Last update: September 2021) R&R @ JEEA

    We empirically study registries, focusing mostly (but not exclusively) on the AEA RCT Registry, and theoretically discuss issues related to incentives behind registration. The Mathematica notebook referenced in the Appendix can be found here.

    Evolutionarily Stable (Mis)specifications: Theory and Applications

    with Kevin He (Last update: August 2021) Presented @ EC '21

    We introduce a selection criterion on behavioral biases in environments with learning, and show that it need not select for a bias-free worldview in some common applications.

    Hypothetical Beliefs Identify Information

    (Last update: May 2021) R&R @ JET

    I demonstrate how to recover a decisionmaker's information structure from posterior beliefs over states, together with posterior beliefs that each signal could be observed. In the process, I make new observations on the geometric structure of information.

    Iterative Weak Learnability and Multi-Class AdaBoost

    with In-Koo Cho and Cheng Ding (Last update: January 2021) Rejected with encouragement to resubmit @ JMLR

    We propose a classification algorithm with generalizes AdaBoost to a multi-class, which requires an intuitive and simple to check condition to be valid.

  • Publications

    I heard it was this or perish...

    False Positives and Transparency


    American Economic Journal: Microeconomics, 2022, 14(2): 478-505.

    Lack of transparency over research methods can induce bias. But the incentive to de-bias may lead to more informative experiments.


    The model introduced is one of costly communication with partial (sender) commitment.

    Informational Robustness in Intertemporal Pricing

    (with Xiaosheng Mu)

    Review of Economic Studies, 2021, 88(3): 1224-1252.

    Constant price paths deliver the optimal profit guarantee when a seller does not know how buyers learn about a product.


    Formally, this paper introduces an informationally robust approach into the dynamic pricing literature.

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