Jonathan A. Libgober
Assistant Professor of Economics, University of Southern California
Welcome to my website!
I am an economist studying information economics and mechanism design. I am interested in both pure theory and applied questions.
I received my PhD in Economics from Harvard in May 2018. I have been at USC since the start of 2019.
Drew Fudenberg, Eric Maskin, Jerry Green, Ben Golub
Contact me for more info. (Last update: March 29, 2019)
Information Economics, Pure and Applied
I am a theorist who settings where the acquisition, transmission or dynamics of information play a major role. I am particularly interested in questions related to the design of optimal policies in these situations.
I have studied pricing with consumer learning, researcher incentives, and biases in dynamic belief updating.
Informational Robustness in Intertemporal Pricing
with Xiaosheng Mu (January 2019) R&R @ Review of Economic Studies
Constant price paths deliver the optimal profit guarantee when a seller does not know how buyers learn about a product.
False Positives and Transparency
Lack of transparency over research methods can induce biased claims. But it also creates an incentive to counteract the de-biasing of that research.
Available upon request; to be posted soon
A principal wants to choose a project and allocate it competitively. In some cases, the ability to randomize across participants (but not across projects) is necessary for competition to be beneficial.
Works In Progress
Email me if you have any questions
Contracting with Experiment Choice: Interpreting Failure
A principal hires an agent to develop a new technology. The uncertainty about the productivity of the relationship creates a novel incentive conflict: the agent may prefer to keep changing projects in case failure causes the principal to become pessimistic too early.
The Informed Principal with Evolving Private Information
A principal with a privately observed state designs a mechanism facing an agent with serial correlation. The interaction of the principal's and the agent's private information yields distortions away from first best, and in certain settings both are necessary.
Thesis Title: Information and Learning in Mechanism Design
M.A. awarded 2014, field exams in Microeconomic Theory and Industrial Organization
University of Chicago
S.B. in Mathematics (Departmental Honors, Paul R. Cohen award for top 5 record among seniors)
A.B. in Economics (Departmental Honors, David S. Hu award for coursework and thesis)
A.B. in Statistics
Phi Beta Kappa