Presenters

Andrei Zeleneev

Yifei Zhang

Lichen Zhang

I am an assistant professor of economics at the University of Hong Kong. I received my Ph.D. from the University of Minnesota in 2020. I am interested in quantitative macroeconomics that combines data, theory, and policy.

David Zhang

David is a fifth year PhD student at Harvard Business School

Mengxi Zhang

I am a postdoctoral researcher at Institute for Microeconomics & Hausdorff Center for Mathematics, University of Bonn. I received my PhD in Economics from Boston University.

My primary research interests are in the areas of Applied Microeconomic Theory and Mechanism Design.

Nan Zhao

I am a Ph.D. candidate in Economics at Boston University. My main research interest is microeconomic theory with a focus on dynamic contracts. My work is primarily concerned with incentive provision in settings of dynamic moral hazard and persistent private information.

Jun Zhao

My name is Jun Zhao (I also go by Bean). I am currently a Ph.D. candidate in Economics at Vanderbilt University. I am currently on the job market in 2020-2021. I will present my Job Market Paper "Campaign Spending in Senate Elections: A Structural Analysis of a Two-Stage Election with Endogenous Candidate Entry", in which I develop a two-stage contest model with entry and also a model for voters to study the effects of campaign spending on electoral outcomes given endogenous candidate entry in the U.S. Senate elections.

Ling Zhong

Junjie Zhou

working on projects related to social networks and digital economy.

Wu Zhu

I am a fifth-year Ph.D Student in Economics at the University of Pennsylvania and will be available for interviews at the 2020/2021 job market. My research spans several fields: Macroeconomics, Finance, Machine Learning, Networks, and the Chinese Economy. However, it shares a common theme: the use of big data to understand the role of networks in investor behavior, firm decision making, asset pricing, the business cycle, and systemic risk.

Under this theme, my work can be divided into three branches:
i) Innovation network and its implication on business cycle, asset pricing, and investment;
ii) Equity-holding network and its implication on corporate finance, governance, and monetary policy;
iii) Machine learning.