JU HU UNIVERSITY OF PENNSYLVANIA

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JU HU
<https://economics.sas.upenn.edu/graduate-program/candidates/ju-hu>
<juhu1@sas.upenn.edu>
UNIVERSITY OF PENNSYLVANIA
Placement Director: Iourii Manovskii
Placement Director: Andrew Postlewaite
Graduate Student Coordinator: Kelly Quinn
MANOVSKI@ ECON.UPENN.EDU
APOSTLEW@ECON.UPENN.EDU
KQUINN @ ECON.UPENN.EDU
Office Contact Information
328 McNeil Building
3718 Locust Walk
Philadelphia, PA 19104
Cell Phone: 267-909-1250
Personal Information:
Citizenship: China
Date of Birth: April 02, 1985
Gender: Male
Undergraduate Studies:
B.A., Finance, Fudan University, Shanghai, China, 2007
Masters Level Work:
M.A., Finance, Fudan University, Shanghai, China, 2010
Graduate Studies:
University of Pennsylvania, 2010 to present
Thesis Title: “Essays on Reputations and Dynamic Games”
Expected Completion Date: May 2016
Thesis Committee and References:
Professor George J. Mailath (Advisor)
432 McNeil Building
3718 Locust Walk
Philadelphia, PA 19104
gmailath@econ.upenn.edu
215-898-7908
Professor Rakesh V. Vohra
451 McNeil Building
3718 Locust Walk
Philadelphia, PA 19104
rvohra@seas.upenn.edu
215-898-6777
Professor Yuichi Yamamoto
457 McNeil Building
3718 Locust Walk
Philadelphia, PA 19104
yyam@sas.upenn.edu
215-898-8761
Teaching and Research Fields:
Microeconomic Theory, Game Theory, Dynamic Games
215-898-6880
215-898-7350
215-898-5691
Teaching Experience:
Fall, 2011
Fall, 2012
Spring, 2012, 2013
Spring, 2015
Summer, 2012, 2013,
2014
Econ 701 Microeconomic Theory I (graduate level), University of
Pennsylvania, Teaching Assistant for Prof. Andrew Postlewaite and
Steven Matthews
Econ 701 Microeconomic Theory I (graduate level), University of
Pennsylvania, Teaching Assistant for Prof. Andrew Postlewaite and
Mallesh Pai
Econ 212 Game Theory, University of Pennsylvania, Teaching Assistant
for Prof. Tymofiy Mylovanov
Econ 212 Game Theory, University of Pennsylvania, Teaching Assistant
for Prof. Yuichi Yamamoto
Econ 897 Graduate Math Camp , University of Pennsylvania, Instructor
Professional Activities:
Presentations:
2012-2015
Penn Micro Theory Lunch Club, University of Pennsylvania
2015
Micro Theory Seminar, University of Pennsylvania
Referee Activities:
Theoretic Economics, International Economic Review
Other:
2013-2014
Co-organizer, University of Pennsylvania Micro Theory Lunch Club
Honors, Scholarships, and Fellowships:
2011-2013
Xinmei Zhang Fellowship, School of Arts and Science, University of
Pennsylvania
2013-2014
Sidney Weintraub Memorial Fellowship, University of Pennsylvania
Publications:
“Reputation in the Presence of Noisy Exogenous Learning”, Journal of Economic Theory, 2014, Volume
153, 64-73.
Research Paper:
“Biased Learning and Permanent Reputation” (Job Market Paper)
Abstract: This paper studies reputation effects between a long-lived seller and different short-lived
buyers where the short-lived buyers do not know how long the seller has been in business. Departing
from standard assumptions in repeated games, this paper assumes that buyers enter the market at random
times and only observe a coarse public signal upon entry. The signal measures the difference between
the number of good and bad outcomes in a biased way: a good outcome is more likely to increase the
signal than a bad outcome to decrease it. The seller has a short-run incentive to exert low effort, but
makes high profits if it were possible to commit to high effort.
First, we show if the bias is large, in the complete information game, always exerting low effort is the
unique equilibrium. We then introduce incomplete information. There are two types of the seller. One is
a commitment type who always exerts high effort and the other is a normal type who behaves
strategically to maximize long-run payoff. If there is small but positive chance that the seller is a
commitment type, in any equilibrium, the normal seller must exert high effort at some signals to build up
his reputation. Moreover, the seller builds up his reputation only to milk it. In any equilibrium, once the
seller builds up reputation through reaching a high enough signal, the seller then exploits by exerting
low effort. Because all buyers only have limited information, they are unable to distinguish the two types
of the seller no matter how long the game has been played. Consequently, the incentives of building
reputation never disappear in the long-run.
“Reputation in the Presence of Noisy Exogenous Learning”
Abstract: This paper studies the reputation effect in which a long-lived player faces a sequence of
uninformed short-lived players and the uninformed players receive informative but noisy exogenous
signals about the type of the long-lived player. We provide an explicit lower bound on all Nash
equilibria payoffs of the long-lived player. The lower bound shows when the exogenous signals are
sufficiently noisy and the long-lived player is patient, he can be assured of a payoff strictly higher than
his minmax payoff.
“Social Learning and Market Experimentation”
Abstract: This paper studies optimal dynamic monopoly pricing when a monopolist sells a product with
unknown quality to a sequence of short-lived buyers who have private information about the quality.
Because past prices and buyers’ purchase behavior convey information about private signals, they jointly
determine the public belief about the quality of the monopolist’s product. The monopolist’s is essentially
doing experimentation in the market because every price charged generates not only current period profit
but also additional information about the quality. We focus on information structures with a continuum
of signals. Under a mild regularity condition on information structures, we show in equilibrium, the
optimal price is an increasing function of the public beliefs. In addition, we fully characterize
information cascade sets in terms of information structure. We find the standard characterization in
terms of boundedness of information structure in the social learning literature no longer holds in the
presence of a monopoly. In fact, whether herding occurs or not depends more on the values of the
conditional densities of the signals at the lowest signal.
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