DEPARTMENT OF INDUSTRIAL AND
ENTERPRISE SYSTEMS ENGINEERING
GE/IE 590 SEMINAR
Constrained Optimization Approaches to
Estimation of Structural Models -- An Overview
Assistant Professor Che-Lin Su
University of Chicago Booth School of Business
Chicago, IL
Abstract
Maximum likelihood estimation of structural models is often viewed as computationally difficult. This
impression is due to a focus on the Nested Fixed-Point approach. We present a constrained optimization
approach to the general problem and demonstrate the use of this approach to estimate discrete choice
models such as single-agent sequential decision models, random-coefficient demand systems, and games
of incomplete information.
Biography
Che-Lin Su is an Assistant Professor of Operations Management at the University of Chicago Booth
School of Business. He is interested in developing and applying computational methods to study business
applications that arise in operations, economics, and quantitative marketing. His current research topics
include empirical estimation of economics models, incentive problems with applications to executive
compensation design and nonlinear pricing. Before joining the Chicago Booth faculty in 2008, he was a
postdoctoral research fellow at the Center for Mathematical Studies in Economics and Management
Science at the Kellogg School of Management at Northwestern University and the NBER in Cambridge,
Massachusetts. He received his Ph.D in Management Science and Engineering from Stanford University
in 2005.
Location:
Date:
Time:
101 Transportation Building
Thursday, September 24, 2009
4-5 p.m.