NORTHWESTERN UNIVERSITY
  • About Kellogg
  • Programs
  • Faculty & Research
  • Global
  • News & Events
  • Support Kellogg
Kyoungwon Seo
Kyoungwon Seo

MANAGERIAL ECONOMICS & DECISION SCIENCES
Assistant Professor of Managerial Economics & Decision Sciences

Print Overview
Kyoungwon Seo is an Assistant Professor of Managerial Economics & Decision Sciences at Kellogg School of Management, Northwestern University. He has completed his Ph.D. in Economics at the University of Rochester in 2008. His research interests involve economic theory such as decision theory and game theory. He is currently working on decision making and updating under uncertainty and ambiguity. He teaches courses in statistics at the MBA level.

Areas of Expertise
Economic Theory
Economics of Uncertainty
Game Theory
Microeconomics
Print Vita
Education
PhD, 2008 (expected), Economics, Arts & Sciences, University of Rochester
MA, 2002, Economics, Seoul National University
BA, 1998, Economics, Seoul National University

 
Print Research
Research Interests
Decision theory, game theory

Articles
Epstein, Larry and Kyoungwon Seo. Forthcoming. Symmetry of Evidence without Evidence of Symmetry. Theoretical Economics.
Epstein, Larry and Kyoungwon Seo. 2009. Subjective States: A More Robust Model. Games and Economic Behavior. 67(2): 408-427.
Seo, Kyoungwon. 2009. Ambiguity and Second-Order Belief. Econometrica. 77(5): 1575-1605.
Epstein, Larry, Massimo Marinacci and Kyoungwon Seo. 2007. Coarse Contingencies and Ambiguity. Theoretical Economics. 2(4): 355-394.
Working Papers
Klibanoff, Peter, Kyoungwon Seo. 2011. Relevance and Symmetry.
AbstractLink
Epstein, Larry and Kyoungwon Seo. A de Finetti theorem for capacities: ambiguity about correlation.

 
Print Teaching
Teaching Interests
Statistics
Full-Time / Part-Time MBA
Statistical Methods For Management Decisions (DECS-434-0)

This course counts toward the following majors: Decision Sciences.

This sequel to DECS-433 extends the statistical techniques learned in that course to allow for the exploration of relationships between variables. Topics include one- and two-population hypothesis testing, correlation, simple and multiple regression analysis, and qualitative variables. The course also covers applications of the material and a number of case studies. Extensive use of spreadsheet statistical analysis software is required.

Doctoral
Decision Theory (MECS-462-0)
This PhD-level course on decision theory focuses on axiomatic theories of individual decision making under risk and uncertainty. The course briefly explores utility theory under certainty and the notion of preferences and their representation, then progresses to the classic theories of decision under risk and uncertainty: von Neumann and Morgenstern, Anscombe and Aumann, and Savage. This lasts roughly half the course and constitutes a basic grounding in the subject. From there the course explores topics that expand on the classical work and are nearer to the current research frontier. These topics may include Allais Paradox, Prospect Theory and Machina's approach; Ellsberg's paradox, uncertainty aversion, and Gilboa and Schmeidler representations; dynamics - Bayesian updating, consistency, preferences over the timing of the resolution of risk/uncertainty; and notions of belief and probability in decision making.