Peter Klibanoff
Peter Klibanoff

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

Print Overview

Professor Peter Klibanoff joined the Kellogg faculty in 1994 after receiving his PhD in Economics from MIT.

His research interests span a range of topics in economic theory. Some topics of special interest include decision theory, especially issues related to modeling decision making under uncertainty and ambiguity; optimal pricing and regulation; game theory including mechanism design; and asset pricing. His research has appeared in leading journals such as Econometrica, Journal of Economic Theory, Journal of Finance, Theoretical Economics and the Review of Economic Studies.

He teaches competitive strategy and statistics at the MBA level and decision theory at the doctoral level. His MBA statistics textbook (Managerial Statistics: A Case-Based Approach) is published by South-Western Cengage Learning (formerly Thomson South-Western).

Areas of Expertise
Behavioral Economics
Behavioral Finance
Economic Theory
Economics of Uncertainty
Game Theory
Microeconomics
Regulation
Print Vita
Education
PhD, 1994, Economics, Massachusetts Institute of Technology
BA, 1990, Applied Mathematics, Harvard University, Summa Cum Laude

Academic Positions
Associate Professor of Managerial Economics and Decision Sciences, Kellogg School of Management, Northwestern University, 2000-present
Assistant Professor of Managerial Economics and Decision Sciences, Kellogg School of Management, Northwestern University, 1994-2000

 
Print Research
Research Interests
Economic theory, including: decision theory and issues related to modeling decision making under uncertainty and ambiguity; optimal pricing and regulation; game theory; mechanism design; asset pricing; and behavioral economics.

Articles
Baliga, Sandeep, Eran Hanany and Peter Klibanoff. Forthcoming. Polarization and Ambiguity. American Economic Review.
Abdellaoui, Mohammed, Peter Klibanoff and Laetitia Placido. 2014. Experiments on compound risk in relation to simple risk and to ambiguity. Management Science.
Klibanoff, Peter and Michel Poitevin. 2013. A Theory of (De)centralization.
Klibanoff, Peter. 2013. Thoughts on Policy Choice Under Ambiguity. Journal of Institutional and Theoretical Economics. 169(1): 134-138.
Klibanoff, Peter, Massimo Marinacci and Sujoy Mukerji. 2012. On the Smooth Ambiguity Model: A Reply. Econometrica. 80(3): 1303-1321.
Hanany, Eran, Peter Klibanoff and Erez Marom. 2011. Dynamically Consistent Updating of Multiple Prior Beliefs: An Algorithmic Approach. International Journal of Approximate Reasoning. 52(8): 1198-1214.
Klibanoff, Peter, Massimo Marinacci and Sujoy Mukerji. 2011. Definitions of Ambiguous Events and the Smooth Ambiguity Model. Economic Theory. 48(2-3): 399-424.
Klibanoff, Peter and Tapas Kundu. 2010. Monopoly Pricing under a Medicaid-Style Most-Favored-Customer Clause and Its Welfare Implication. B.E. Journal of Economic Analysis & Policy. 10(1 (Contributions)): Article 77.
Hanany, Eran and Peter Klibanoff. 2009. Updating Ambiguity Averse Preferences. B.E. Journal of Theoretical Economics. 9(1 (Advances))
Klibanoff, Peter, Massimo Marinacci and Sujoy Mukerji. 2009. Recursive Smooth Ambiguity Preferences. Journal of Economic Theory. 144: 930-976.
Hanany, Eran and Peter Klibanoff. 2007. Updating Preferences with Multiple Priors. Theoretical Economics. 2(3): 261-298.
Klibanoff, Peter and Emre Ozdenoren. 2007. Subjective Recursive Expected Utility. Economic Theory. 30(1): 49-87.
Klibanoff, Peter, Massimo Marinacci and Sujoy Mukerji. 2005. A Smooth Model of Decision Making under Ambiguity. Econometrica. 73(6): 1849-1892.
Klibanoff, Peter. 2001. Characterizing Uncertainty Aversion through Preference for Mixtures. Social Choice and Welfare. 18(2): 289-301.
Klibanoff, Peter. 2001. Stochastically Independent Randomization and Uncertainty Aversion. Economic Theory. 18(3): 605-620.
Reprinted in:
Uncertainty in Economic Theory: A collection of essays in honor of David Schmeidler's 65th birthday, edited by Itzhak Gilboa, 244-260. Routledge, 2004.
Casadesus-Masanell, Ramon, Peter Klibanoff and Emre Ozdenoren. 2000. Maxmin Expected Utility Over Savage Acts with a Set of Priors. Journal of Economic Theory. 92(1): 35-65.
Casadesus-Masanell, Ramon, Peter Klibanoff and Emre Ozdenoren. 2000. Maxmin Expected Utility Through Statewise Combinations. Economics Letters. 66(1): 49-54.
Ghirardato, Paolo, Peter Klibanoff and Massimo Marinacci. 1998. Additivity with Multiple Priors. Journal of Mathematical Economics. 30(4): 405-420.
Klibanoff, Peter, Owen Lamont and Thierry Wizman. 1998. Investor Reaction to Salient News in Closed-End Country Funds. Journal of Finance. 53(2): 673-699.
Reprinted in:
Behavioral Finance , edited by Hersh Shefrin, Edward Elgar Publishing, 2001.
Klibanoff, Peter and Jonathan Morduch. 1995. Decentralization, Externalities, and Efficiency. Review of Economic Studies. 62(2): 223-247.
Working Papers
Klibanoff, Peter, Sujoy Mukerji and Kyoungwon Seo. 2012. Relevance and Symmetry.
Klibanoff, Peter, Sujoy Mukerji and Kyoungwon Seo. 2012. Relating Preference Symmetry Axioms.
Klibanoff, Peter. 1996. Uncertainty, Decision and Normal Form Games.
Klibanoff, Peter. 1995. Dynamic Choice with Uncertainty Aversion.
Other
Klibanoff, Peter. "Kellogg Statistics Essentials (Online Course).".
Klibanoff, Peter. "Essays on Uncertainty in Economics." PhD Dissertation; Massachusetts Institute of Technology.
Klibanoff, Peter. "Solutions to Review Exercises for A Theory of Incentives in Procurement and Regulation by Jean-Jacques Laffont and Jean Tirole. MIT Press..".
Books
Klibanoff, Peter, Boaz Moselle, Brett Saraniti and Alvaro Sandroni. 2006. Managerial Statistics: A Case-Based Approach. Mason, OH: Cengage Learning (formerly Thomson South-Western).
Cases
Schmedders, Karl, Peter Eso, Peter Klibanoff and Graeme Hunter. 2007. Pedigree vs. Grit: Predicting Mutual Fund Manager Performance. Case 5-407-755 (KEL396).
Schmedders, Karl, Peter Eso, Peter Klibanoff and Graeme Hunter. 2006. Orangia Highways (A). Case 5-106-007(A) (KEL185).
Schmedders, Karl, Peter Eso, Peter Klibanoff and Graeme Hunter. 2006. Orangia Highways (B). Case 5-106-007(B) (KEL186).
Schmedders, Karl, Peter Eso and Peter Klibanoff. Where Art Meets Science: Predicting Movie Grosses..

 
Print Teaching
Teaching Interests
Competitive strategy, managerial statistics, decision theory, microeconomics 
Full-Time / Part-Time MBA
Business Analytics II (DECS-431-0)
This sequel to DECS-430 extends the statistical techniques learned in that course to allow for the exploration of relationships between variables, primarily through multivariate regression. In addition to learning basic regression skills, including modeling and estimation, students will deepen their understanding of hypothesis testing and how to make inferences and predictions from data. Students will also learn new principles such as identification and robustness. The course has an intense focus on managerially relevant applications, cases and interpretations.

Executive MBA
Economics of Competition (MECNX-441-0)
Economics of Competition prepares students to diagnose the determinants of an industry’s structure and formulate rational, competitive strategies for coping with that structure.

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.