Donald Dale
Clinical Professor of Managerial Economics and Decision Sciences
Associate Chair of the Managerial Economics and Decision Sciences Department
Don Dale is Clinical Professor of Managerial Economics & Decision Sciences at the Kellogg School of Management at Northwestern University, and Associate Chair of that department. He holds a BS in economics and a BA in physics from the University of Delaware, and a PhD in economics from Princeton University. Prior to joining Kellogg in 2015, Don was a tenured professor of economics and finance at Muhlenberg College in Allentown PA. Don has also held a position at the Woodrow Wilson School of Public and International Affairs at Princeton University. Don teaches a portfolio of courses in microeconomic theory, data analytics, and game theory. His research interests are primarily experimental in methodology, and focus on questions of responses to incentives, charitable giving, and gambling behavior.
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Ph.D., 2000, Economics, Princeton University
M.A., 1993, Economics, Princeton University
B.S., 1990, Economics, University of Delaware
B.A., 1990, Physics, University of Delaware -
Associate Professor, Economics and Finance, Muhlenberg College, 2006-2015
Assistant Professor of Economics, Economics, Muhlenberg College, 2000-2006
Lecturer, Economics, Woodrow Wilson School of Public and International Affairs, Princeton University, 1994-2000
Adjunct Professor, University of Delaware, 1991 -
Sidney Levy Teaching Award, AY 22-23
Chairs Core Course Teaching Award
L.G. Lavengood Outstanding Professor of the Year Award, 2020
Kellogg Impact Award, 2018
Chairs' Core Course Teaching Award, 2017-2018
Kellogg Impact Award, Winter 2016
Woodrow Wilson School Teaching Excellence Award, Princeton University, 1996
Princeton University Fellowship, Princeton University, 1990-1994
Business for Scientists and Engineers
For practitioners and academics in science and engineering, this highly focused program provides a solid grounding in business concepts, industry-specific tools and practical frameworks for developing the business acumen you need to advance your life’s work.
The PHYSICIAN CEO™ Program
Game Theory and Strategic Decisions (MECNM-452-0)
Field Study (MECN-498-0)
Field Studies include those opportunities outside of the regular curriculum in which a student is working with an outside company or non-profit organization to address a real-world business challenge for course credit under the oversight of a faculty member.
Game Theory and Strategic Decisions (MECN-452-0)
How does a decision-maker make good decisions in strategic situations - situations where outcomes depend on the choices of other purposeful individuals as well as one's own? Participants in this course will gain an understanding of how to use the concepts and tools of Game Theory to guide their decisions. Topics include backward induction and subgame perfection, collusion and competition, mixed strategies, credibility and commitment, negotiation and bargaining, information asymmetry, market entry, and bidding strategies in auctions. This course makes extensive use of individual and group experiments and discussion.
Microeconomic Analysis (MECN-430-0)
1Ys: This course is either waived during the admissions process or completed during the Summer term. Among the topics this core course addresses are economic analysis and optimal decisions, consumer choice and the demand for products, production functions and cost curves, market structures and strategic interactions, and pricing and non-price concepts. Cases and problems are used to understand economic tools and their potential for solving real-world problems.
Business Analytics (DECSM-431-0)
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 managerial relevant applications, cases and interpretations.
