Daniel Martin
Daniel Martin

Assistant Professor of Managerial Economics & Decision Sciences

Print Overview

Daniel Martin is an Assistant Professor in the Managerial Economics and Decision Sciences (MEDS) department at Kellogg.  He is a behavioral and experimental economist who studies the processing and disclosure of information.  For example, he investigates why firms do not voluntarily and clearly disclose information about product quality and why consumers do not pay full attention to information about prices or product quality.  His research has appeared in the top journals of the American Economic Association, Royal Economic Society, and Harvard Kennedy School.  Before receiving a PhD in Economics from New York University, he was the co-founder of a small business, which is now one of the leading providers of IT services to small and medium-sized businesses in the Carolinas.

Professor Martin teaches Business Analytics II, a class on multivariate regression techniques, in the core curriculum of the MBA program.  Since arriving at Kellogg, he has received six Kellogg Impact Awards from the Kellogg Student Association.  He also teaches a PhD class on behavioral economics.

Areas of Expertise
Behavioral Economics
Economic Theory
Experimental Economics
Industrial Organization Economics
Information Economics
Pricing Strategy

Print Vita
PhD, 2013, Economics, New York University
MBA, 2002, University of North Carolina
BA, 1998, Economics, Vanderbilt University

Academic Positions
Assistant Professor, Kellogg School of Management, 2015-present
Assistant Professor, Paris School of Economics, 2013-2015

Other Professional Experience
Co-Founder, WorkSmart Inc., 2001-2009

Print Research
Research Interests

Inattention and Perception

Information Disclosure

Caplin, Andrew, Mark Dean and Daniel Martin. 2011. Search and Satisficing. American Economic Review. 101: 2899-2922.
Caplin, Andrew and Daniel Martin. 2015. A Testable Theory of Imperfect Perception. The Economic Journal. 125: 184-202.
Dean, Mark and Daniel Martin. 2016. Measuring Rationality with the Minimum Cost of Revealed Preference Violations. Review of Economics and Statistics. 98(3): 524-534.
Caplin, Andrew and Daniel Martin. 2016. The Dual-Process Drift Diffusion Model: Evidence from Response Times. Economic Inquiry. 54(2): 1274-1282.
Martin, Daniel. 2017. Strategic Pricing with Rational Inattention to Quality. Games and Economic Behavior. 104: 131-145.
Caplin, Andrew and Daniel Martin. 2017. Defaults and Attention: The Drop Out Effect. Revue Economique. 68(5): 747-755.
Working Papers
Jin, Ginger, Michael Luca and Daniel Martin. 2018. Complex Disclosure.
Jin, Ginger, Michael Luca and Daniel Martin. 2017. Is No News (Perceived As) Bad News? An Experimental Investigation of Information Disclosure.
Caplin, Andrew and Daniel Martin. 2018. Framing as Information Design.
Bouacida, Elias and Daniel Martin. 2017. Predictive Power in Behavioral Welfare Economics.

Print Teaching
Full-Time / Evening & Weekend MBA
Business Analytics II (DECS-431-0)

This core course is equivalent to the course DECS-440 (MMM Business Analytics).

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.

Field Study (DECS-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.

Economic Theory II: Advanced Topics in Game Theory (MECS-550-2)
This course is designed to deeply cover a current research area in game theory that has seen recent, fruitful developments. Besides covering the topic, the course is meant to give students a perspective over an entire subliterature. The student sees how a field developed over time, thinks about other ways it could have developed, and learns what early work in the area influenced followup research. The topic and faculty change periodically. Recent and anticipated future topics include: matching theory and market design; games and interactions in large economies; network economics; and bounded rationality. The topic is one in which the instructor is an expert and has active research interest.

Research in Economics (MECS-560-3)
This course introduces first-year PhD students to the economics research environment. With an emphasis on breadth, and minimal prerequisite knowledge at the graduate level, students are exposed to the process of forming and answering research questions. To implement this goal, the course typically involves a handful of instructors each giving their own perspective on successful approaches to research by highlighting significant recent works in their respective fields of interest.