Daniel Martin
Daniel Martin

MANAGERIAL ECONOMICS & DECISION SCIENCES
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 studies information economics, including why firms do not voluntarily disclose information about product quality and why consumers only pay partial attention to information about product quality.  His research has appeared in the top journals of the American Economic Association and the Royal Economic Society.  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 in the Carolinas.



Print Vita
Education
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
Visiting Assistant Professor, Kellogg School of Management, 2014-2015
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



Articles
Martin, Daniel and Mark Dean. Forthcoming. Measuring Rationality with the Minimum Cost of Revealed Preference Violations. Review of Economics and Statistics.
Caplin, Andrew and Daniel Martin. 2015. A Testable Theory of Imperfect Perception. The Economic Journal. 125: 184-202.
Caplin, Andrew, Mark Dean and Daniel Martin. 2011. Search and Satisficing. American Economic Review. 101: 2899-2922.
Working Papers
Jin, Ginger, Michael Luca and Daniel Martin. 2015. Is No News (Perceived As) Bad News? An Experimental Investigation of Information Disclosure.
Martin, Daniel. 2015. Strategic Pricing with Rational Inattention to Quality.
Caplin, Andrew and Daniel Martin. 2015. The Dual-Process Drift Diffusion Model: Evidence from Response Times.
Caplin, Andrew and Daniel Martin. 2015. Defaults and Attention: The Drop Out Effect.
Caplin, Andrew and Daniel Martin. 2015. Framing Effects and Optimization.

 
Print Teaching
Full-Time / Part-Time 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.