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Strategy

Associate Professor of Strategy

Amanda Starc

Amanda Starc, Ph.D., is an Associate Professor of Strategy at the Kellogg School of Management and a Faculty Research Fellow at the National Bureau of Economic Research (NBER). She received her BA in Economics from Case Western Reserve University, and her PhD in Business Economics from Harvard University. Dr. Starc’s research agenda sits at the intersection of industrial organization and health economics. Her research spans three main themes. First, she studies the fundamental economic question of what health insurance covers and how it is priced. Second, she studies how information shapes consumer demand for both insurance and health care. Finally, she studies the efficacy of market mechanisms in allocating goods and services in health care markets. 

About Amanda
Research interests
  • Health Economics and Industrial Organization
Teaching interests
  • Health Economics
  • Firm Strategy
  • Doctor of Philosophy, 2011, Business Economics, Harvard University
    Bachelor of Arts, 2006, Economics, Case Western Reserve University, Summa Cum Laude
  • Associate Professor of Strategy, Kellogg School of Management, Northwestern University, 2016-present
    Assistant Professor of Health Care Management, Wharton School, University of Pennsylvania, 2011-2016
  • Assistant Professor, University of Pennsylvania, 2011-2016
  • NSF Grant for "Mortality Effects of Health Insurance Networks and Providers"
    NIHCM Research Award, National Institute of Health Care Management
  • Associate Editor, RAND Journal of Economics, 2023
    Co-Editor, American Economic Journal: Economic Policy, 2024
    Associate Editor, Journal of Political Economy: Microeconomics, 2022
    Associate Editor, Journal of Health Economics, 2019

Using Analytics to Create and Capture Value in Healthcare (HCAKX-941-0)

This course is for managers who want to better understand empirical arguments in the healthcare industry. Students will become familiar with basic tools of modern data science through hands-on experience and will learn how to use analytics and data to address decisions faced by healthcare firms. Data-driven analyses require going beyond statistically significant relationships to assess cause and effect. This course extends regression analysis to answer causal questions.