Günter J. Hitsch
Günter J. Hitsch studies quantitative marketing and industrial organization. His research interests include dynamic models of firm and consumer decision-making with a specific focus on dynamic advertising, pricing, sequential experimentation, and consumer discount factor estimation. His recent research focuses on the application and development of ideas from the machine learning and causal inference literatures in marketing and industrial organization, including customer-targeting and optimal pricing. His research also focuses on understanding the structure of the U.S. retail industry, with a specific focus on pricing and promotion setting.
Hitsch's research has been widely published and he has been invited to give talks at the University of California at Berkeley, Harvard University, Stanford University, Columbia University, Yale University, Northwestern University, and the Massachusetts Institute of Technology.
Learn More about Günter J. Hitsch »