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.

He is the recipient of two Kilts Center Fellowships, a True North Communications Inc. Scholarship, and a Fellowship from the Ministry of Science in Austria. Hitsch is a member of the American Economic Association, American Marketing Association, the Econometric Society, and INFORMS.

He earned an undergraduate degree from the University of Vienna in 1995. Hitsch received a master’s degree in economics in 1997 and a master’s degree in economics in 1998, as well as a PhD in economics in 2001 from Yale. He joined the Chicago Booth faculty in 2001.

Hitsch enjoys skiing, cooking, and classical music. He wants his students to learn that “good marketing isn’t fluffy.”

 

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