Jann Spiess

Research Statement

Jann works on integrating techniques and insights from machine learning into the econometric toolbox. His research brings together microeconometric methods, statistical decision theory, and mechanism design to clarify the use of flexible prediction algorithms in causal inference and data-driven decision-making. He is particularly interested in the role of human and machine decisions in replicable and robust inferences from big data.

Bio

Jann holds a PhD in economics from Harvard University. Previously, Jann obtained a master’s degree in public policy from the Harvard Kennedy School. His background is in mathematics with a focus on probability theory and combinatorics, which he studied at the University of Cambridge (Part III of the Mathematical Tripos) and the Technical University of Munich. Jann also studied and worked in Hangzhou, China and Ouagadougou, Burkina Faso.

Academic Degrees

• PhD, Economics, Harvard University, 2018
• AM, Economics, Harvard University, 2015
• MPP, Public Policy, Harvard University, 2013
• MASt, Mathematics, University of Cambridge, 2011
• BSc, Mathematics, Technical University of Munich, 2010

Awards and Honors

• David A. Wells Prize for best dissertation, Department of Economics, Harvard University, 2018
• Restud Tour, 2018