Jann Spiess

Jann Spiess
Assistant Professor, Operations, Information & Technology
Contact Info
JannSpiess

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.

Research Interests

  • Data-driven Decision-making
  • Machine Learning
  • Econometrics
  • Causal Inference
  • Data Science

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

Publications

Journal Articles

Jens Ludwig, Sendhil Mullainathan, Jann Spiess. American Economic Association. May 2019, Vol. 109, Pages 71-76.
Jann Spiess, Talia Gillis. The University of Chicago Law Review. March 2019, Vol. 86, Issue 2, Pages 459-487.
Jann Spiess, Sendhil Mullainathan. Journal of Economic Perspectives. 2017, Vol. 31, Issue 2, Pages 87–106.

Teaching

Degree Courses

2020-21

This is the first course in the sequence in graduate econometrics. The course covers some of the probabilistic and statistical underpinnings of econometrics, and explores the large-sample properties of maximum likelihood estimators. You are...

Base Data and Decisions is a first-year MBA course in statistics and regression analysis. The course is taught using a flipped classroom model that combines extensive online materials with a lab-based classroom approach. Traditional lecture...

2019-20

Base Data and Decisions is a first-year MBA course in statistics and regression analysis. The course is taught using a flipped classroom model that combines extensive online materials with a lab-based classroom approach. Traditional lecture...

This year-long course takes a hands-on approach to learning about conducting research in Operations, Information and Technology. It will cover a broad spectrum of cutting-edge research in OIT from conceiving an idea to formulating a research...

Stanford University Affiliations

Stanford GSB