Timothy B. Armstrong
ProfessorDepartment of Economics
University of Southern California
Lecture notes
The following is a selection of lecture notes related to my research interests. If you are currently taking one of my courses, please see the course site on Blackboard for up-to-date lecture notes.Research topics. Slides discussing some of my research interests. Used for guest lecture in PhD econometrics topics course.
Nonparametric estimation. Lecture notes on nonparametric estimation, emphasizing the finite-sample approach to bias-variance optimization and bias-aware CIs. Used for first year econometrics Ph.D. course.
Decision theory. Lecture notes on decision theory as it applies to some topics from a standard first year econometrics Ph.D. course.
Optimal inference and adaptation bounds. From Spring 2016 Ph.D. topics course.
Moment inequalities and weak instruments. Lecture notes on moment inequalities and weak IV, with an emphasis on computation. From Fall 2017 second year Ph.D. course.
Courses taught
USC ECON 570: Big Data Econometrics (Fall 2022). Master's course covering methods for high-dimensional data.
USC ECON 460: Economic Applications of Machine Learning (Fall 2021, Fall 2022). Advanced undergraduate course covering methods for high-dimensional data.
Yale ECON 135: Introduction to Probability and Statistics (Fall 2012, Fall 2013, Fall 2015, Fall 2016, Fall 2019). First semester of year-long undergraduate sequence covering probability, statistics and econometrics.
Yale ECON 420: Applied Econometrics (Fall 2016, Fall 2017, Fall 2019, Fall 2020). Advanced topics course in econometrics for undergraduates; online for Fall 2020.
Yale ECON 554: Econometrics V (Spring 2014, Spring 2016). Advanced topics course in econometrics for Ph.D. students.
Yale ECON 551: Econometrics II (Spring 2016, Spring 2017, Spring 2018, Spring 2020, Spring 2021). Second semester of year-long econometrics sequence for first year Ph.D. students.
Yale ECON 556: Topics in Empirical Economics and Public Policy (Fall 2017). Second year course in applied econometrics for Ph.D. students.