Computational Methods in Economics
University of Chicago (B.A.)
This page provides links to my course material and my teaching experience.
This course introduces the empirical and computational techniques necessary for numerical estimation and simulation in economics. Through examples in economics, the course covers topics such as optimization, function approximation, and monte carlo techniques. Emphasis will be placed on developing effective programming and research practices. The course is structured through a series of applications in topics such as segregation, occupational choice, and repeated games. The course will be taught in R. Though helpful, no previous experience with R is required.
These files are also on our github page here.
This course introduces the empirical and computational techniques necessary for numerical estimation and simulation in economics. Through examples in economics, the course covers topics such as optimization, function approximation, and monte carlo techniques. Emphasis will be placed on developing effective programming and research practices. The course is structured through a series of applications in topics such as segregation, occupational choice, and repeated games. The course will be taught in R. Though helpful, no previous experience with R is required.
Additional files and help are also on our github page here.
This colloquium covers the computer tools and programming techniques to implement and test economic ideas and theories quantitatively. It is more of an “engineering” than a “theory” course, focusing on the practical – working on problems and solutions. The goal is not only to provide students with an introduction to two valuable programming languages (R and C++) but also to introduce good programming, data, and project management techniques.
The class syllabus can be downloaded Here
This colloquium covers the computer tools and programming techniques to implement and test economic ideas and theories quantitatively. It is more of an “engineering” than a “theory” course, focusing on the practical – working on problems and solutions. The goal is not only to provide students with an introduction to two valuable programming languages (R and C++) but also to introduce good programming, data, and project management techniques.
This colloquium covers the computer tools and programming techniques to implement and test economic ideas and theories quantitatively. It is more of an “engineering” than a “theory” course, focusing on the practical – working on problems and solutions. The goal is not only to provide students with an introduction to a number of valuable programming languages, but also to introduce good programming, data, and project management techniques.
This will be an interactive session covering R basics and standard programming techniques in R. Students should bring their computers to participate if possible.Comparisons will be drawn between R, Stata, and Matlab. Using the tools covered in the previous session in the second session will live-code a simulation of Schelling's Segregation model. This will cover control flow, random number generation, matrix manipulation, functions, proper coding etiquette, and plotting in R.
Please install R and Rstudio and run this code prior to arrival (code).
Files from Past Years (including Stata intro): Stata code | Stata data | CPI data | R code
University of Chicago (B.A.)
University of Chicago (B.A.)
University of Chicago (co-teaching, Ph.D.)
University of Chicago (co-teaching, Ph.D.)
University of Chicago (co-teaching, Ph.D.)
University of Chicago (co-teaching, B.A.)
University of Chicago (co-teaching, B.A.)
University of Chicago (co-teaching, B.A.)
University of Chicago (co-teaching, B.A.)
Yale University (teaching, B.A.)
University of Chicago (Becker and Murphy; Ph.D.)
University of Chicago (Becker and Murphy; Ph.D.)
University of Chicago (Murphy; Ph.D.)
Booth Graduate School of Business (Gibbs; Exec. MBA)
Booth Graduate School of Business (Stole; Exec. MBA)
University of Chicago (Lima and Tsiang; B.A.)