Welcome to AECO 803, a Ph.D. topics course that I’m calling “Quantitative Macro-Labor.” This page (as well as the Blackboard page) will host course content. In addition to posting PDFs of the course material, I will make (to the extent possible) LaTeX code and programs available when used in class. I find that exploring code that others have used is far more helpful than most tutorials. Some material I cannot make available online. If this is the case, please email me. Any other instructors are free to use my material, but please note where it came from and let me know so that I can list it in my activity reports to the College.
Syllabus: link (tex)
Cluster Access: (link)
Projects:
Introduction/Research Proposal: Write the “introduction” to a paper on a macro-labor question in which you are interested. Here is some advice that I have aggregated from others: link, tex
Slides:
Lecture 5: Comparative Statics and Measuring Wage Dispersion in Frictional Models: The McCall Model (link, tex, figures)
Lecture 14: Local Numerical Solution Techniques (link, tex, figures)
- Supplemental handouts: Linearizing Hansen (1985), Solving Hansen (1985)
- Version history: Fall 2022 (Current version) (link, tex, figures); Spring 2019 (link, tex, figures)
Special Lecture: Affirmative Action and Beliefs (link)
Lecture 21: Matching Models with Heterogeneity II
- Version history: Fall 2022 (Current version); Spring 2019
Lecture 22: DSGE Estimation
- Version history: Fall 2022 (Current version); Spring 2019
Final Presentations 12/3 and 12/5.
Programs (I’ll update these as I clean them):
Access the shared folders on the campus cluster or see me/email me directly.
Previous Homework Assignments (course now project based):
Here are some other great resources for class materials:
Gianluca Violante’s course on quantitative macroeconomics: link
Jesus Fernandez-Villaverde’s slides on computational techniques: link
Makoto Nakajima’s notes on solution techniques: link
Daron Acemoglu and David Autor lectures on labor economics: link
Chris Tonetti’s write-up on income processes: link
Useful review of linearization: link
Here are other useful resources for programming or data:
Tom Sargent and John Stachurski’s website on dynamic macroeconomics in Python and Julia: link
Anaconda Python: link
CEPR SIPP webpage: link
IPUMs CPS webpage: link
Anthony Damico’s website on survey data: link
SIPP FTP and data definitions: link
And other fun material:
Inspirational Teddy Roosevelt Quotes: link