Ph.D. Topics: Quantitative Macro-Labor (AECO 803) – Fall 2024

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
Empirical Regularities Project: Explore the empirical facts surrounding the question that you presented in the introduction/research proposal project.
Final/Model Project: The final project is meant to tie these three assignments together. Write down a theoretical model with a mechanism that you believe can explain the phenomena that you see in the data. The key to this project is to correctly understand the economic mechanisms at play in your question.

Slides:

Lecture 1: Introduction (link, tex, figures)
Lecture 2: Income Processes (link, tex, figures)
Lecture 3: Panel Data and Empirical Regularities (link, tex, figures)
Lecture 4: Introduction to Frictional Labor Markets: The McCall Model (link, tex, figures)
Lecture 5: Comparative Statics and Measuring Wage Dispersion in Frictional Models: The McCall Model (link, tex, figures)
Lecture 6: On-the-Job Search in Partial Equilibrium Models (link, tex, figures)
Lecture 7: Wage-Tenure Contracts (Burdett and Coles, 2003) (link, tex, figures)
Lecture 8: Sequential Auctions (Postel-Vinay and Robin, 2002) (link, tex, figures)
Lecture 9: The DMP Model (link, tex, figures)
Lecture 10: Part Time Endogenous Separations (link, tex, figures)
Lecture 11: Efficiency and the Hosios Condition (link, tex)–Skipping for Fall 2024
  • Version history: Fall 2022 (Current version) (link, tex); Spring 2019 (link, tex)
Lecture 12: Directed Search (link, tex, figures)–Skipping for Fall 2024
Lecture 13: The Block Recursive Equilibrium (link, tex, figures)
Lecture 14: Matching Models with Heterogeneity I (link, tex, figures)
Lecture 15: Matching Models with Heterogeneity II (link, tex, figures)
Lecture 16: Local Numerical Solution Techniques (link, tex, figures)–Skipping for Fall 2024
Lecture 17: Global Numerical Solution Techniques (link, tex, figures)
Lecture 18: The Income Fluctuation Problem (link, tex)
  • Version history: Fall 2024 (Current version) (link, tex); Fall 2022 (link, tex); Spring 2019 (link, tex)
Lecture 19: Heterogeneous Agent Models (link, tex, figures)
Lecture 20: Solving Heterogeneous Agent Models I (link, tex, figures)
Lecture 21: Heterogeneous Agent Models II (link, tex, figures)
Lecture 22: Estimating DSGE Models (link, tex, figures)
Lecture 23: Beliefs in Macro-Labor I (link, tex, figures)
  • Version history: Fall 2024 (Current version) (link, tex, figures)
Lecture 24: Beliefs in Macro-Labor II (link, tex, figures)
  • Version history: Fall 2024 (Current version) (link, tex, figures)

Special Lecture: Labor Market Power (link)
Special Lecture: AI and Expectations (link)
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):

Homework 1: Solve McCall model (link, tex, figures)
  • Version history: Fall 2022 (Current version) (link, tex, figures); Spring 2019 (link, tex, figures)
Homework 2: Solve DMP model

figures); Spring 2019 (link, tex, figures)

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