Ph.D. Topics: Quantitative Macro-Labor

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.

Syllabus: link (tex)
Cluster Access: Panel Data and Empirical Regularities (link)

Slides:
Lecture 1: Introduction (link,tex)
Lecture 2: Income Processes (link,tex)
Lecture 3: Panel Data and Empirical Regularities (link,tex)
Lecture 4: Introduction to Frictional Labor Markets: The McCall Model (link,tex)
Lecture 5: Comparative Statics and Measuring Wage Dispersion in Frictional Models (link,tex)
Lecture 6: On-the-Job Search in Partial Equilibrium Models (link,tex)
Lecture 7: Burdett-Mortensen II and Accessing the Cluster (link,tex)

Programs (I’ll update these as I clean them):
Code to work with Survey of Income and Program Participation: link
Code to work with the Panel Study of Income Dynamics: link
Code to work with the National Longitudinal Survey of Youth, 1979: link

Here are some other great resources for class materials:
Gianluca Violante’s course on quantitative macroeconomics: link
Chris Tonetti’s write-up on income processes: 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