Ph.D. Macro II (AECO701)

Welcome to AECO 701, the second semester of the first-year Ph.D. macro sequence. This 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. Please note: my LaTeX code is generally a mess. 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.

I should note that much of this material is based on lectures developed by the previous instructors of this course: John Jones, Betty Daniel, and Yue Li. I have also linked to other course pages that I found helpful in developing this material below.

Syllabus: link (tex)
Cluster Access: (link)

Homework (please email to myself and the TA by the due date):
Problem Set 1 (Due: 2/10): Programming practice (link,tex)
Problem Set 1 Answer Key (link,tex,code)
Problem Set 2 (Due: 2/24): Markov chains (link,tex)
Problem Set 2 Answer Key (link,tex,code)
Problem Set 3 (Due 2/24): Linear difference equations (link,tex)
Problem Set 4 (Due 3/24): Income fluctuation problem (link,tex)
Problem Set 4 Answer Key (link,tex)
Problem Set 5 (Due 4/7): The RBC Model (link,tex)
Problem Set 6 (Due 5/12): The Heterogeneous Agent Model (link,tex)

Exam Answer Keys:
Midterm: link

Lecture 1: Introduction (link,tex)
Lecture 2: Overview of Macro Models (link,tex)
Lecture 3: Stochastic Processes I (link,tex)
Lecture 4: Stochastic Processes II (link,tex)
Lecture 5: Linear Difference Equations (link,tex)
Lecture 6: Lucas Critique (link,tex)
Lecture 7: Dynamic Programming (link,tex)
Lecture 8: Consumption Smoothing and Permanent Income (link,tex)
Lecture 9: Asset Pricing and Lucas Tree (link,tex)
Lecture 10: Complete Markets (link,tex)
Lecture 11: Stochastic Neoclassical Growth (link,tex)
Lecture 12: Solution Methods I: Guess and Verify (link,tex)
Lecture 13: Midterm!
Lecture 14: The RBC Model (link,tex)
Lecture 15: Solution Methods II: Log-Linearization (link,tex)
Lecture 16: Solution Methods III: Value Function Iteration (link,tex)
Lecture 17: RBC Calibration and Extensions (link,tex)
Lecture 18: New Keynesian Model I (link,tex)
Lecture 19: New Keynesian Model II (link,tex)
Lecture 20: Financial Frictions (link,tex)
Lecture 21: Income Fluctuations (link,tex)
Lecture 22: Heterogeneous Agents (link,tex)
Lecture 23: Solving Heterogeneous Agents (link,tex)
Lecture 24: McCall Model (link,tex)
Lecture 25: Diamond-Mortensen-Pissarides (link,tex)
Lecture 26: Hosios Condition (link,tex)
Lecture 27: Directed Search (link,tex)

Access the shared folders on the campus cluster or see me/email me directly.

Here are some other great resources for class materials:
Eric Sim’s PhD macro II course: link
Chris Edmond’s PhD macro II course: link
Dirk Krueger’s macro notes: 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

And other fun material:
Inspirational Teddy Roosevelt Quotes: link