Ph.D. Macro II (AECO701) – Spring 2023

PLEASE NOTE THAT I AM USING for all class material now.

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, Yue Li, and Betty Daniel, in order in which they taught the course (least recent to most recent). 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 submit on the campus cluster. please also email myself and our TA):
Problem Set 1 (Due: 2/2): Programming practice (link, tex)
Problem Set 1 Answer Key
Problem Set 2: Markov chains
Problem Set 2 Answer Key
Problem Set 3: Linear difference equations and the Contraction Mapping Theorem
Problem Set 3 Answer Key
Problem Set 4: Income fluctuation problem and Guess and Verify method
Problem Set 4 Answer Key
Problem Set 5: The RBC Model
Problem Set 6: The Heterogeneous Agent Model

Exam Answer Keys:

Lecture 1: Introduction (link, tex, figures)
Lecture 2: Overview of Macro Models (link, tex, figures)
Lecture 3: Stochastic Processes I (link, tex, figures)
Lecture 4: Stochastic Processes II (link, tex, figures)
Lecture 5: Linear Difference Equations (link, tex, figures)
Lecture 6: Lucas Critique
Lecture 7: Dynamic Programming
Lecture 8: Consumption Smoothing and Permanent Income
Lecture 9: Asset Pricing and Lucas Tree
Lecture 10: Complete Markets
Lecture 11: Stochastic Neoclassical Growth
Lecture 12: Solution Methods I: Guess and Verify
Lecture 13: The RBC Model
Lecture 14: Midterm!
Lecture 15: Solution Methods II: Value Function Iteration
Lecture 16: Solution Methods III: Log-Linearization
Lecture 16 Supplemental Material: Linearizing Hansen (1985) Model
Lecture 17: RBC Calibration and Extensions
Lecture 21: Income Fluctuations
Lecture 22: Heterogeneous Agents
Lecture 23: Solving Heterogeneous Agents
Lecture 24: McCall Model
Lecture 25: Diamond-Mortensen-Pissarides

Extra Lectures (will not be tested):
Lecture 26: Hosios Condition
Lecture 27: Directed Search

Retired Lectures:

Lecture 18: New Keynesian Model I
Lecture 19: New Keynesian Model II
Lecture 20: Financial Frictions

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
AnalyizeSurveyDataFree (asdfree): a website that includes MANY R codes to analyze many publicly available survey datasets: link (original github)

And other fun material:
Inspirational Teddy Roosevelt Quotes: link