**PLEASE NOTE THAT I AM USING** https://www.bengriffy.com/teaching/ph-d-macro-ii/ **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:

Slides:

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

Code:

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

**A**nalyize**S**urvey**D**ata**Free (**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