Ph.D. Macro II (AECO 701) – Spring 2024

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: Betty Daniel, Yue Li, and John Jones, in order in which they taught the course (most recent to least 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: 1/25): Programming practice (link, tex)
  • Version history: Spring 2021 (Original version) (pdf, tex)

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Problem Set 1 Answer Key (link, tex)
  • Code (matlab)
  • For previous versions: 2021 (Current version) (pdf, tex)

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Problem Set 2 (Due 2/15): Markov chains (link, tex)
  • Version history: Spring 2021 (Current version) (pdf, tex, figures)

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Problem Set 2 Answer Key

pdf, tex)

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Problem Set 3: Linear difference equations and the Contraction Mapping Theorem


Problem Set 3 Answer Key

  • For previous versions: 2021 (Current version) (pdf, tex)
Problem Set 4: Income fluctuation problem and Guess and Verify method


Problem Set 4 Answer Key


Problem Set 5: The RBC Model


Problem Set 5 Answer Key

  • For previous versions: 2021 (Current version) (pdf, tex)
Problem Set 6: The Heterogeneous Agent Model


Problem Set 6 Answer Key

  • For previous versions: 2021 (Current version) (pdf, tex)

Likely Future Assignments (note that these may change prior to being assigned):

Exam Answer Keys:

Midterm


Final


Slides:

Lecture 1: Introduction (link, tex, figures)
  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 2: Overview of Macro Models (link, tex, figures)
  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 3: Stochastic Processes I (link, tex, figures)
  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 4: Stochastic Processes II (link, tex, figures)
  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 5: Linear Difference Equations (link, tex, figures)
  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 6: Lucas Critique (link, tex, figures)
  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 7: Dynamic Programming (pdf, tex, figures)
  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 8: Consumption Smoothing and Permanent Income (pdf, tex, figures)
  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 9: Asset Pricing and Lucas Tree (pdf, tex, figures)
  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 10: Complete Markets (pdf, tex, figures)
  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 11: Stochastic Neoclassical Growth (pdf, tex, figures)
  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 12: Solution Methods I: Guess and Verify

figures)

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  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 13: The RBC Model

figures)

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  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 14: Midterm!
Lecture 15: Solution Methods II: Log-Linearization

  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 15: Solution Methods III: Value Function Iteration

  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 16 Supplemental Material: Linearizing Hansen (1985) Model

  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 17: RBC Calibration and Extensions

  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 22: Heterogeneous Agents

  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 23: Solving Heterogeneous Agents

  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 24: McCall Model

  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 25: Diamond-Mortensen-Pissarides

  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 26: Hosios Condition

figures)

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  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 27: Directed Search

  • Version history: Spring 2021 (Current version) (pdf, tex, figures)

Briefly Resting Lectures:

Lecture 18: New Keynesian Model I

  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 19: New Keynesian Model II

  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 20: Financial Frictions

  • Version history: Spring 2021 (Current version) (pdf, tex, figures)
Lecture 21: Income Fluctuations

  • Version history: Spring 2021 (Current version) (pdf, tex, figures)


Programs (I’ll update these as I clean them):
Access the shared folders on the campus cluster or see me/email me directly.

Here are some other great resources for class materials (some links may no longer be working):
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