Professors German Cubas and Bent Sorensen
Macro III (macro topics)
Fall 2018
Syllabus Updated Sep 23
Scheduling: Classes to be rescheduled so far: August 27, August 29, September 5, October 17, and October 22.
Make-up classes: Friday Sep 21, 4 pm; Friday Oct 26 4pm, Saturday Oct 27, 9am-12am (two presentations)
Course structure (tentative):
We will have 6-10 homeworks followed by in-depth student presentations (a full class each, but we will help you) and a final project.
The grade will be determined from your homeworks (20%), presentation (20%), participation (discussion other students presentations (20%), final project (40%). The final project is due TBA (around last day of class)
We will cover econometric methods commonly used for more (or less) structural models. We will start with the econometric tools and then we will cover some recent and/or influential articles that uses these tools. Everything is tentative, except that Bent will talk about Structural VARs the first week.
GMM Notes part 3 (The first 2 pages are the most important. The theory is not going to be on exam.)
Andersen-Sorensen GMM 1996 (about estimating a Stochastic Volatility model, but the paper illustrates clearly some features of GMM estimation, which is why it is included here).
Alastair Hall's GMM resources You may want to check out the lecture (as a supplement to the class's lectures) and Kostas Kyriakoulis's GMM Toolbox for MATLAB, which is linked there.
Hansen-Singleton GMM program, the data
Some VAR notes by Christopher Sims and Stock&Watson (skim these, or read them, we will not expect you to know details)
Blanchard-Quah paper (you don't need to know the detail, but know the logic of imposing long-run constraints)
Paper by Barsky and Eric Sims (this way of using VARs may become more common)
German's slides on heterogeneity in macroeconomics
German's slides on estimation of income processes
Homework 1: Estimate a VAR (I suggested looking at real GDP growth, unemployment, and interest rates) but you can chose other data. Plot impulse response functions. Explain how you determine the number of lags.
Homework 2 Matlab Hansen-Singleton pgm Due Wed October 24
Gauss program1 (some commands in program are obscure, they trap errors to prevent program from crashing, Bent will go over some of it in class).