MacroEconometricsF2019

MacroEconometricsF2019 Macroeconometrics
Fall 2019 Instructor: Bent E. Sorensen

No class: Wednesday September 4th and November 25th (last day of classes)

No lecture: Monday October 21st. You are required to meet with me and commit to topic for you presentation. I would like like you to come to my office and talk about this in advance, but this is the deadline for you to commit (subject to revision, that is fine, but I need to know what your moving ahead with

Make-up classes: TBA. We will have some classes and/or student presentations after Thanksgiving.

Syllabus

To pass the class: Occasional homeworks, one (or two?) presentations, a final project.

August 26th, I will finish the Kalman Filter/Smoother and then I will talk loosely about subfields of macroeconometrics for a couple of classes, see list below, to give you an idea of what is available, before we continue doing some of the fields more rigorously with programming. I will add references (in particular to surveys or survey-like articles as we go along)

A good place to look for summaries of econometric topics is the list of NBER lectures. NBER econometrics lectures

One good way to get an idea for your class project is too look at recent issue of the American Economic Review or American Economic Journal: Macroeconomics. These journals request authors to post their data (if feasible).

Vector Autoregressive Models (VARs) and Structural VARs, see Stock and Watson JEP survey on VARs (or see the NBER lecture on this and Local Projections)
Teaching notes on SVARs

Teaching notes on Granger Causality
Lutz Kilian has done very influential work on oil prices using VARs and he will present in the macro seminar September 16th. We may want to study his AER 2009 paper before he comes
Dynamic Factor Models Stock and Watson (again) survey (I will find or write some material on static factor models to start from, if we do this material)
Regime Switching Models (Popularized by Hamilton, so Chapter 22 in his Time Series Analysis may be the place to start)
Unit roots and co-integration (I have written notes on unit root testing and Johansen cointegration that I will post)
Bayesian methods (applications to dynamic models, VARs)
More micro: Dynamic models of panel data, Duration models,
Models of volatility.Teaching notes (if we dig into it they will need some updating)
GMM methods. GMM can be uses in the any context, but sometimes it is the natural tool to use.

Notes:

Notes on Kalman Filter .

Notes on Unit Roots .

Notes on Cointegration .

Notes on The APT and Static Factor Analysis .

Homework # ;Due

Homework 1 Matlab code loops Matlab code loops Mon Sep 9

Gauss code

Homework 2 Mon Sep 9

Homework 3 Mon Oct 21