2018macroIII
Classes: Friday 9:15 - 10:45, RB106
Seminars: Friday 11:00 - 12:30, RB106
Teachers: Aleš Maršál
Office Hours:
Ales: after the Friday class
Grading:
Homework Assignments: 40%
In-Class Preliminary Exam 1: 20%, March 31, 9:15 - 10:45, RB105
Final Exam: 40%, Last week , 9:15 - 12:00
Course Material:
Textbook:
The ABCs of RBCs : an introduction to dynamic macroeconomic models, by McCandless;
Monetary Policy, Inflation, and the Business Cycle: An Introduction to the New Keynesian Framework, by J. Gali
Other: Course slides and problem sets: posted below
Course Content
1. Introduction
1.1 Lecture:
slides with course motivation, outline, requirements, literature,
short history of business cycles - the underlying paper, policy analysis with macro models
1.2 Seminar:
matlab basics: slides, code solving the class exercise, NICHOLAS SIM code we did not mange to look at in class, Winistörfer P. and Canova F., 2006,''Introduction to Matlab'', Matlab cheat sheet, nice youtube lecture, source of some other materials
Function approximation: slides, approx.m, classpolinomials.m
Log-linearization: Katrin's lecture notes on log-linearization, Uhlig log-linearization, yet another lecture notes, very nice material on the story behind Lagrange Multipliers
Problem set 1, due 6.10.2017
2. Stylized facts
2.1 Lecture:
Introduction to macro data: slides, matlab code to reproduce the class material: hpfilter.m, bandpass.m, stylizedfacts.m
Recommended reading Stock and Watson (1998): "Business Cycle Fluctuations in U.S. Macroeconomic Time Series",
Obligatory reading: King and Rebelo (2000): "Resuscitating Real Business Cycles", (chapter 2)
Nice lecture notes by Eric Sims
2.2 Seminar:
Matlab code: in class exercise solution, system of linear equations
US data set, Guide to NIPA tables
Problem set 2, due 20.10.2017
3. Real Business Cycle Model
3.1 Lecture:
code for the first model we did in the class: optimal growth model,
code for the growth model with labor: optimal growth model with labor leisure choice,
stochastic growth model,
RBC model with balanced growth path,
important reading King and Rebelo (2000): "Resuscitating Real Business Cycles",
King Plosser Rebelo (2001): ".Production, Growth and Business Cycles: Technical Appendix"
Methods for solving rational expectations models: slides, Undetermined coefficients (Uhlig 1997), Perturbation Methods by SGU, QZ decomposition (Klein 1999, JEDC)
3.2 Seminar:
Introduction to dynare, stochastic growth model log-linearized by dynare, log-lin model in dynare, model in levels
code for RBC model with balanced growth path
Calibration - updated slides, paper by Cooley 1997, Calibrated Models
model evaluation + observation equation based on Pfeifer lecture notes
code to solve basic growth model by diagonalization
Paul Klein solab function implementing QZ decomposition, application to our stochastic growth model
Problem set 3, due 10.11.2017
Problem sets results can be find here.
Problem set 4, due 24.11.2017
Problem set 4 solution:
slides
code to solve the King Rebelo 1999 by:
method of undetermined coefficients
QZ decomposition (using solab.m function)
dynare in levels
dynare log-lin solution
4. Performance of RBC model
4.1 Model Evaluation
Model evaluation in my slides, underlying paper for the discussion is here, lecture by Chris Sims see here
see critique by Galí (1999) of RBC models, some evidence and discussion on monetary policy neutrality Gali textbook ch.1
for summary on what we know about shocks driving the cycle see Ramey 2016
clean dynare output function
this code shows how to use Kalman filter to extract shocks from the observable series (watch Kalman filter explained in an extremely intuitive way, see Pfeifer lecture notes on how to link observables with your model variables), and it also demonstrates one way how to run loops in dynare, you will also need this .mod file, this is the code for King Rebelo 99 when frish elasticity is different from one
Problem set 5 (Criticism of RBC), due 1.12.2017
Solution, ExpKingRebeloMIII.mod file, code to get TFP innovations using Kalman filter
4.2 Beyond Calibration
my slides, baseline model
Estimating baseline model using GMM, Ruge Murcia (2011) for the Handbook of Empirical Macroeconomics
DSGE VAR code
Bayesian Estimation code
5. Classical Monetary Model
4.1 Lecture: slides, Gali chapter 2, dynare code, hand solution code
4.2 Seminar: Model evaluations
Problem set 6, due 15.1.2017
Solution