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: can be found here
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: can be found here
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, 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 to xx.xx.2022
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 to xx.xx.2022
3. Real Business Cycle Model
3.1 Model derivation:
Supplementary document to the solution to Brock and Mirman (1972) model
Slides discussing calibration, nice paper by Cooley (1997) on Calibration
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, lecture notes, Undetermined coefficients (Uhlig 1997), Perturbation Methods by SGU, QZ decomposition (Klein 1999, JEDC)
3.2 Supplementary code:
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, some algebra on the labor leisure choice growth model
stochastic growth model,
RBC model with balanced growth path,
4. Performance of RBC model
4.1 Model Evaluation
Summary of RBC performance as a motivation to NK model , 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
5. Classical Monetary Model
4.1 Lecture: slides, Gali chapter 2, dynare code, code for hand solution code
6. Future of Macroeconomics
choose one of the following papers and prepare for the discussion, i) J. Stiglitz assessment of what went wrong, ii) Larry Christiano and Martin Eichenbaum defense of DSGE models, iii) on the future of macro by Blanchard, iv) on the trouble of Macro by Paul Romer, v) Macroeconomics and Methodology by Chris Sims, vi) The Past, Present, and Future of Macroeconomic Forecasting