2018macroIII

  • Syllabus

  • 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:

1.2 Seminar:

2. Stylized facts

2.1 Lecture:

2.2 Seminar:

3. Real Business Cycle Model

3.1 Lecture:

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 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