Matlab programming
Course contents
This course covers some useful tools needed to solve, simulate and/or estimate micro-founded macroeconomic dynamic stochastic general equilibrium (DSGE) models. This course mainly focuses on stochastic models aimed at explaining business cycle fluctuations.
The course is organized around two objectives:
Point (i) contains a theoretical presentation of methods necessary to estimate and evaluate DSGE models. In particular bayesian methods and state space models are presented together with Markov chain Monte Carlo algorithms (MCMC)
In order to handle point (ii), we will begin with a brief introduction on Matlab use. Then, simulation and estimation of model are done by programming or by using Dynare.
Topics
Prerequisites
A basic knowledge of multivariate time series, statistics and simulation methods.
Learning outcomes
The main objective is to develop skills to estimate, analyze and validate dynamic stochastic general equilibrium models.
Teaching methods
Part of the class will be devoted to the discussion of some theoretical issues related to the topics. Each theoretical topic will be integrated by examples and applications.
Assessment methods
Each student will have to make a presentation of a research article. The presentation should last approximately 25 minutes and count for the 80% of the final grade. The student is expected to (1) Explain how the presented paper contributes to existing literature (2) explain the methodology and results (3) discuss the strengths and weaknesses of the paper, and, if possible, give your recommendations for changes that would strengthen the paper. The remaining 20% is going to depend on participation in lectures.
Syllabus
Office hours
By appointment.