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Teri Dunn
Programme Executive
 

Methods Summer Programme
London School of Economics
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London WC2A 2AE
 

Email: summer.methods@lse.ac.uk
Tel: +44 (0)20 7955 6422
 

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ME421 Tools for Macroeconomists: The Essentials

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This is a hands-on graduate-level course teaching key techniques to analyse and estimate macroeconomics models. It teaches the key building blocks of numerical analysis such as function approximation and numerical integration. The course shows how these techniques are used in perturbation and projection methods to accurately solve nonlinear dynamic stochastic models. Relevant theoretical aspects such as the Blanchard-Kahn conditions and the possibility of sunspots solutions are also covered. The course also teaches the tools to estimate such models (Kalman filter, Bayesian estimation, MCMC). 

Students are taught how to use Dynare, but also how to write Matlab programs to solve a variety of models with other techniques. In addition to teaching techniques, the course also focuses on practical problems that researchers run into when using these techniques.

The course is aimed at PhD students and academics.

Course benefits

This course will provide students with:

  • a chance to learn a solid set of different tools to analyse and estimate modern macroeconomic models
  • a better understanding of the properties of modern macroeconomic models
  • a better understanding of the importance of nonlinearities
  • a better understanding of the limitations of popular techniques

Prerequisites
Basic knowledge of DSGE models, and in particular, concepts such as Euler equations, state variables, and the Bellman equation.
Some knowledge of Matlab. Students with a rudimentary knowledge of Matlab may still take the course, but may not attain the full benefits of the afternoon computer assignments.

The course teaches the key building blocks of numerical analysis such as function approximation and numerical integration. The course shows how these building blocks are used in perturbation and projection methods to accurately solve nonlinear dynamic stochastic models. Relevant theoretical aspects such as the Blanchard-Kahn conditions and the possibility of sun spots solutions are also covered. The course also teaches the tools to estimate such models with Bayesian estimation techniques.

In the morning sessions, a lecture is given by one of the two instructors. In the afternoon sessions, students work in groups on computer assignments with the help of the instructors and teaching assistants.

Monday - Solving and analysing your first DSGE model

  • State variables
  • Policy rules (i.e. the recursive solution to DSGE models)
  • Impulse response functions
  • Perturbation analysis
  • Certainty equivalence
  • Dynare
  • Using the homotophy idea to get good initial values for the steady state (often the hardest part of running Dynare)
  • Parameter values and properties of basic neoclassical model
  • Stylised facts

Tuesday - Key tools from the numerical approximation literature and projection methods

  • Numerical integration (Gaussian quadrature)
  • Function approximation (Splines & Polynomials)
  • Projection methods
  • Endogenous grid points
  • Fixed point iteration
  • Time iteration

Wednesday - Topics

  • Parameterized Expectations Algorithm
  • Value Function Iteration
  • Accuracy tests: Euler errors, Dynamic Euler equation test, DHM statistic
  • Occasionally binding constraints and penalty functions
  • Blanchard-Kahn conditions
  • Sunspots and self-fulfilling expectations

Thursday - Kalman filter and full information methods

  • Kalman filter
  • State space form
  • Maximum Likelihood
  • Avoiding the singularity problem

Friday - Bayesian estimation

  • Bayesian estimation
  • MCMC
  • Metropolis Hastings
More detailed information on the course can be found on Professor den Haan's website.

Software used
Dynare and MATLAB

The course has tremendously increased my skill, particularly the computer exercise. Having a direct practical experience is a amazing opportunity.
2016 Participant

This course was impressive. Incredibly demanding but the exercise units made the abstract concepts mesh in practice and allowed us to experience parts of the implementation first hand. 
2015 Participant

An all-around outstanding learning experience!
2014 Participant

I thought Petr and Wouter were amazing at simplifying difficult concepts and boiling it down to the core.
2014 Participant

Excellent. The instructor introduces several frontier fields of research.
2011 Participant

The course sets the right focus, and is very well organized and structured. The professor is an excellent teacher and highly committed.
2011 Participant


Please note: The below timetable contains approximate hours only.

  Tu  Th   F
 Morning lecture  3 3  3 3 3
 Afternoon class 3 3 3 3 3
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Course details


Dates
14 - 18 August 2017

Format
Lectures (15 hours)
Practical classes (15 hours)

Location
LSE's Central London Campus

Teaching faculty
Professor Wouter den Haan
Department of Economics
Dr Petr Sedlacek
University of Bonn

2017 Tuition fees
Student rate: £725
Academic staff/charity rate: £1,500
Professional rate: £2,300

*Current PhD students are also eligible for a £150 ESRC scholarship.


 
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