'Tools for Macroeconomists: The Essentials and Advanced Tools' will be run online. These intensive graduate-level courses provide a combination of lectures and hands-on computer sessions. Participants will leave with a deep understanding of numerical methods and a portfolio of Matlab codes implementing them.
We are keeping a close eye on the situation with Covid-19 and if possible, we may be able to run an in person option for those that would like it.
For more information, see the Programme website.
This course covers basic building blocks of numerical analysis, their use in solving modern macroeconomic models and an introduction into model estimation. Students will use Matlab code to solve and analyse macroeconomic models.
- function approximation, numerical integration
- perturbation, projection methods
- Kalman filter, Bayesian estimation, MCMC methods
This course teaches state-of-the-art methods for solving and analyzing advanced macro-economic models. Participants will not only write their own code, but also learn how to resolve problems that researchers may run into when using these advanced methods.
- models with heterogeneous agents
- continuous time models
- models with occassionally binding constraints
Each morning, a 3 hour lecture will introduce participants to the topic of the day. The focus is not on a single technique, but on state-of-the-art alternatives understanding when their use is appropriate. The key aim is to understand the techniques, not just being able to run programs and generate output.
Every afternoon, participants will implement the techniques discussed in lectures. Carefully designed assignments are solved in groups with the help of the instructor and teaching assistants. This is a crucial part of the course as it forces participants to truly understand the inner workings of the computational methods.
The assignments are based on pre-prepared Matlab code which includes the structure necessary for solving the assignment. However, the code leaves out the key computing steps. This way students do not waste effort on setting up the computer code, while at the same time being forced to put together the key elements necessary for implementing the computational method.
At the end of the course, answers to all assignments are made available. Therefore, participants walk away with a portfolio of Matlab codes implementing all the discussed computational techniques.
- Students (MPhil/MRes/MSc/PhD): £475 per course
- Academics: £625 per course
- Professionals (Central banks and non-academic institutions): £2,300 per course
How to Apply:
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