Advanced Computational Methods in Macroeconomics

Event Date
Keynes Room, Faculty of Economics


This Masterclass on 'Advanced Computational Methods in Macroeconomics' given by Professor Jesus-Fernandez Villaverde

Monday       27th May, 2-5pm
Tuesday       28th May, 2-5pm
Weds           29th May, 4-7pm 


JI Visitor Link(s):

1 Master Class

This master class will introduce some of the essential tools to undertake research in machine learning and continuous-time methods in economics.

2 Course structure

The course will be organized around three sessions of three hours (with a 20-minute break each day).

  • Introduction to Deep Learning in Macroeconomics
  • Applications of Deep Learning in Macroeconomics
  • Continuous-time Methods in Macroeconomics

Summing up all these sessions, you should expect around 480 minutes of lectures plus individual work and office hours.

3 Course material

All the material will be based on my lecture notes and slides. I will provide all the relevant material before the course starts.

Depending on time, we will also go over some Matlab and Python code.

4 Pre-requisites

It is assumed students are familiar with first-year graduate school macroeconomics and have some basic experience coding.

Familiarity with basic continuous-time methods (e.g., Hamiltonians) would be useful, but it is not required.

Enquiries: Marion Reusch,

JI Research Theme
Event Organiser