ENSAE Paris - École d'ingénieurs pour l'économie, la data science, la finance et l'actuariat

Macroeconomics 2 : Fluctuations

Objective

In this course, students will discover many numerical methods, that are needed for the approximate solution of macroeconomic models (perturbation, interpolation, dynamic programming...).

Over the full course, students will have the opportunity to review various models with the additional goal to be able to "code and play" with any of them.

They will also learn practical foundations needed to practically understand more advanced model such as heterogenous agents models.

The course will alternate between traditional lectures and hands-on tutorial sessions using programming language Julia.

Planning

- recursive sequences: solow model

- perturbation methods (×2): new-keynesian model, neoclassical model

- discretization

- discrete markov chain problem (dmdp) (×2): mccall model

- interpolation 

- value-function iteration: dynamic portfolio optimization

- time iteration variants: consumption saving