Numerical methods in economics 2022

Prof.ssa Renata Bottazzi

  • Date:

    11 APRIL
    22 APRIL 2022
     from 11:00 to 13:00
  • Event location: Aula IV, Via Belle Arti 41 and STAT PhD Classes Virtual Room - In presence and online event

  • Type: Cycle 37 - Short courses and seminars

After completing the course students should have an understanding of how to numerically solve and simulate dynamic optimisation models in economics. The first part of the course is devoted to introducing the theoretical setup:  recursive methods are discussed in relation to standard dynamic models, such as a lifecycle model of consumption and savings; and, the numerical methods that are typically used for the computational solution and simulation of such models are introduced. The second part of the course is devoted to the practical implementation in Matlab of the methods acquired in the first part.

Course contents

1. Theory of Dynamic Programming (DP): Bellman equation and recursive solution.

2. Numerical methods for DP problems: value function iteration and policy function iteration. Interpolation methods, numerical integration and simulation of the model.

3. Analysis of an economic model in finite horizon: solution and estimation methods for a simple life cycle consumption and savings model. Infinite horizon and solution methods.

4. Practical implementation of a simple DP model in Matlab.


Suggested readings

The topics covered in this course are mainly based on the books listed below. More detailed references and relevant papers from the economics literature will be provided at the beginning of the course.

Adda, Jerome and Russell Cooper (2003). Dynamic Economics. Cambridge, MIT Press.
Judd, Kenneth (1998). Numerical Methods in Economics. Cambridge, MIT Press.
Ljungqvist, Lars and Thomas Sargent (2012). Recursive Macroeconomic Theory. 3rd Edition. Cambridge, MIT Press.
Stokey, Nancy and Robert Lucas (1989). Recursive Methods in Economic Dynamics. Cambridge, Harvard University Press.