Two - Year Master Degree in Economics

MACROECONOMICS MOD. DYNAMIC AND NUMERICAL

MACROECONOMICS MOD. DYNAMIC AND NUMERICAL

Academic year 2024/2025

Sommario del corso

• Course objectives
• Results of learning outcomes
• Program
• Course delivery
• Learning assessment methods
• Suggested readings and bibliography
• Teaching tools
• Course card

Course objectives

The course aims at introducing students to numerical techniques and languages for solving dynamic stochastic general equilibrium models

 The course is an introduction  to contemporary numerical methods in quantitative economics: stochastic difference equation, rational expectation equilibria, non linear models, dynamic programming, markov chains and other tools used in contemporary economics.

 The main example will be from macroeconomics and many models will be Dynamic Stochastic General Equilibrium (DSGE) models. Nevertheless, the tools taught can be used in and field of economics. The spirit of the course is to help student realizing that contemporary economics has to rely on computer power and computing methods.

 The main language  used in the application is Python, a popular open source code that is now in becoming increasingly used in economics. Knowledge of Python or any other programming language  is not essential, but some background in basic programming will be an advantage. 

Results of learning outcomes

Students will be able to use standard open source software to solve dynamic models, and to be read to enter more advanced macroeconomic topics

Program

Details of the program will be distributed at the beginning of the course. The Lectures in Quantitative Economics by Sargent, T.  and J.  Stachursky are a good exampls of some the issues that will be covered.

Course delivery

The teaching will be standard in most class. Numerical examples will be provided in class. The classes will also be organized in compter lab, and students can either use their own computer or the computer provided by the University. 

Learning assessment methods

Learning will be assessed via a set of problem sets and a final exam/essay in which the students will aplly numerical techniques learnt in the course

Alogoskoufis, (2019) George Dynamic Macreoconomics, MIT Press.

Acemoglu, Daron (2009) Introduction to Modern Economic Growth, Princeton University Press

Class Notes and Handouts will be available for most topics and delivered on moodle 

Courses that borrow this teaching

• Simulation models for economics (MAT0048)
  Laurea Magistrale (M.Sc.) in Stochastics and Data Science

• Teaching material
• Exams and finals
• Class schedule
• Go to Moodle
• Register for the course
• Enrolled students
• Invia email agli studenti registrati
• Export table