Computational Macroeconomics combines macroeconomic theory with hands-on programming.  The course provides you with both an analytical understanding of macroeconomic models and the tools needed to build and solve them.

At its core, the course introduces lifecycle and overlapping generations (OLG) models — a foundational framework for analyzing how different generations interact in the economy. These models are widely used in macroeconomic research to study questions such as the effect of demographic change on returns to capital or the design and reform of pension systems.

Alongside the economic theory, the course builds practical skills in numerical solution methods, with a focus on value function iteration. You will implement these methods directly in Python, bridging the gap between abstract economic modeling and working, executable code.

By the end of the course, you will be able to build and analyze OLG models from the ground up, apply value function iteration to solve quantitative economic models, and implement solution algorithms in Python.

This course is ideal preparation for writing a thesis at the Chair of Macroeconomics and for anyone looking to engage seriously with modern economic research.