Modern business cycle theory and growth theory uses stochastic dynamic general equilibrium models. In order to solve these models, economists need to use many mathematical tools. This book presents various methods in order to compute the dynamics of general equilibrium models. In Part I, the representative-agent stochastic growth model is solved with the help of value function iteration, linear and linear quadratic approximation methods, parameterized expectations and projection methods. In order to apply these methods, fundamentals from numerical analysis are reviewed in detail. In Part II, the authors discuss methods in order to solve heterogeneous agent economies. This part of the book also serves as an introduction to the modern theory of distribution economics. Applications include the dynamics of the income distribution over the business cycle or the demographic transition in a large-scale overlapping generations model. In the tables below, computer codes to all applications can be downloaded.

The book's webpage at Springer Errata

CoRRAM: User Guide and Toolkit

• MATLAB  (September 12, 2024)
• GAUSS  (March 06, 2023) 

GAUSS, PYTHON, JULIA & FORTRAN Routines

If you have questions or suggestions pertaining to the programs from Ch1 through Ch6 and Ch11 please contact Alfred Maußner.

Burkhard Heer will be pleased to answer any questions about the programs from Ch7, Ch8, Ch9 and Ch10.

More detailed descriptions of the python codes are also presented here.