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This course teaches you computational methods to solve deterministic as well as stochastic life-cycle models with overlapping generations using Python.

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Frederik-Tim-Econ/Course-in-Computational-Macro

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A Course in Computational Macroeconomics

By Frederik Bjørn Christensen and Tim Dominik Maurer.

Short Description

  • Lecture 1: A Deterministic General-Equilibrium Life-cycle Model
    • This lecture numerically solves a deterministic multiperiod overlapping-generations model in general equilibrium.
    • In excerise 1 you are asked to introduce a pension scheme to the model (Solutions are provided).
  • Lecture 2: Dynamic Transition Path
    • This lecture solve for the transition path from a pre to a post-shock steady state.
    • We consider an MIT-policy-shock that introduces a pension scheme.
  • Lecture 3: A Partial-Equilibrium Life-cycle Model with Income Risk
    • This lecture solves and simulates a life-cycle model with income risk in partial equilibrium using backward induction.
  • Lecture 4: The Endogenous Grid Method
    • This lecture solves the model in Lecture 3 using the more efficient Endogenous Grid Method.

COURSE PREREQUISITES

The course requires basic knowledge of:

SOFTWARE REQUIREMENTS

This module requires the following:

  • Python 3.8
  • Jupyter Notebook
  • We suggest to download the Python environment Anaconda
    • It includes Python, Jupyter Notebooks, Spyder (Python Editor) and more...

Guides

For guides on how to run the code of each individual lecture, each lecture folder contains a separate readme.md file.

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This course teaches you computational methods to solve deterministic as well as stochastic life-cycle models with overlapping generations using Python.

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