A high performance, open source Python code library for economics

  from quantecon.markov import DiscreteDP
  aiyagari_ddp = DiscreteDP(R, Q, beta)
  results = aiyagari_ddp.solve(method='policy_iteration')

Before installing quantecon we recommend you install the Anaconda Python distribution, which includes a full suite of scientific python tools. Note: quantecon is now only supporting Python version 3.5+. This is mainly to allow code to be written taking full advantage of new features such as using the @ symbol for matrix multiplication. Therefore please install the latest Python 3 Anaconda distribution.

Next you can install quantecon by opening a terminal prompt and typing

pip install quantecon

Once quantecon has been installed you should be able to import it as follows:

import quantecon as qe

You can check the version by running

print(qe.__version__)

If your version is below what’s available on PyPI then it is time to upgrade. This can be done by running

pip install --upgrade quantecon

Many examples of QuantEcon.py in action can be found at Quantitative Economics. See also the

• Documentation
• Notebook gallery

QuantEcon.py is supported financially by the Alfred P. Sloan Foundation and is part of the QuantEcon organization.

An alternative is to download the sourcecode of the quantecon package and install it manually from the github repository. For example, if you have git installed type

git clone https://github.com/QuantEcon/QuantEcon.py

Once you have downloaded the source files then the package can be installed by running

pip install flit
flit install

(To learn the basics about setting up Git see this link.)

QuantEcon.py is MIT licensed, so you are free to use it without any charge and restriction. If it is convenient for you, please cite QuantEcon.py when using it in your work and also consider contributing all your changes back, so that we can incorporate it.

A BibTeX entry for LaTeX users is

@article{10.21105/joss.05585,
author = {Batista, Quentin and Coleman, Chase and Furusawa, Yuya and Hu, Shu and Lunagariya, Smit and Lyon, Spencer and McKay, Matthew and Oyama, Daisuke and Sargent, Thomas J. and Shi, Zejin and Stachurski, John and Winant, Pablo and Watkins, Natasha and Yang, Ziyue and Zhang, Hengcheng},
doi = {10.5281/zenodo.10345102},
title = {QuantEcon.py: A community based Python library for quantitative economics},
year = {2024},
journal = {Journal of Open Source Software},
volume = {9},
number = {93},
pages = {5585}
}