QuantEcon/QuantEcon.py
QuantEcon/QuantEcon.py has 2,416 GitHub stars and 2,292 forks. GitHot measured 0 stars in 24 hours. Last checked 2026-11-07 21:14 UTC. Last push 2026-11-02.
A community based Python library for quantitative economics
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README.md
OriginalQuantEcon.py
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')
Installation
Install QuantEcon.py from PyPI:
pip install quantecon
If you use conda, install from conda-forge (Anaconda Distribution is not required):
conda install -c conda-forge quantecon
Usage
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
Examples and Sample Code
Many examples of QuantEcon.py in action can be found at Quantitative Economics. See also the
QuantEcon.py is supported financially by the Alfred P. Sloan Foundation and is part of the QuantEcon organization.
Downloading the quantecon Repository
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
cd QuantEcon.py
pip install .
(To learn the basics about setting up Git see this link.)
Citation
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 = {10.21105/joss.05585},
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},
url = {https://joss.theoj.org/papers/10.21105/joss.05585}
}
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