About

QuantEcon is a nonprofit organization dedicated to improving economic modeling by enhancing computational tools for economists. 

Our activities include

  • developing and facilitating the development of open source software for economic modeling, and
  • building open, collaborative platforms for sharing, discussing and documenting open source software

Development is centered on open source scientific computing environments such as Python, R and Julia and is hosted on github

QuantEcon is a NumFocus and PSL Fiscally Sponsored Project.

Contact

Send feedback to contact@quantecon.org

Join the Discourse forum

You can reach out to the QuantEcon team via the Discourse forum.

The forum is a good place to ask questions, get guidance on contributing to the project, or request new lectures or library features.

QuantEcon is sponsored by NumFOCUS, a U.S. 501(c)(3) nonprofit organization that supports and promotes world-class, innovative, open source scientific software.

Through NumFOCUS, QuantEcon can receive tax-deductible donations to help support ongoing development.

Your donations will go towards:

  • developing and facilitating the development of open source software for economic modeling, and
  • building open, collaborative platforms for sharing, discussing and documenting open source software

To support the QuantEcon project:

Develop and contribute code

We welcome submission of algorithms and high quality code to QuantEcon.py and QuantEcon.jl on all topics in quantitative economics.

Write a notebook

If you’ve written code related to quantitative economics and want to share it with the community, we encourage you to submit it as a Jupyter notebook to QuantEcon Notes.

Contributing to the lectures

QuantEcon develops and supports the following lecture series for quantitative economics and datascience.

Bug fixes or small updates are welcome as pull requests (PR).

Some PR requirements:

  1. A PR should address just one lecture
  2. Python lectures should execute with the latest Anaconda environment. Please update and check prior to submitting your PR.

Information on contributing to the python lectures can be found here