Great, you are interested in contributing to the package.
To get acquainted with the code base, you can check out our issue tracker for some immediate and clearly defined tasks. For more involved contributions, please see our roadmap below. All submissions are required to follow this project-agnostic contribution guide
We aim for improvements to the
grmpy package in three domains: Objects of Interest, Estimation Methods, and Numerical Methods.
Objects of Interest¶
- adding marginal surplus and marginal cost parameters as presented by Eisenhauer et al. ()
- implementing polynomial and local-instrumental variable estimation as outlined by Heckman et al. ()
- exploring alternative optimization algorithms to address large estimation tasks