skillmodels
Introduction
Welcome to skillmodels, a Python implementation of estimators for skill formation models. The econometrics of skill formation models is a very active field and several estimators were proposed. None of them is implemented in standard econometrics packages.
Installation
Warning: To run skillmodels you need to install jax and jaxlib. At the time of writing, in most use cases, it is faster on a CPU than on a GPU, so it should be sufficient to install the CPU version, which is available on all platforms. In any case, for installation of jax and jaxlib, please consult the jax docs.
Skillmodels can be installed via PyPI or via GitHub. To do so, type the following in a terminal:
$ pip install skillmodels
or, for the latest development version, type:
$ pip install git+https://github.com/OpenSourceEconomics/skillmodels.git
Documentation
The documentation is hosted at readthedocs
Developing
We use pixi for our local development environment. If you want to work with or extend the skillmodels code base you can run the tests using
$ git clone https://github.com/OpenSourceEconomics/skillmodels.git
$ pixi run tests
This will install the development environment and run the tests. You can run mypy using
$ pixi run mypy
Before committing, install the pre-commit hooks using
$ pre-commit install
Documentation
You can build the documentation locally. After cloning the repository you can cd to the docs directory and type:
$ make html
Citation
It took countless hours to write skillmodels. I make it available under a very permissive license in the hope that it helps other people to do great research that advances our knowledge about the formation of cognitive and noncognitive skills. If you find skillmodels helpful, please don't forget to cite it. Below you can find the bibtex entry for a suggested citation. The suggested citation will be updated once the code becomes part of a published paper.
@Unpublished{Gabler2024,
Title = {A Python Library to Estimate Nonlinear Dynamic Latent Factor Models},
Author = {Janos Gabler},
Year = {2024},
Url = {https://github.com/OpenSourceEconomics/skillmodels}
}
Feedback
If you find skillmodels helpful for research or teaching, please let me know. If you encounter any problems with the installation or while using skillmodels, please complain or open an issue at GitHub
Metadata
Release files for skillmodels 0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| skillmodels-0.1.2.tar.gz | 1.3 MB | With provenance | Details for skillmodels-0.1.2.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| skillmodels-0.1.2-py3-none-any.whl | Python 3 | none | any | Details for skillmodels-0.1.2-py3-none-any.whl |
Total release size: 2.7 MB
Release files / skillmodels-0.1.2.tar.gz
| Download URL | skillmodels-0.1.2.tar.gz |
|---|---|
| Size | 1.3 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / skillmodels-0.1.2-py3-none-any.whl
| Download URL | skillmodels-0.1.2-py3-none-any.whl |
|---|---|
| Size | 1.4 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.14
|
Provenance
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PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 29, 2026.
Transparency logSecurity for skillmodels 0.1.2
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
Full provenance
All 2 files in this release have been uploaded with provenance metadata.
Attestation for skillmodels-0.1.2.tar.gz
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 29, 2026.
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