The scpi_pkg
package provides Python implementations of estimation and inference procedures for Synthetic Control methods.
Matias D. Cattaneo ([email protected])
Yingjie Feng ([email protected])
Filippo Palomba ([email protected])
Rocio Titiunik ([email protected])
https://nppackages.github.io/scpi/
To install/update use pip
pip install scpi_pkg
from from scpi_pkg.scdata import scdata
from from scpi_pkg.scdataMulti import scdataMulti
from scpi_pkg.scest import scest
from scpi_pkg.scpi import scpi
from scpi_pkg.scplot import scplot
from scpi_pkg.scplotMulti import scplotMulti
- Replication: Germany reunification example.
- cvxpy (>= 1.1.18)
- dask (>= 2021.04.0)
- ecos (>= 2.0.7)
- luddite (>= 1.0.2)
- numpy (>= 1.20.1)
- pandas (>= 1.5.0)
- plotnine (>= 0.8.0)
- scikit-learn (>= 0.24.1)
- scipy (>= 1.7.1)
- statsmodels (>= 0.12.2)
For overviews and introductions, see nppackages website.
- Cattaneo, Feng, Palomba, and Titiunik (2022) scpi: Uncertainty Quantification for Synthetic Control Estimators.
- Cattaneo, Feng, and Titiunik (2021): Prediction Intervals for Synthetic Control Methods.
<br>
Journal of the American Statistical Association. - Cattaneo, Feng, Palomba, and Titiunik (2022): Uncertainty Quantification in Synthetic Controls with Staggered Treatment Adoption, working paper.
<br><br>