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The package computes point estimates and prediction intervals for Synthetic Control methods as proposed in Cattaneo, Feng, and Titiunik (2021).

Project description

SCPI_PKG

The scpi_pkg package provides Python implementations of estimation and inference procedures for Synthetic Control methods.

Authors

Matias D. Cattaneo (cattaneo@princeton.edu)

Yingjie Feng (fengyj@sem.tsinghua.edu.cn)

Filippo Palomba (fpalomba@princeton.edu)

Rocio Titiunik (titiunik@princeton.edu)

Website

https://nppackages.github.io/scpi/

Installation

To install/update use pip

pip install scpi_pkg

Usage

from from scpi_pkg.scdata import scdata
from scpi_pkg.scest import scest
from scpi_pkg.scpi import scpi
from scpi_pkg.scplot import scplot

Dependencies

  • cvxpy (>= 1.1.18)
  • dask (>= 2021.04.0)
  • nlopt (>= 2.7.0)
  • numpy (>= 1.20.1)
  • pandas (>= 1.2.4)
  • plotnine (>= 0.8.0)
  • scikit-learn (>= 0.24.1)
  • scipy (>= 1.7.1)
  • statsmodels (>= 0.12.2)

References

For overviews and introductions, see nppackages website.

Software and Implementation

Technical and Methodological

  • Cattaneo, Feng, and Titiunik (2021): Prediction Intervals for Synthetic Control Methods.
    Journal of the American Statistical Association.

  • Cattaneo, Feng, Palomba, and Titiunik (2022): Uncertainty Quantification in Synthetic Controls with Staggered Treatment Adoption, working paper.



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