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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


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


Matias D. Cattaneo (

Yingjie Feng (

Filippo Palomba (

Rocio Titiunik (



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


  • 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.

Software and Implementation

Technical and Methodological

  • 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.


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