Synthetic Control Methods

The scpi package implements estimation, inference and graphical procedures for synthetic control methods, including designs with a single treated unit, multiple treated units and staggered treatment adoption.

• scdata: data preparation for synthetic control estimation with one treated unit.
• scdataMulti: data preparation for multiple treated units and staggered adoption.
• scest: synthetic control point estimation.
• scpi: synthetic control prediction intervals and related uncertainty summaries.
• scplot: plots for single-treated-unit synthetic control results.
• scplotMulti: plots for multiple-treated-unit and staggered-adoption results.

Python Implementation

To install/update in Python type:

pip install scpi_pkg

• Help: PyPI repository.

• Replication: py-script, plot illustration, data.

• Illustration Staggered Adoption: py-script, plot illustration.

R Implementation

To install/update in R type:

install.packages('scpi')

• Help: R Manual, CRAN repository.

• Replication: R-script, plot illustration, data.

• Illustration Staggered Adoption: R-script, plot illustration.

Stata Implementation

The Stata implementation relies on Python, which needs to be available in the system. After Python is installed and linked to Stata, install the required Python packages:

pip install luddite scpi_pkg

To install/update in Stata type:

net install grc1leg, from("http://www.stata.com/users/vwiggins/") replace force
net install scpi, from(https://raw.githubusercontent.com/nppackages/scpi/main/stata) replace force

• Help: scdata, scdatamulti, scest, scpi, scplot, scplotmulti.

• Replication files: do-file, plot illustration, data.

• Illustration Staggered Adoption: do-file, plot illustration.

References

Software and Implementation

• Cattaneo, Feng, Palomba and Titiunik (2025): scpi: Uncertainty Quantification for Synthetic Control Methods.
  Journal of Statistical Software 113(1): 1-38.

Technical and Methodological

• Cattaneo, Feng, Palomba and Titiunik (2027): Uncertainty Quantification in Synthetic Controls with Staggered Treatment Adoption.
  Review of Economics and Statistics, forthcoming.
  Supplemental

• Cattaneo, Feng and Titiunik (2021): Prediction Intervals for Synthetic Control Methods.
  Journal of the American Statistical Association 116(536): 1865-1880.
  Supplemental

Funding

This work was supported by the National Science Foundation through grants SES-1947805, SES-2019432, and SES-2241575, and by the National Institutes of Health through grant R01 GM072611-16.