scpi-package {scpi} | R Documentation |
scpi
: A Package to Compute Synthetic Control Prediction Intervals With Multiple Treated Units and Staggered Adoption
Description
The package implements estimation, inference procedures, and produces plots for Synthetic Control (SC) methods using least squares, lasso, ridge, or simplex-type constraints. Uncertainty is quantified using prediction intervals according to Cattaneo et al. (2021) and Cattaneo et al. (2025).
Included functions are: scdata and scdataMulti for data preparation, scest for point estimation, scpi for inference procedures, and scplot and scplotMulti for plots.
print()
and summary()
methods are available for scest
and scpi
.
Companion Stata and Python packages are described in Cattaneo et al. (2025).
Related Stata, R, and Python packages useful for inference in SC designs are described in the following website:
https://nppackages.github.io/scpi/
For an introduction to synthetic control methods, see Abadie (2021) and references therein.
Author(s)
Matias Cattaneo, Princeton University. cattaneo@princeton.edu.
Yingjie Feng, Tsinghua University. fengyj@sem.tsinghua.edu.cn.
Filippo Palomba, Princeton University (maintainer). fpalomba@princeton.edu.
Rocio Titiunik, Princeton University. titiunik@princeton.edu.
References
Abadie A (2021).
“Using Synthetic Controls: Feasibility, Data Requirements, and Methodological Aspects.”
Journal of Economic Literature, 59(2), 391–425.
ISSN 0022-0515, doi:10.1257/jel.20191450.
Cattaneo MD, Feng Y, Palomba F, Titiunik R (2025).
“Uncertainty Quantification in Synthetic Controls with Staggered Treatment Adoption.”
Review of Economics and Statistics, 1–46.
ISSN 0034-6535, 1530-9142, doi:10.1162/rest_a_01588.
Cattaneo MD, Feng Y, Palomba F, Titiunik R (2025).
“scpi: Uncertainty Quantification for Synthetic Control Methods.”
Journal of Statistical Software, 113(2), 1–38.
doi:10.18637/jss.v113.i01.
Cattaneo MD, Feng Y, Titiunik R (2021).
“Prediction Intervals for Synthetic Control Methods.”
Journal of the American Statistical Association, 116(536), 1865–1880.
ISSN 0162-1459, doi:10.1080/01621459.2021.1979561.
See Also
Useful links: