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scpi

Prediction Intervals for Synthetic Control Methods with Multiple Treated Units and Staggered Adoption

Installation

About

Implementation of prediction and inference procedures for Synthetic Control methods using least square, lasso, ridge, or simplex-type constraints. Uncertainty is quantified with prediction intervals as developed in Cattaneo, Feng, and Titiunik (2021) for a single treated unit and in Cattaneo, Feng, Palomba, and Titiunik (2023) for multiple treated units and staggered adoption. More details about the software implementation can be found in Cattaneo, Feng, Palomba, and Titiunik (2022) .

nppackages.github.io/scpi/

Key Metrics

Version 2.2.5
R ≥ 4.1.0
Published 2023-11-01 178 days ago
Needs compilation? no
License GPL-2
CRAN checks scpi results

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Maintainer

Maintainer

Filippo Palomba

fpalomba@princeton.edu

Authors

Matias Cattaneo

aut

Yingjie Feng

aut

Filippo Palomba

aut / cre

Rocio Titiunik

aut

Material

Reference manual
Package source

In Views

CausalInference

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

scpi archive

Depends

R ≥ 4.1.0

Imports

abind ≥ 1.4.5
CVXR ≥ 1.0-10
doSNOW ≥ 1.0.19
dplyr ≥ 1.0.7
ECOSolveR ≥ 0.5.4
fastDummies ≥ 1.6.3
foreach ≥ 1.5.1
ggplot2 ≥ 3.3.3
magrittr ≥ 2.0.1
MASS ≥ 7.3
Matrix ≥ 1.3.3
methods ≥ 4.1.0
parallel ≥ 4.1.0
purrr ≥ 0.3.4
Qtools ≥ 1.5.6
reshape2 ≥1.4.4
rlang ≥ 0.4.11
stats ≥ 4.1.0
stringr ≥1.4.0
tibble ≥ 3.1.2
tidyr ≥ 1.1.3
utils ≥ 4.1.1

Suggests

testthat ≥ 3.0.0