Package: Synth 1.2-0

Synth: Synthetic Control Group Method for Comparative Case Studies

Implements the synthetic control group method for comparative case studies as described in Abadie and Gardeazabal (2003) and Abadie, Diamond, and Hainmueller (2010, 2011, 2014). The synthetic control method allows for effect estimation in settings where a single unit (a state, country, firm, etc.) is exposed to an event or intervention. It provides a data-driven procedure to construct synthetic control units based on a weighted combination of comparison units that approximates the characteristics of the unit that is exposed to the intervention. A combination of comparison units often provides a better comparison for the unit exposed to the intervention than any comparison unit alone.

Authors:Jens Hainmueller [aut, cre], Alexis Diamond [aut]

Synth_1.2-0.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
Synth/json (API)

# Install 'Synth' in R:
install.packages('Synth', repos = c('https://j-hai.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/j-hai/synth/issues

Datasets:
  • basque - Panel Data from Spanish Regions to demonstrate the use of the Synthetic Control Method
  • smoking - Annual State-Level Cigarette Sales in the United States, 1970-2000
  • synth.data - Panel Data to demonstrate the use of the Synthetic Control Method

On CRAN:

Conda:

8.89 score 3 stars 1 packages 938 scripts 2.1k downloads 9 mentions 13 exports 6 dependencies

Last updated from:b3e2eaa6eb. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK436
source / vignettesOK408
linux-releaseOK480
macos-releaseOK336
macos-oldrelOK329
windows-develOK459
windows-releaseOK446
windows-oldrelOK324
wasm-releaseOK95

Exports:collect.optimxdataprepfn.Vgaps.plotpath.plotspec.pred.funcsynthsynth_datasynth_inferencesynth_mspe_plotsynth_mspe_testsynth_placebossynth.tab

Dependencies:kernlabnloptrnumDerivoptimxpracmargenoud

Inference for Synthetic Control Estimators
Overview | Which inference method should I use? | 1. Build the synthetic control | 2. Prediction intervals: synth_inference() | Split-conformal (default) | Parametric (Gaussian residuals) | When to use which | 3. Placebo inference | Generate the placebos | Test | Plot the placebo distribution | Plot the placebo gaps | 4. Combining prediction intervals and placebos | Alternative QP backends | See also | References
Rendered frominference.Rmdusingknitr::rmarkdown

Last update: 2026-10-04
Started: 2026-05-05

Quickstart: building a synthetic control with Synth
1. Build the inputs | 2. Fit the synthetic control | 3. Inspect | 4. What next?
Rendered fromsynth-quickstart.Rmdusingknitr::rmarkdown

Last update: 2026-10-04
Started: 2026-05-05