Synthetic Control Methods

The synthetic control method enables researchers to estimate causal effects by constructing a synthetic version of a treatment unit through a weighted combination of control units. It is implemented as both an R package and a Stata routine, based on the methods developed in the following papers Abadie, Diamond, and Hainmueller (2010), Abadie, Diamond, and Hainmueller (2015), and Abadie, Diamond, and Hainmueller (2011). This work was awarded the Gosnell Prize for Excellence in Political Methodology.

→ Read the explainer — a self-contained tutorial on the synthetic control method for R and Stata users, with the canonical Proposition 99 example worked end-to-end.

Source on GitHub: j-hai/Synth (R package) · j-hai/synth-stata (Stata routine).

What’s new in Synth 1.2-0 (May 2026)

Version 1.2-0 is the development version on GitHub; install it with remotes::install_github("j-hai/Synth") (CRAN currently has 1.1-10). It adds a substantial set of user-facing features:

• Built-in inference. synth_inference() returns split-conformal (Chernozhukov–Wuthrich–Zhu 2021) or parametric prediction intervals around the synthetic counterfactual. synth_placebos() plus synth_mspe_test() give the canonical Abadie–Diamond–Hainmueller (2010) placebo p-value in two calls.
• Ergonomic data prep. synth_data() is a one-line wrapper around dataprep() for the common case (panel + treated unit + treatment date + auto-controls).
• Alternative QP backends. Optional quadopt = "cvxr" (CVXR + CLARABEL) and quadopt = "torch" (Frank-Wolfe simplex LS via the torch package, with CPU/CUDA/MPS support). Both live in Suggests: — no required dependency.
• ggplot2 support. autoplot() methods on the inference and placebo objects produce publication-quality figures.
• Cross-platform parallel placebos. parallel = TRUE does the right thing on Windows (PSOCK cluster) and unix-likes (forks).
• Two vignettes. vignette("synth-quickstart") for a 5-minute intro and vignette("inference") for the inference deep dive on the Proposition 99 example. A GitHub install includes them only with remotes::install_github("j-hai/Synth", build_vignettes = TRUE), which needs knitr, rmarkdown, and pandoc.
• Fixes and renames (October 2026). dataprep() labels now follow the data when controls or periods are given out of order, predictors.op is applied to control units as well as the treated unit (results change only for operators other than "mean"), and invalid operators stop with a clear message. The placebo functions are now synth_placebos(), synth_mspe_test(), and synth_mspe_plot(), with a plot() method; the old names (generate_placebos() etc.) clashed with SCtools.

Worked example: California’s Proposition 99

The 1988 California cigarette-tax measure is a textbook case for the synthetic control method. With the new API the entire workflow is seven function calls:

library(Synth); library(ggplot2)
data(smoking)

dp <- synth_data(
  panel              = smoking,
  outcome            = "cigsale",
  unit_col           = "state_id",
  time_col           = "year",
  treated            = "California",
  treatment_time     = 1989,
  predictors         = c("lnincome", "age15to24", "retprice", "beer"),
  special_predictors = list(
    list("cigsale", 1988, "mean"),
    list("cigsale", 1980, "mean"),
    list("cigsale", 1975, "mean")),
  unit_names_col     = "state_name"
)

fit  <- synth(dp)
inf  <- synth_inference(fit, dp, method = "conformal", alpha = 0.10)
pl   <- synth_placebos(fit, dp)
test <- synth_mspe_test(pl)  # one-sided p-value = 0.026

autoplot(inf)                # 90% conformal band
autoplot(pl, mspe_threshold = 5)  # placebo overlay

The synthetic California puts about 90% of weight on Utah, Nevada, Montana, and Connecticut (close to the mix in the published Proposition 99 paper). Post / pre MSPE ratio is 128 and the placebo p-value is 0.026 — the effect is unusually large relative to other states.

The current CRAN release (1.1-10, April 2026) addressed quadopt = "LowRankQP" fail-fast, the missing-data check in dataprep(), quieter defaults, and a path.plot() y-axis fix for negative-valued series.

The Stata routine was likewise updated in April 2026 to version 0.0.8 with native Apple Silicon support (the optimizer plugin now ships an arm64 Mach-O slice; previously it failed to load on M-series Macs running Stata 17+ natively), portable C source that compiles cleanly on macOS / Linux / Windows, and typo / version-declaration cleanup.

Synth for R — also on GitHub

Synth for Stata — also on GitHub