mspe_ratio_pval: Permutation Inference via MSPE Ratio for SCM

In coresynth: Fast and Unified Synthetic Control Methods

Permutation Inference via MSPE Ratio for SCM

Description

Computes the Abadie et al. (2010) / Abadie (2021) permutation p-value. For each control unit, a leave-one-out synthetic control is fitted.

Usage

mspe_ratio_pval(
  fit,
  mspe_threshold = 0,
  max_iter = 100L,
  tol = 1e-04,
  use_covariates = NULL,
  alternative = c("two.sided", "greater", "less")
)

Arguments

fit	A coresynth object from scm_fit() with method = "scm".
mspe_threshold	Minimum pre-treatment MSPE for including a control unit in the two-sided test. Ignored for one-sided tests. Default: 0 (no filtering).
max_iter	Passed to scm_placebo_cpp() (outcomes-only fits) or scm_placebo_x_cpp() (covariate fits). Default 100L.
tol	Passed to scm_placebo_cpp() or scm_placebo_x_cpp(). Default 1e-4.
use_covariates	Controls which predictor specification the placebo refits use. Default NULL (recommended) mirrors the treated fit: if the fit was estimated with a predictors specification, each placebo unit is refit with that same specification (the Abadie et al. 2010 / Synth convention – treated and placebo statistics are computed under one common spec); outcomes-only fits use the fast C++ outcomes-only placebo. Set TRUE/FALSE to force either path; note that FALSE on a covariate fit compares a covariate-based treated statistic against outcomes-only placebo statistics, which breaks the exchangeability logic of the permutation test.
alternative	Direction of the alternative hypothesis: "two.sided" (default) uses the MSPE ratio statistic; "greater" tests whether the treatment increased the outcome; "less" tests whether the treatment decreased the outcome. One-sided tests use the signed ATT as the test statistic.

Details

When alternative = "two.sided" (default), the test statistic is the post/pre MSPE ratio, following Abadie et al. (2010). When alternative = "greater" or "less", the test statistic is the signed average post-treatment gap (ATT), giving a one-sided permutation test as recommended by Abadie (2021) S.3.5 for improved power when the direction of the treatment effect is known.

The placebo refits mirror the treated fit's outer optimiser and evaluation window: a fit estimated with the multi-start outer search (v_optim = "multistart", or the "auto" default with predictors) or with a v_window runs every placebo unit through the same configuration, keeping the permutation statistic exchangeable across units.

Value

An object of class scm_placebo (a list) with:

• p_value: Permutation p-value between 0 and 1

• mspe_ratio_treated: MSPE_post / MSPE_pre for the treated unit (two.sided only)

• mspe_ratios_all: Named numeric vector (treated first, then controls); two.sided only

• placebo_effects: Named N_co-vector of placebo ATT estimates

• treated_effect: ATT estimate for the treated unit

• n_placebo_used: Number of control units used

• gaps: T x N_co matrix of placebo gap paths (unit minus its synthetic control over all periods), for the Abadie et al. (2010) Figure 4-7 plot

• treated_gap: T-vector of the treated unit's gap path

• mspe_pre_treated, mspe_pre_placebo: Pre-treatment MSPEs used for the relative pruning rule in plot.scm_placebo()

• times, T_pre: Time axis metadata for plotting

See Also

plot.scm_placebo() for the placebo gap and MSPE ratio plots.

coresynth documentation built on Aug. 28, 2026, 1:06 a.m.