Skip to contents

Leave-One-Out Donor Robustness for SCM

Source: R/scm.R
loo_donors.Rd

Iteratively re-estimates the synthetic control excluding one contributing donor at a time, holding the predictor weights V fixed at their baseline values (Abadie, Diamond & Hainmueller 2015, footnote 20). The spread of the leave-one-out ATT estimates shows how much the result hinges on any single donor.

Usage

loo_donors(fit, weight_threshold = 1e-06)

Arguments

fit

A sharp coresynth object from scm_fit() with method = "scm".

weight_threshold

Only donors whose baseline weight exceeds this value are dropped (removing a zero-weight donor cannot change the fit). Default 1e-6.

Value

A list with:

  • att_original: baseline ATT

  • results: data.frame with one row per excluded donor (donor, weight, att_loo)

  • att_range: range of the leave-one-out ATTs

Details

For penalised fits (lambda_pen used), the same penalty is re-applied in each leave-one-out QP.

See also

placebo_in_time(), mspe_ratio_pval()