SparseSC Estimator
GeoSC’s only implemented estimator selector is sparsesc. SparseSC learns a
regularised match space and donor weights from pre-treatment outcomes and
optional covariates.
Conceptually, it chooses unit weights and match-space weights to reduce treated-versus-synthetic pre-period discrepancy subject to regularisation:
$$ (\widehat W, \widehat V) = \arg\min_{W,V} \left|Y^{pre}{\mathcal T}-Y^{pre}{\mathcal C}W\right|_V^2
- \mathcal P_W(W) + \mathcal P_V(V). $$
This is an explanatory simplification, not a line-by-line restatement of every
vendored optimisation path. With sparse_sc_fast_estimation: true, GeoSC calls
the vendored fast path, which uses RidgeCV-backed match-space machinery. The
full path uses SparseSC’s penalty search and coordinate-descent machinery.
Regularisation controls overfit; it does not make an ineligible donor valid.
Inspect pre-fit, fitted unit weights, weight concentration, and sensitivity to
substantive donor exclusions. The selected_weight from GeoSC’s donor stage is
not
; fitted weights are exposed in inference diagnostics.
The package vendors a pinned, locally governed SparseSC fork. See Vendored Dependencies for provenance.