sc_estimator: solving for standard synthetic control weights

In maxkllgg/masc: Matching and Synthetic Controls Estimator

Description

Solves for synthetic control weights up to the designated treatment period, using only information in the outcome paths (no other covariates).

Usage

sc_estimator(
  treated,
  donors,
  treated.covariates,
  donors.covariates,
  treatment,
  nogurobi = FALSE,
  psdtol = 1e+06,
  BarConvTol = 1e-08,
  BarIterLimit = 1e+05,
  sigf.ipop = 5,
  margin.ipop = 5e-04,
  ...
)

Arguments

donors	See masc.
nogurobi	A logical value. If true, uses LowRankQP to solve the synthetic control estimator, rather than gurobi.
treated:	See masc.
covariates.donors:	See masc.
treated.donors:	See masc.
treatment:	An integer. The period T' in which forecasting begins (either the true treatment period or the first period after a cross-validation fold).

Value

A list. The named component weights.sc contains the vector of synthetic control weights. Weights are ordered in the same manner as the columns in Z0. The objval.sc component contains the objective value (pre-period fit) of the synthetic control.

References

Kellogg, M., M. Mogstad, G. Pouliot, and A. Torgovitsky. Combining Matching and Synthetic Control to Trade off Biases from Extrapolation and Interpolation. Working Paper, 2019.

See Also

Other masc functions: cv_masc(), masc_by_phi(), masc(), solve_masc()

maxkllgg/masc documentation built on Sept. 7, 2021, 8:44 a.m.