MSCMT: Multivariate Synthetic Control Method Using Time Series

Multivariate Synthetic Control Method Using Time Series. Three generalizations of the synthetic control method (which has already an implementation in package 'Synth') are implemented: first, 'MSCMT' allows for using multiple outcome variables, second, time series can be supplied as economic predictors, and third, a well-defined cross-validation approach can be used. Much effort has been taken to make the implementation as stable as possible (including edge cases) without losing computational efficiency.

Version: 1.3.0
Depends: R (≥ 3.2.0)
Imports: stats, utils, parallel, lpSolve, ggplot2, lpSolveAPI, Rglpk, Rdpack
Suggests: Synth, DEoptim, rgenoud, DEoptimR, GenSA, GA, soma, cmaes, Rmalschains, NMOF, nloptr, hydroPSO, pso, LowRankQP, kernlab, reshape, knitr, rmarkdown
Published: 2017-08-17
Author: Martin Becker [aut, cre], Stefan Klößner [aut], Karline Soetaert [com], LAPACK authors [cph]
Maintainer: Martin Becker <martin.becker at>
License: GPL-2 | GPL-3 [expanded from: GPL]
Copyright: inst/COPYRIGHTS
MSCMT copyright details
NeedsCompilation: yes
Materials: NEWS
CRAN checks: MSCMT results


Reference manual: MSCMT.pdf
Vignettes: Checking and Improving Results of package Synth
SCM Using Time Series
Working with package MSCMT
Package source: MSCMT_1.3.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: MSCMT_1.2.0.tgz
OS X Mavericks binaries: r-oldrel: MSCMT_1.3.0.tgz
Old sources: MSCMT archive


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