Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Michael W. Robbins, Steven Davenport
Title: microsynth: Synthetic Control Methods for Disaggregated and Micro-Level Data in R
Abstract: The R package microsynth has been developed for implementation of the synthetic control methodology for comparative case studies involving micro- or meso-level data. The methodology implemented within microsynth is designed to assess the efficacy of a treatment or intervention within a well-defined geographic region that is itself a composite of several smaller regions (where data are available at the more granular level for comparison regions as well). The effect of the intervention on one or more time-varying outcomes is evaluated by determining a synthetic control region that resembles the treatment region across pre-intervention values of the outcome(s) and time-invariant covariates and that is a weighted composite of many untreated comparison regions. The microsynth procedure includes functionality that enables its user to (1) calculate weights for synthetic control, (2) tabulate results for statistical inferences, and (3) create time series plots of outcomes for treatment and synthetic control. In this article, microsynth is described in detail and its application is illustrated using data from a drug market intervention in Seattle, WA.

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Paper: microsynth: Synthetic Control Methods for Disaggregated and Micro-Level Data in R     Download PDF (Downloads: 109)
microsynth_2.0.17.tar.gz: R source package Download (Downloads: 6; 2MB)
v97i02.R: R replication code Download (Downloads: 9; 4KB)

DOI: 10.18637/jss.v097.i02

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.