microsynth: Synthetic Control Methods for Disaggregated and Micro-Level Data in R

2021
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.
JOURNAL OF STATISTICAL SOFTWARE
卷号:97|期号:2
ISSN:1548-7660
收录类型
SSCI
发表日期
2021
学科领域
循证社会科学-方法
国家
美国
语种
英语
DOI
10.18637/jss.v097.i02
其他关键词
ESTIMATORS
资助机构
RAND's Center for Causal Inference
资助信息
The authors would like to thank RAND's Center for Causal Inference for generously providing funds to support the development of microsynth.
被引频次(WOS)
2
被引更新日期
2022-01
来源机构
RAND Corporation RAND Corporation Pardee RAND Graduate School
关键词
synthetic control methods micro-level causal inference Synth program evaluation