PanelMatch: Matching Methods for Causal Inference with Time-Series Cross-Sectional Data

Implements a set of methodological tools that enable researchers to apply matching methods to time-series cross-sectional data. Imai, Kim, and Wang (2018) <> proposes a nonparametric generalization of the difference-in-differences estimator, which does not rely on the linearity assumption as often done in practice. Researchers first select a method of matching each treated observation for a given unit in a particular time period with control observations from other units in the same time period that have a similar treatment and covariate history. These methods include standard matching methods based on propensity score and Mahalanobis distance, as well as weighting methods. Once matching is done, both short-term and long-term average treatment effects for the treated can be estimated with standard errors. The package also offers a visualization technique that allows researchers to assess the quality of matches by examining the resulting covariate balance.

Version: 1.0.0
Depends: R (≥ 2.14.0)
Imports: Rcpp (≥ 0.12.5), data.table, ggplot2, CBPS, stats, graphics, grDevices, MASS, Matrix, methods
LinkingTo: RcppArmadillo, Rcpp, RcppEigen
Suggests: knitr, rmarkdown, testthat (≥ 2.1.0)
Published: 2020-02-28
Author: In Song Kim [aut, cre], Adam Rauh [aut], Erik Wang [aut], Kosuke Imai [aut]
Maintainer: In Song Kim <insong at>
License: GPL (≥ 3)
NeedsCompilation: yes
SystemRequirements: C++11
CRAN checks: PanelMatch results


Reference manual: PanelMatch.pdf
Vignettes: Using PanelMatch
Package source: PanelMatch_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: PanelMatch_1.0.0.tgz, r-oldrel: PanelMatch_1.0.0.tgz


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