Authors: In Song Kim ([email protected]), Adam Rauh ([email protected]), Erik Wang ([email protected]), Kosuke Imai ([email protected])
PanelMatch is an R package implementing a set of methodological tools proposed by Imai, Kim, and Wang (2021) that enables researchers to apply matching methods for causal inference on time-series cross-sectional data with binary treatments. The package includes implementations of matching methods based on propensity scores and Mahalanobis distance, as well as weighting methods. PanelMatch enables users to easily calculate a variety of possible quantities of interest, along with standard errors. The software is flexible, allowing users to tune the matching, refinement, and estimation procedures with a large number of parameters. The package also offers a variety of visualization and diagnostic tools for researchers to better understand their data and assess their results.
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