PanelMatch-package {PanelMatch} | R Documentation |
Matching Methods for Causal Inference with Time-Series Cross-Sectional Data
Description
Implements a set of methodological tools that enable researchers to apply matching methods to time-series cross-sectional data. Imai, Kim, and Wang (2021) 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.
Details
Package: | PanelMatch |
Type: | Package |
Version: | 2.0.0- |
Date: | 2021-09-02 |
License: | GPL (>= 3) |
Author(s)
In Song Kim <insong@mit.edu>, Erik Wang <haixiao@Princeton.edu>, Adam Rauh <amrauh@umich.edu>, and Kosuke Imai <imai@harvard.edu>
Maintainer: In Song Kim insong@mit.edu
References
Imai, Kosuke, In Song Kim and Erik Wang. (2021)