PanelMatch-package: Matching Methods for Causal Inference with Time-Series...

Description Details Author(s) References

Description

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.

Details

Package: PanelMatch
Type: Package
Version: 0.0.1-
Date: 2018-03-01
License: GPL (>= 3)

Author(s)

In Song Kim <insong@mit.edu>, Erik Wang <haixiao@Princeton.edu>, Adam Rauh <adamrauh@mit.edu>, and Kosuke Imai <imai@harvard.edu>

Maintainer: In Song Kim insong@mit.edu

References

Imai, Kosuke, In Song Kim and Erik Wang. (2018)


PanelMatch documentation built on Feb. 28, 2020, 5:07 p.m.