PanelMatch: Matching Methods for Causal Inference with Time-Series Cross-Section Data
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866908491267964928 |
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| author | Rauh, Adam Kim, In Song Imai, Kosuke |
| author_facet | Rauh, Adam Kim, In Song Imai, Kosuke |
| contents | Analyzing time-series cross-sectional (also known as longitudinal or panel) data is an important process across a number of fields, including the social sciences, economics, finance, and medicine. PanelMatch is an R package that implements a set of tools enabling researchers to apply matching methods for causal inference with time-series cross-sectional data. Relative to other commonly used methods for longitudinal analyses, like regression with fixed effects, the matching-based approach implemented in PanelMatch makes fewer parametric assumptions and offers more diagnostics. In this paper, we discuss the PanelMatch package, showing users a recommended pipeline for doing causal inference analysis with it and highlighting useful diagnostic and visualization tools. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_02073 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | PanelMatch: Matching Methods for Causal Inference with Time-Series Cross-Section Data Rauh, Adam Kim, In Song Imai, Kosuke Methodology Applications Analyzing time-series cross-sectional (also known as longitudinal or panel) data is an important process across a number of fields, including the social sciences, economics, finance, and medicine. PanelMatch is an R package that implements a set of tools enabling researchers to apply matching methods for causal inference with time-series cross-sectional data. Relative to other commonly used methods for longitudinal analyses, like regression with fixed effects, the matching-based approach implemented in PanelMatch makes fewer parametric assumptions and offers more diagnostics. In this paper, we discuss the PanelMatch package, showing users a recommended pipeline for doing causal inference analysis with it and highlighting useful diagnostic and visualization tools. |
| title | PanelMatch: Matching Methods for Causal Inference with Time-Series Cross-Section Data |
| topic | Methodology Applications |
| url | https://arxiv.org/abs/2503.02073 |