May 13, 2024, 3:14 p.m. | /u/turingincarnate

Data Science www.reddit.com

Hi, to those of you who regularly use synthetic controls/causal inference for impact analysis, perhaps [my implementation](https://github.com/jgreathouse9/mlsynth/blob/main/Vignettes/PCR/PCRVignette.md) of principal component regression will be useful. As the name suggests, it uses SVD and universal singular value thresholding in order to denoise the outcome matrix. OLS (convex or unconstrained) is employed to estimate the causal impact in the usual manner. I replicate the Proposition 99 case study from the econometrics/statistics literature. As usual, comments or suggestions are most welcome.

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