Robustness values for DiD: how strong must hidden confounders be to overturn results
analisereal · x · 2026-09-17
The author explains the second use of the decomposition: asking how strong an unobserved confounder would need to be to overturn the conclusions. This yields robustness values for difference-in-differences, quantifying the minimal confounder strength that would invalidate the results.
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