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What is Difference-in-Differences With A Continuous Treatment-2024 about?

This paper explores difference-in-differences (DiD) methodologies for continuous treatments, highlighting the challenges of selection bias and the need for stronger assumptions to interpret treatment effects. It critiques the common use of two-way fixed-effects (TWFE) estimators, proposing alternative nonparametric estimators that yield clearer causal interpretations. The authors demonstrate the practical implications of their findings through an application to a Medicare reform study, revealing significant

Author

Yue Jiao

Language

EN