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This document discusses issues with using differences-in-differences (DD) estimation to evaluate causal effects. Specifically, it notes that while DD is a popular method, the standard errors produced are often inconsistent because they ignore serial correlation in outcomes over time. Through simulations using placebo laws, the authors show conventional DD standard errors severely understate the standard deviation of estimates, resulting in false significance for many estimates. They evaluate several methods

Author

Luis Ceballos

Language

EN