Double-Robust Estimation in Difference-in-Differences with an Application to Traffic Safety Evaluation

18 Mar 2019 Li Fan Li Fan

Difference-in-differences (DID) is a widely used approach for drawing causal inference from observational panel data. Two common estimation strategies for DID are outcome regression and propensity score weighting... (read more)

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