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This document is a survey by Michael Lechner on the difference-in-difference (DiD) estimation strategy used for estimating causal effects in econometrics. It covers the history, models, identification issues, estimation challenges, and specific inference issues related to DiD methods, while also discussing extensions such as nonlinear estimators and propensity-score matching. The survey aims to provide a comprehensive overview while complementing existing literature on the topic.

Author

rk477660

Language

EN