Portada del sitio > Asignaturas / Teaching > Trabajo de Fin de Grado (TFG). Grado en Economía > Materiales útiles para realizar el TFG > Modelos Diff-in-diff (DID) > The Role of Parallel Trends in Event Study Settings: An Application to (...)
The Role of Parallel Trends in Event Study Settings: An Application to Environmental Economics
Authors: Michelle Marcus, Pedro H. C. Sant’Anna (2021) JAERE, volume 8, number 2.
Miércoles 14 de junio de 2023, por Carlos San Juan
Difference-in-differences (DID) research designs usually rely on variation
of treatment timing such that, after making an appropriate parallel trends assumption, one can identify, estimate, and make inference about causal effects. In practice,
however, different DID procedures rely on different parallel trends assumptions (PTAs),
and recover different causal parameters. In this paper, we focus on staggered DID
(also referred as event studies) and discuss the role played by the PTA in terms of
identification and estimation of causal parameters. We document a “robustness” versus “efficiency” trade-off in terms of the strength of the underlying PTA and argue
that practitioners should be explicit about these trade-offs whenever using DID procedures. We propose new DID estimators that reflect these trade-offs and derive their
large sample properties. We illustrate the practical relevance of these results by assessing
whether the transition from federal to state management of the Clean Water Act affects
compliance rates
Documentos adjuntos
-
Difference-in-differences (DID) research designs usually rely on variation of treatment timing such that, after making an appropriate parallel trends assumption, one can identify, estimate, and make inference about causal effects. In practice, however, different DID procedures rely on different parallel trends assumptions (PTAs), and recover different causal parameters. In this paper, we focus on staggered DID (also referred as event studies) and discuss the role played by the PTA in terms of identification and estimation of causal parameters. We document a “robustness” versus “efficiency” trade-off in terms of the strength of the underlying PTA and argue that practitioners should be explicit about these trade-offs whenever using DID procedures. We propose new DID estimators that reflect these trade-offs and derive their large sample properties. We illustrate the practical relevance of these results by assessing whether the transition from federal to state management of the Clean Water Act affects compliance rates
RSS 2.0