Comparar métodos

	Estudo de Evento em Painel	Diferenças em Diferenças (DiD)
Área	Inferência causal	Econometria
Família	Regression model	Regression model
Ano de origem	1990s–2020s (modern panel formulation)	1994
Autor original	Formalized by Freyaldenhoven, Hansen, Perez-Orive & Shapiro (2021); widely applied in finance (Fama et al. 1969) and policy evaluation	Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
Tipo	Quasi-experimental / causal panel design	Causal inference / panel regression
Fonte seminal	Freyaldenhoven, S., Hansen, C., Perez-Orive, J., & Shapiro, J. M. (2021). Visualization, Identification, and Estimation in the Linear Panel Event-Study Design. NBER Working Paper 29170. National Bureau of Economic Research.	Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Outros nomes	event-study regression, dynamic DiD, relative-time regression, distributed-lag panel model	diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Relacionados	4	5
Resumo	A panel event study estimates the dynamic causal effect of a treatment or policy by regressing an outcome on a full set of relative-time indicators — one for each period before and after the event — while controlling for unit and time fixed effects. The resulting coefficient plot shows how the treated units diverged from untreated units at each point in calendar time relative to their treatment date, making both pre-treatment trend violations and post-treatment effect trajectories immediately visible.	Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes.