Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Event Study Design (Causale Event Study)× | Panel Data Fixed Effects Model× | |
|---|---|---|
| Vakgebied≠ | Causale inferentie | Econometrie |
| Familie | Regression model | Regression model |
| Jaar van ontstaan≠ | 2021 | 2014 |
| Grondlegger≠ | Sun & Abraham (2021); Callaway & Sant'Anna (2021) | Hsiao (textbook treatment); within transformation of panel data |
| Type≠ | Dynamic causal panel regression | Panel data regression |
| Oorspronkelijke bron≠ | Sun, L. & Abraham, S. (2021). Estimating Dynamic Treatment Effects in Event Studies with Heterogeneous Treatment Effects. Journal of Econometrics, 225(2), 175–199. DOI ↗ | Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗ |
| Aliassen≠ | dynamic difference-in-differences, event-study DiD, dynamic treatment effects, leads-and-lags model | fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli |
| Verwant | 5 | 5 |
| Samenvatting≠ | The event study design is a generalised difference-in-differences model that estimates a separate treatment-effect coefficient for each period before and after an intervention, tracing the dynamics of the effect over event time. Its modern, heterogeneity-robust form was developed by Sun & Abraham (2021) and Callaway & Sant'Anna (2021). | The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014). |
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