Machine Learning-Augmented Panel Event Study
De machine learning-augmented panel event study breidt de klassieke panel event study uit door parametrische contrafactuele modellen te vervangen of aan te vullen met machine learning-schatters — zoals LASSO, random forests, of matrix completion — om nauwkeurigere pre-event baselines te construeren, schendingen van parallelle trends te detecteren, en geldige causale effectschattingen te produceren over meerdere post-event perioden.
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Bronnen
- Chernozhukov, V., Wuthrich, K., & Zhu, Y. (2021). An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls. Journal of the American Statistical Association, 116(536), 1849-1864. DOI: 10.1080/01621459.2021.1920957 ↗
- Freyaldenhoven, S., Hansen, C., & Shapiro, J. M. (2019). Pre-event Trends in the Panel Event-Study Design. American Economic Review, 109(9), 3307-3338. DOI: 10.1257/aer.20180609 ↗
Deze pagina citeren
ScholarGate. (2026, June 3). Machine Learning-Augmented Panel Event Study Estimator. ScholarGate. https://scholargate.app/nl/causal-inference/machine-learning-augmented-panel-event-study
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Difference-in-Differences (DiD)Econometrie↔ compare
- Panel Data Fixed Effects ModelEconometrie↔ compare
- Synthetic Control Method (SCM)Causale inferentie↔ compare
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