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| Robust Panel Event Study× | Diferenču starpībām (Diff-in-Diff)× | |
|---|---|---|
| Nozare≠ | Cēloņsakarību secināšana | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2021 | 1994 |
| Autors≠ | Sun & Abraham (2021); Freyaldenhoven, Hansen, Shapiro & Weidner (2021) | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Tips≠ | Quasi-experimental / causal inference | Causal inference / panel regression |
| Pirmavots≠ | Sun, L., & Abraham, S. (2021). Estimating dynamic treatment effects in event studies with heterogeneous treatment effects. Journal of Econometrics, 225(2), 175-199. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Citi nosaukumi≠ | robust event-study estimator, heteroskedasticity-robust panel event study, staggered-robust event study, robust ES design | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| Saistītās≠ | 4 | 5 |
| Kopsavilkums≠ | A robust panel event study extends the standard panel event study design by applying heteroskedasticity- and autocorrelation-robust (HAC) standard errors and, where staggered treatment adoption exists, interaction-weighted estimators that remain valid even when treatment effects are heterogeneous across cohorts and time periods. It is widely used in economics, finance, and policy research to trace the dynamic causal path of an intervention. | 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. |
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