Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Dinamiskais paneļa notikumu pētījums× | Fiksēto efektu paneļa datu modelis× | |
|---|---|---|
| Nozare≠ | Cēloņsakarību secināšana | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2021 | 2014 |
| Autors≠ | Sun & Abraham (2021); Callaway & Sant'Anna (2021) | Hsiao (textbook treatment); within transformation of panel data |
| Tips≠ | Quasi-experimental / causal inference | Panel data regression |
| Pirmavots≠ | Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-Differences with multiple time periods. Journal of Econometrics, 225(2), 200-230. DOI ↗ | Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗ |
| Citi nosaukumi | dynamic event study, panel event-study regression, leads-and-lags event study, event-time panel design | fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli |
| Saistītās≠ | 4 | 5 |
| Kopsavilkums≠ | The dynamic panel event study is a quasi-experimental method that uses panel data to trace out how a treatment effect evolves over time — before and after a defining event — by estimating a flexible regression of leads and lags around the treatment date. It simultaneously tests for pre-existing parallel trends and maps the full dynamic profile of causal impact across multiple post-event periods. | 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). |
| ScholarGateDatu kopa ↗ |
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