Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Paneļdatu entropijas balansēšana× | Fiksēto efektu paneļa datu modelis× | |
|---|---|---|
| Nozare≠ | Cēloņsakarību secināšana | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2012 (cross-section); panel adaptation mid-2010s onward | 2014 |
| Autors≠ | Hainmueller (2012); extended to panel settings by subsequent applied econometric work | Hsiao (textbook treatment); within transformation of panel data |
| Tips≠ | Covariate balancing / reweighting estimator | Panel data regression |
| Pirmavots≠ | Hainmueller, J. (2012). Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies. Political Analysis, 20(1), 25-46. DOI ↗ | Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗ |
| Citi nosaukumi | EB-panel, panel entropy balancing, entropy reweighting in panel data, panel-EB | fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | Panel data entropy balancing extends Hainmueller's (2012) entropy balancing method to longitudinal settings. It computes unit-level weights for control observations so that their covariate moments exactly match those of the treatment group across panel periods, then plugs these weights into a weighted panel regression to estimate causal treatment effects without requiring a correctly specified propensity score model. | 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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