Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Reģresijas atslēguma dizains panelī (Panel Data Regression Discontinuity Design)× | Panel Data Difference-in-Differences (Panel DiD / TWFE)× | |
|---|---|---|
| Nozare | Cēloņsakarību secināšana | Cēloņsakarību secināšana |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1960 (original RDD); panel extension codified 2000s–2010s | 1985–2004 |
| Autors≠ | Thistlethwaite & Campbell (1960); panel extension developed through Lee & Lemieux (2010) and related applied work | Ashenfelter & Card (1985); codified by Angrist & Pischke (2009); serial correlation critique by Bertrand, Duflo & Mullainathan (2004) |
| Tips≠ | Causal inference / quasi-experimental | Causal inference / panel regression |
| Pirmavots≠ | Lee, D. S., & Lemieux, T. (2010). Regression Discontinuity Designs in Economics. Journal of Economic Literature, 48(2), 281-355. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Citi nosaukumi | Panel RD, Panel RDD, Longitudinal Regression Discontinuity, Fixed-Effects RDD | Two-Way Fixed Effects DiD, TWFE, Panel DiD, Panel Diff-in-Diff |
| Saistītās≠ | 5 | 4 |
| Kopsavilkums≠ | Panel data regression discontinuity design (Panel RDD) combines the sharp local identification of a regression discontinuity with the within-unit variation available in repeated-observation panel data. Units are observed across multiple periods, and treatment is assigned based on whether a running variable crosses a known threshold. By leveraging both the discontinuity and panel structure, researchers can control for unobserved unit-level heterogeneity while estimating a causal treatment effect near the threshold. | Panel Data Difference-in-Differences extends the classic two-period DiD design to settings with multiple units observed across many time periods. By absorbing unit-level fixed effects and time fixed effects simultaneously, it isolates the causal effect of a treatment or policy change while controlling for both time-invariant unit heterogeneity and common time shocks affecting all units. |
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