Compara mètodes
Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.
| Variables Instrumentals Dinàmiques (IV Panel / Arellano-Bond)× | Variables instrumentals en dades de panel (Panel IV / 2SLS)× | |
|---|---|---|
| Camp | Inferència causal | Inferència causal |
| Família | Regression model | Regression model |
| Any d'origen≠ | 1991 | 1978-1991 |
| Autor original≠ | Arellano & Bond (1991); extended by Blundell & Bond (1998) | Hausman (1978); Anderson & Hsiao (1982); Arellano & Bond (1991) |
| Tipus≠ | Dynamic panel causal estimation | Causal inference / panel regression |
| Font seminal | Arellano, M., & Bond, S. (1991). Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. Review of Economic Studies, 58(2), 277-297. DOI ↗ | Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58(2), 277-297. DOI ↗ |
| Àlies | Dynamic IV, Dynamic Panel IV, Arellano-Bond GMM, System GMM | Panel IV, Panel 2SLS, Within-IV, Fixed-Effects IV |
| Relacionats≠ | 5 | 4 |
| Resum≠ | Dynamic Instrumental Variables estimation addresses endogeneity in panel models where the outcome depends on its own past values. By first-differencing to remove unit fixed effects and then using lagged levels as instruments for the differenced lagged outcome, it produces consistent causal estimates even when standard OLS or fixed-effects are biased by dynamic feedback. | Panel data instrumental variables combines the bias-correcting power of instrumental variables (IV) with the within-unit variation exploited by panel data methods. It addresses endogeneity — omitted variables, reverse causation, or measurement error — in longitudinal settings where observations are repeated across units and time. Seminal contributions come from Hausman (1978) on specification testing and Arellano and Bond (1991) on GMM-based panel IV. |
| ScholarGateConjunt de dades ↗ |
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