Salīdzināt metodes

	Dinamiskās instrumentālās mainīgās (Dinamiskais panelis IV / Arellano-Bond)	Panel Data Instrumentu Mainīgie (Panel IV / 2SLS)
Nozare	Cēloņsakarību secināšana	Cēloņsakarību secināšana
Saime	Regression model	Regression model
Izcelsmes gads	1991	1978-1991
Autors	Arellano & Bond (1991); extended by Blundell & Bond (1998)	Hausman (1978); Anderson & Hsiao (1982); Arellano & Bond (1991)
Tips	Dynamic panel causal estimation	Causal inference / panel regression
Pirmavots	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.	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.
Citi nosaukumi	Dynamic IV, Dynamic Panel IV, Arellano-Bond GMM, System GMM	Panel IV, Panel 2SLS, Within-IV, Fixed-Effects IV
Saistītās	5	4
Kopsavilkums	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.