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| Análisis de Datos de Panel× | Estimador de Mínimos Cuadrados Generalizados (GMM) de Arellano-Bond× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1966–1978 | 1991 |
| Autor original≠ | Balestra & Nerlove (1966); Mundlak (1978); Hausman (1978) | Manuel Arellano and Stephen Bond |
| Tipo≠ | Panel regression framework | GMM estimator for dynamic panel data |
| Fuente seminal≠ | Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. ISBN: 978-3030539528 | 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 ↗ |
| Alias | longitudinal data analysis, pooled cross-sectional time-series analysis, panel regression, data panel analysis | AB-GMM, Difference GMM, first-difference GMM, Arellano-Bond estimator |
| Relacionados | 5 | 5 |
| Resumen≠ | Panel data analysis models data that track multiple units — countries, firms, individuals — over time, enabling researchers to control for unobserved unit-level heterogeneity that would otherwise bias cross-sectional or time-series estimates. The two core specifications are fixed effects and random effects, selected via the Hausman test. | The Arellano-Bond GMM estimator is the standard approach for dynamic panel data models in which the lagged dependent variable appears as a regressor. By first-differencing to remove fixed effects and using deeper lags as instruments, it yields consistent estimates even when the error is serially correlated and regressors are endogenous. |
| ScholarGateConjunto de datos ↗ |
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