Salīdzināt metodes
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| Dinamiskais paneļa datu modelis× | Panel Data Analysis× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1988–1991 | 1966–1978 |
| Autors≠ | Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988) | Balestra & Nerlove (1966); Mundlak (1978); Hausman (1978) |
| Tips≠ | Dynamic regression / GMM estimation | Panel regression framework |
| 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. DOI ↗ | Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. ISBN: 978-3030539528 |
| Citi nosaukumi | dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model | longitudinal data analysis, pooled cross-sectional time-series analysis, panel regression, data panel analysis |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | The dynamic panel data model extends standard panel regression by including a lagged value of the outcome variable as a regressor, capturing persistence and adjustment dynamics. Because the lagged dependent variable is correlated with the unit-specific fixed effect, ordinary OLS or within estimators are biased; GMM-based methods using internal instruments are the standard remedy. | 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. |
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