Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Panel ARMA modelis× | Fiksēto efektu paneļa modelis (FE)× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1980s–2000s | 1978 |
| Autors≠ | Baltagi, Hsiao and related panel data literature | Mundlak (1978); classical treatment in Wooldridge (2010) and Baltagi (2021) |
| Tips≠ | Panel time series model | Panel regression estimator |
| Pirmavots≠ | Baltagi, B. H. (2008). Econometric Analysis of Panel Data (4th ed.). John Wiley & Sons. ISBN: 978-0470518861 | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 |
| Citi nosaukumi | Panel ARMA, ARMA panel model, panel autoregressive moving average, cross-sectional ARMA | within estimator, FE model, within-group estimator, LSDV model |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | The Panel ARMA model extends the classical Autoregressive Moving Average (ARMA) framework to panel data, allowing each cross-sectional unit to carry an individual effect while the within-unit error dynamics follow an ARMA(p, q) process. It captures both autocorrelation and moving-average dependence in panel residuals, yielding efficient estimates when the error structure is correctly specified. | The panel fixed effects (FE) model controls for all time-invariant, unit-specific unobserved heterogeneity by absorbing it into individual intercepts. By sweeping out unit means through the within transformation, FE yields unbiased estimates of the effect of time-varying regressors even when omitted unit-level confounders are correlated with those regressors. |
| ScholarGateDatu kopa ↗ |
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