Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Paneļa autoregresijas (Panel AR) modelis× | Panel ARIMA modelis× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1980s-2000s | 1970s–2000s |
| Autors≠ | Hsiao, C.; Arellano, M. | Extension of Box-Jenkins ARIMA (Box & Jenkins, 1970) to panel settings; formalised in panel econometrics literature (Hsiao, 2003) |
| Tips≠ | Autoregressive time-series model for panel data | Time-series model applied to panel data |
| Pirmavots | Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717 | Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717 |
| Citi nosaukumi | panel autoregressive model, PAR model, AR model for panel data, panel AR(p) | Panel ARIMA, ARIMA for panel data, cross-sectional ARIMA, multi-unit ARIMA |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | The Panel AR model extends the classical univariate autoregressive model to panel data, capturing how each unit's own past values predict its current value while controlling for unobserved individual heterogeneity through fixed or random effects. It is foundational for modelling dynamic persistence in micro or macro panel datasets. | The Panel ARIMA model extends the classical Box-Jenkins ARIMA framework to panel data, fitting autoregressive integrated moving-average dynamics to multiple cross-sectional units observed over time. It accommodates unit-specific short-run dynamics and non-stationarity, making it suitable for forecasting and dynamic analysis when both cross-sectional and temporal dimensions are present. |
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