Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Panel Spatial Durbin Model× | Panel Spatial Error Model× | |
|---|---|---|
| Nozare | Telpiskā analīze | Telpiskā analīze |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2009–2010 | 1988 / 2003 |
| Autors≠ | LeSage & Pace (2009); panel extension by Elhorst (2010) | Anselin (1988); extended to panels by Elhorst (2003, 2014) |
| Tips≠ | Spatial panel regression | Spatial econometric panel model |
| Pirmavots | Elhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. ISBN: 978-3642403408 | Elhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. ISBN: 978-3642403408 |
| Citi nosaukumi | SDM panel, spatial Durbin panel model, panel SDM, PSDM | panel SEM, spatial error panel model, panel spatial autocorrelation error model, SEM panel |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | The Panel Spatial Durbin Model (PSDM) extends the cross-sectional Spatial Durbin Model to panel data, capturing both spatial lag dependence in the outcome and spatial spillovers from neighbouring units' explanatory variables across multiple time periods. It simultaneously accounts for unobserved unit-specific and time-specific heterogeneity, making it one of the most comprehensive spatial panel specifications available. | The Panel Spatial Error Model (panel SEM) extends the classical spatial error model to panel data, allowing spatial dependence to enter through the error term across cross-sectional units over multiple time periods. It accounts for spatially correlated omitted variables without imposing a substantive spatial spillover in the outcome itself. |
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