Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Telpiskais laika panelis modelis× | Telpiskais laika telpiskais nobīdes modelis× | |
|---|---|---|
| Nozare | Telpiskā analīze | Telpiskā analīze |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2003–2014 | 2003-2008 |
| Autors≠ | J. Paul Elhorst | Anselin, Le Gallo & Jayet; Elhorst |
| Tips | Spatial panel regression | Spatial panel regression |
| Pirmavots≠ | Elhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. ISBN: 978-3642403408 | Anselin, L., Le Gallo, J., & Jayet, H. (2008). Spatial Panel Econometrics. In L. Matyas & P. Sevestre (Eds.), The Econometrics of Panel Data (pp. 625-660). Springer. link ↗ |
| Citi nosaukumi | ST-SPM, spatiotemporal panel model, space-time panel econometrics, dynamic spatial panel model | ST-SAR, spatial-temporal lag model, spatiotemporal autoregressive model, space-time SAR model |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | The Space-Time Spatial Panel Model extends standard spatial panel econometrics to jointly account for cross-sectional spatial dependence, temporal autocorrelation, and unit-level heterogeneity. It allows outcomes in one location and time period to be influenced by outcomes in neighboring locations and by the location's own past, making it the canonical framework for dynamic spatiotemporal panel data analysis. | The Space-Time Spatial Lag Model extends the classic spatial autoregressive (SAR) lag model to panel data, capturing how the outcome in each location at each time point is influenced by the contemporaneous outcomes of neighboring locations, while also controlling for unit-specific and time-specific fixed effects. |
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