Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Regresia Ponderată Geografic Panel Multiscalară (Panel MGWR)× | Panel Spatial Durbin Model× | |
|---|---|---|
| Domeniu | Analiză spațială | Analiză spațială |
| Familie | Regression model | Regression model |
| Anul apariției≠ | 2017-2020 | 2009–2010 |
| Autorul original≠ | Fotheringham, Yang & Kang (MGWR base); panel extension developed in spatial econometrics literature | LeSage & Pace (2009); panel extension by Elhorst (2010) |
| Tip≠ | Spatially varying coefficient panel regression | Spatial panel regression |
| Sursa seminală≠ | Fotheringham, A. S., Yang, W., & Kang, W. (2017). Multiscale Geographically Weighted Regression (MGWR). Annals of the American Association of Geographers, 107(6), 1247-1265. DOI ↗ | Elhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. ISBN: 978-3642403408 |
| Denumiri alternative | Panel MGWR, MGWR panel data, multiscale GWR panel, panel spatially varying coefficient model | SDM panel, spatial Durbin panel model, panel SDM, PSDM |
| Înrudite | 5 | 5 |
| Rezumat≠ | Panel MGWR extends Multiscale Geographically Weighted Regression to repeated-observations (panel) data, allowing each predictor to operate at its own spatial bandwidth while controlling for unit-specific or time-specific fixed effects. It is used when both spatial heterogeneity and temporal structure matter simultaneously. | 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. |
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