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| Model Data Panel Spasial (FE/RE)× | Regresi Berbobot Geografis (GWR)× | |
|---|---|---|
| Bidang | Analisis Spasial | Analisis Spasial |
| Keluarga | Regression model | Regression model |
| Tahun asal≠ | 2014 | 2002 |
| Pencetus≠ | Elhorst; Lee & Yu | Fotheringham, Brunsdon & Charlton |
| Tipe≠ | Spatial econometric panel model | Local spatial regression |
| Sumber perintis≠ | Elhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. DOI ↗ | Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168 |
| Alias | spatial panel FE/RE, spatial econometric panel, spatial lag/error panel, Uzamsal Panel Modeli (Spatial Panel FE/RE) | GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR) |
| Terkait≠ | 4 | 5 |
| Ringkasan≠ | The spatial panel model is a family of econometric models that adds spatial dependence to panel data (units observed over time). It combines fixed- or random-effects panel structure with spatial lag, spatial error, or spatial Durbin components, and is developed in the modern spatial-econometrics literature by Elhorst (2014) and Lee & Yu (2010). | Geographically Weighted Regression is a local regression method, introduced by Fotheringham, Brunsdon and Charlton (2002), that allows the regression coefficients to vary across space. Instead of one global equation, it fits a separate set of coefficients at every location, capturing spatial heterogeneity in the relationships. |
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