方法对比
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| 时空空间回归× | 面板空间回归× | |
|---|---|---|
| 领域 | 空间分析 | 空间分析 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1990s–2000s | 1988-2014 |
| 提出者≠ | Anselin, LeSage, Pace and colleagues in spatial econometrics | Anselin, Elhorst, and colleagues in spatial econometrics |
| 类型≠ | Spatio-temporal regression model | Spatial panel regression |
| 开创性文献≠ | LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247 | Elhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. ISBN: 978-3642403408 |
| 别名 | spatio-temporal regression, spatial panel regression, space-time regression, ST spatial regression | spatial panel model, panel spatial econometrics, spatial panel data regression, PSR |
| 相关 | 6 | 6 |
| 摘要≠ | Space-Time Spatial Regression extends classical spatial regression to panel settings where georeferenced units are observed across multiple time periods. By embedding a spatial weights matrix into a panel regression framework, it simultaneously controls for spatial dependence among cross-sectional units and temporal dynamics, yielding unbiased and consistent estimates in spatio-temporal data. | Panel Spatial Regression extends standard panel data models by explicitly accounting for spatial dependence among cross-sectional units observed over time. It combines the temporal control of panel fixed or random effects with a spatial weights matrix that encodes geographic or network proximity, yielding unbiased and efficient estimates when observations are spatially correlated across units. |
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