方法对比
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| 时空空间回归× | 空间滞后模型（SAR / 空间自回归）× | |
|---|---|---|
| 领域 | 空间分析 | 空间分析 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1990s–2000s | 1988 |
| 提出者≠ | Anselin, LeSage, Pace and colleagues in spatial econometrics | Anselin (textbook formalisation); LeSage & Pace |
| 类型≠ | Spatio-temporal regression model | Spatial autoregressive regression |
| 开创性文献≠ | LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247 | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗ |
| 别名 | spatio-temporal regression, spatial panel regression, space-time regression, ST spatial regression | SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag) |
| 相关≠ | 6 | 5 |
| 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. | The Spatial Lag Model is an autoregressive regression that assumes spatial dependence in the dependent variable itself: the outcome values of neighbouring units enter the model as an explanatory term (ρWy). It was formalised in Anselin's Spatial Econometrics (1988) and developed further by LeSage and Pace (2009), and it decomposes spillover effects into direct, indirect, and total impacts. |
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