方法对比
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| 时空空间杜宾模型 (ST-SDM)× | 空间误差模型 (SEM)× | |
|---|---|---|
| 领域 | 空间分析 | 空间分析 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2009-2014 | 1988 |
| 提出者≠ | LeSage & Pace; extended to space-time by Elhorst | Anselin |
| 类型≠ | Spatial econometric panel model | Spatial regression (spatially autocorrelated errors) |
| 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 | ST-SDM, spatiotemporal Durbin model, spatial Durbin panel model, space-time SDM | SEM, spatial error regression, spatial autoregressive error model, Uzamsal Hata Modeli (SEM / Spatial Error) |
| 相关≠ | 6 | 5 |
| 摘要≠ | The Space-Time Spatial Durbin Model extends the cross-sectional Spatial Durbin Model to panel data, simultaneously capturing spatial spillovers in both the dependent variable and the explanatory variables across space and over time. It is the most general and flexible specification in the spatial panel family, nesting the spatial lag and spatial error models as special cases. | The Spatial Error Model, developed within Anselin's spatial econometrics framework (1988), is a regression model that assumes spatial dependence enters through the error term: the disturbances of neighbouring units are correlated. It is used when unobserved shared factors make the errors of nearby observations move together, and it is estimated by maximum likelihood or GMM rather than ordinary least squares. |
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