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| 空间匹配估计量× | 匹配估计量× | |
|---|---|---|
| 领域 | 因果推断 | 因果推断 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2000s–2010s | 1973 |
| 提出者≠ | Extension of Abadie & Imbens (2006) matching estimator to spatial settings; geographic applications developed in urban/environmental econometrics literature | Rubin (1973); large-sample theory by Abadie & Imbens (2006) |
| 类型≠ | Quasi-experimental causal inference | Nonparametric matching / causal inference |
| 开创性文献 | Abadie, A., & Imbens, G. W. (2006). Large Sample Properties of Matching Estimators for Average Treatment Effects. Econometrica, 74(1), 235-267. DOI ↗ | Abadie, A., & Imbens, G. W. (2006). Large Sample Properties of Matching Estimators for Average Treatment Effects. Econometrica, 74(1), 235-267. DOI ↗ |
| 别名 | geographic matching estimator, spatial nearest-neighbor matching, location-based matching estimator, spatially-weighted matching | nearest-neighbor matching, NNM, matching on covariates, covariate matching |
| 相关 | 6 | 6 |
| 摘要≠ | The Spatial Matching Estimator estimates causal treatment effects by pairing each treated geographic unit with one or more similar untreated units nearby, exploiting the assumption that units close in space share similar unobserved characteristics. By restricting matches to a geographic neighbourhood or weighting by spatial proximity, the method controls for location-specific confounders that standard matching ignores. | The matching estimator identifies the causal effect of a treatment by pairing each treated unit with one or more untreated units that have similar observed characteristics. Formalised by Rubin (1973) and given rigorous large-sample theory by Abadie and Imbens (2006), it constructs a credible control group from observational data without requiring a parametric model for the outcome. |
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