方法对比
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| 空间因果影响分析× | 双重差分法 (Diff-in-Diff)× | |
|---|---|---|
| 领域≠ | 因果推断 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2010s (codified) | 1994 |
| 提出者≠ | Delgado & Florax (spatial DiD); Halleck Vega & Elhorst (SLX model); broader lineage in spatial econometrics (Anselin, 1988) | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| 类型≠ | Quasi-experimental causal inference with spatial data | Causal inference / panel regression |
| 开创性文献≠ | Delgado, M. S., & Florax, R. J. G. M. (2015). Difference-in-differences techniques for spatial data: Local autocorrelation and spatial interaction. Economics Letters, 137, 123-126. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| 别名≠ | spatial causal inference, geo-causal analysis, spatial treatment effect estimation, spatial impact evaluation | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| 相关≠ | 4 | 5 |
| 摘要≠ | Spatial causal impact analysis estimates the causal effect of a spatially-targeted intervention — a policy, shock, or treatment applied to particular locations — while explicitly accounting for geographic spillovers between treated and untreated units. By combining quasi-experimental designs such as difference-in-differences or regression discontinuity with spatial econometric models, it separates the direct local effect of a treatment from indirect effects that diffuse to neighbouring areas. | Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes. |
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