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| 双重差分法 (Diff-in-Diff)× | 因果推断的工具变量（IV）方法× | |
|---|---|---|
| 领域≠ | 计量经济学 | 卫生经济学 |
| 方法族≠ | Regression model | Process / pipeline |
| 起源年份≠ | 1994 | 1990s (modern applications) |
| 提出者≠ | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) | Angrist & Pischke (applied econometrics); rooted in econometric theory |
| 类型≠ | Causal inference / panel regression | Method |
| 开创性文献≠ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 | Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press. link ↗ |
| 别名≠ | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) | IV, two-stage least squares, TSLS, causal estimation |
| 相关≠ | 5 | 3 |
| 摘要≠ | 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. | Instrumental variables (IV) is an econometric method to estimate causal effects when treatment or exposure is not randomly assigned and confounding is severe or unmeasured. IV relies on a third variable (instrument) that influences treatment but does not directly affect the outcome, allowing researchers to isolate the causal effect from the noise of confounding. Developed extensively in econometrics (Angrist & Pischke, 1990s–2000s), IV methods are increasingly used in health economics and health services research to leverage natural experiments and policy changes. |
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