方法对比
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| 因果推断的工具变量（IV）方法× | 面板数据固定效应模型× | |
|---|---|---|
| 领域≠ | 卫生经济学 | 计量经济学 |
| 方法族≠ | Process / pipeline | Regression model |
| 起源年份≠ | 1990s (modern applications) | 2014 |
| 提出者≠ | Angrist & Pischke (applied econometrics); rooted in econometric theory | Hsiao (textbook treatment); within transformation of panel data |
| 类型≠ | Method | Panel data regression |
| 开创性文献≠ | Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press. link ↗ | Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗ |
| 别名 | IV, two-stage least squares, TSLS, causal estimation | fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli |
| 相关≠ | 3 | 5 |
| 摘要≠ | 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. | The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014). |
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