方法对比
并排查看您选择的方法;存在差异的行会高亮显示。
| 固定效应面板模型× | 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≠ | 2005 | 1990s (modern applications) |
| 提出者≠ | Baltagi (textbook treatment); Hausman test for FE vs RE choice | Angrist & Pischke (applied econometrics); rooted in econometric theory |
| 类型≠ | Panel data regression | Method |
| 开创性文献≠ | Hausman, J. A. (1978). Specification Tests in Econometrics. Econometrica, 46(6), 1251–1271. DOI ↗ | Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press. link ↗ |
| 别名 | within estimator, panel fixed effects, entity fixed effects model, Panel Sabit Etkiler Modeli | IV, two-stage least squares, TSLS, causal estimation |
| 相关≠ | 5 | 3 |
| 摘要≠ | The fixed effects panel model estimates relationships in panel data (many units observed over time) by exploiting only the within-unit variation, so that unobserved time-invariant heterogeneity is controlled away. It is the central within estimator developed in Baltagi's Econometric Analysis of Panel Data (2005), and the choice between it and the random effects model is settled by the Hausman (1978) test. | 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. |
| ScholarGate数据集 ↗ |
|
|