قارن الطرق
راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.
| طريقة التحكم الاصطناعي لتقييم السياسات× | طريقة المتغيرات الآلية (IV) للاستدلال السببي× | |
|---|---|---|
| المجال≠ | الاستدلال السببي | اقتصاديات الصحة |
| العائلة≠ | Regression model | Process / pipeline |
| سنة النشأة≠ | 2003-2010 | 1990s (modern applications) |
| صاحب الطريقة≠ | Alberto Abadie & Javier Gardeazabal; extended by Abadie, Diamond & Hainmueller | Angrist & Pischke (applied econometrics); rooted in econometric theory |
| النوع≠ | Causal inference / comparative case study | Method |
| المصدر التأسيسي≠ | Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493-505. DOI ↗ | Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press. link ↗ |
| الأسماء البديلة | Synthetic Control Method, SCM, Synthetic Control, Abadie-Diamond-Hainmueller method | IV, two-stage least squares, TSLS, causal estimation |
| ذات صلة≠ | 5 | 3 |
| الملخص≠ | The Synthetic Control Method (SCM) is a causal inference technique for evaluating the effect of a policy or intervention on a single treated unit — such as a region, country, or firm — by constructing a weighted combination of untreated comparison units that closely mirrors the treated unit before the intervention. Introduced by Abadie and Gardeazabal (2003) and formalized by Abadie, Diamond, and Hainmueller (2010), it provides a data-driven, transparent counterfactual for comparative case studies. | 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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