Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Njia ya Kidhibiti Sanisi cha Data ya Paneli× | Tofauti-katika-Tofauti (Diff-in-Diff)× | |
|---|---|---|
| Nyanja≠ | Uhitimisho wa Kisababishi | Ekonometriki |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 2010 | 1994 |
| Mwanzilishi≠ | Alberto Abadie, Alexis Diamond & Jens Hainmueller | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Aina≠ | Causal inference / panel data | Causal inference / panel regression |
| Chanzo asilia≠ | 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 University Press. ISBN: 978-0691120355 |
| Majina mbadala≠ | SCM panel, panel synthetic control, synthetic control estimator, comparative case study | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| Zinazohusiana | 5 | 5 |
| Muhtasari≠ | The panel data synthetic control method estimates the causal effect of an intervention on a single treated unit by constructing a data-driven weighted combination of untreated units — a synthetic control — that best reproduces the treated unit's pre-treatment outcome trajectory. The post-treatment gap between the treated unit and its synthetic counterpart is the estimated treatment effect. | 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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