Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Modeli ya Miundo ya Kimarufuku ya Sera (MSM)× | Tofauti-katika-Tofauti (Diff-in-Diff)× | |
|---|---|---|
| Nyanja≠ | Uhitimisho wa Kisababishi | Ekonometriki |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 2000 | 1994 |
| Mwanzilishi≠ | James M. Robins, Miguel A. Hernan, Babette Brumback | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Aina≠ | Causal inference / weighted regression | Causal inference / panel regression |
| Chanzo asilia≠ | Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550–560. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Majina mbadala≠ | MSM for policy evaluation, policy MSM, causal MSM, structural policy weighting model | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| Zinazohusiana≠ | 6 | 5 |
| Muhtasari≠ | A Policy Evaluation Marginal Structural Model (MSM) is a causal inference framework that estimates the population-average effect of a policy by using inverse probability weighting to create a pseudo-population in which treatment assignment is independent of measured confounders, enabling unbiased comparison of potential outcomes under different policy scenarios from observational data. | 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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