Salīdzināt metodes
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| Robust Synthetic Control Method× | Diferenču starpībām (Diff-in-Diff)× | |
|---|---|---|
| Nozare≠ | Cēloņsakarību secināšana | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2021 | 1994 |
| Autors≠ | Cattaneo, Feng & Titiunik (2021); building on Abadie, Diamond & Hainmueller (2010) | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Tips≠ | Quasi-experimental causal inference | Causal inference / panel regression |
| Pirmavots≠ | Cattaneo, M. D., Feng, Y., & Titiunik, R. (2021). Prediction Intervals for Synthetic Control Methods. Journal of the American Statistical Association, 116(536), 1865-1880. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Citi nosaukumi≠ | Robust SCM, Inference-robust synthetic control, Synthetic control with valid inference, SCM with prediction intervals | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | The robust synthetic control method extends the classic synthetic control estimator by providing statistically valid uncertainty quantification and inference. Developed by Cattaneo, Feng and Titiunik (2021), it addresses a core limitation of the original approach — the lack of formal prediction intervals — making causal conclusions more defensible when only a single treated unit is observed. | 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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