Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Coarsened Exact Matching (CEM)× | Diferenču starpībām (Diff-in-Diff)× | |
|---|---|---|
| Nozare≠ | Cēloņsakarību secināšana | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2011-2012 | 1994 |
| Autors≠ | Iacus, King, & Porro | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Tips≠ | Matching / causal inference | Causal inference / panel regression |
| Pirmavots≠ | Iacus, S. M., King, G., & Porro, G. (2012). Causal Inference without Balance Checking: Coarsened Exact Matching. Political Analysis, 20(1), 1-24. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Citi nosaukumi | CEM, coarsened matching, monotonic imbalance bounding matching | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | Coarsened Exact Matching is a preprocessing method that achieves covariate balance by temporarily coarsening continuous variables into bins, exactly matching treated and control units within those bins, and then discarding all unmatched units. Introduced by Iacus, King, and Porro (2011, 2012), it bounds imbalance on each covariate independently, yielding a matched sample on which any estimator can be applied without relying on a propensity score model. | 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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