Jämför metoder
Granska de valda metoderna sida vid sida; rader som skiljer sig är markerade.
| Policy Evaluation via Coarsened Exact Matching (CEM)× | Differens-i-differens (DiD)× | |
|---|---|---|
| Ämnesområde≠ | Kausal inferens | Ekonometri |
| Familj | Regression model | Regression model |
| Ursprungsår≠ | 2011-2012 | 1994 |
| Upphovsperson≠ | Iacus, King & Porro | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Typ≠ | Matching / quasi-experimental design | Causal inference / panel regression |
| Ursprungskälla≠ | 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 |
| Alias≠ | CEM, Coarsened Exact Matching, CEM policy evaluation, coarsening-based matching | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| Närliggande | 5 | 5 |
| Sammanfattning≠ | Coarsened Exact Matching (CEM) is a quasi-experimental causal-inference technique that creates balanced treatment and control groups from observational data by temporarily coarsening covariates into bins, exactly matching units within those bins, and then pruning unmatched observations before estimating policy effects. Introduced by Iacus, King, and Porro, CEM belongs to the monotonic imbalance bounding family of matching methods and is especially popular in policy evaluation. | 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. |
| ScholarGateDatamängd ↗ |
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