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| Valutazione d'impatto controfattuale nella ricerca educativa× | Difference-in-Differences (Diff-in-Diff)× | |
|---|---|---|
| Campo≠ | Inferenza causale | Econometria |
| Famiglia | Regression model | Regression model |
| Anno di origine≠ | 2000s–2010s | 1994 |
| Ideatore≠ | Blundell & Costa Dias; formalized for EU education policy by the European Commission Joint Research Centre | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Tipo≠ | Quasi-experimental causal inference framework | Causal inference / panel regression |
| Fonte seminale≠ | Blundell, R., & Costa Dias, M. (2002). Alternative approaches to evaluation in empirical microeconomics. Portuguese Economic Journal, 1(2), 91-115. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Alias≠ | CIE in education, counterfactual program evaluation, causal impact evaluation, education policy impact evaluation | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| Correlati | 5 | 5 |
| Sintesi≠ | Counterfactual impact evaluation (CIE) is the systematic application of causal inference designs — such as difference-in-differences, regression discontinuity, matching, and instrumental variables — to measure the genuine effect of education programs, policies, or interventions by constructing a credible counterfactual: what would have happened to participants had they not been treated. | 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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