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Kontrafaktisku seku novērtēšana izglītības pētniecībā×Diferenču starpībām (Diff-in-Diff)×
NozareCēloņsakarību secināšanaEkonometrija
SaimeRegression modelRegression model
Izcelsmes gads2000s–2010s1994
AutorsBlundell & Costa Dias; formalized for EU education policy by the European Commission Joint Research CentreCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TipsQuasi-experimental causal inference frameworkCausal inference / panel regression
PirmavotsBlundell, 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
Citi nosaukumiCIE in education, counterfactual program evaluation, causal impact evaluation, education policy impact evaluationdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Saistītās55
KopsavilkumsCounterfactual 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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ScholarGateSalīdzināt metodes: Counterfactual Impact Evaluation in Education Research · Difference-in-Differences. Izgūts 2026-06-19 no https://scholargate.app/lv/compare