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Salīdzināt metodes

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Kontrafaktiskās ietekmes novērtēšana (CIE)×Diferenču starpībām (Diff-in-Diff)×
NozareCēloņsakarību secināšanaEkonometrija
SaimeRegression modelRegression model
Izcelsmes gads1970s–2000s1994
AutorsHeckman, Imbens, Rubin, and the program evaluation literatureCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TipsCausal inference / program evaluationCausal inference / panel regression
PirmavotsHeckman, J. J., & Vytlacil, E. J. (2007). Econometric evaluation of social programs, Part I: Causal models, structural models and econometric policy evaluation. Handbook of Econometrics, 6B, 4779-4874. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Citi nosaukumiCIE, counterfactual evaluation, counterfactual policy evaluation, impact evaluationdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Saistītās55
KopsavilkumsCounterfactual Impact Evaluation is a family of causal methods that estimates the effect of an intervention by comparing what actually happened to participants with what would have happened had the intervention not taken place. Formalised in the Rubin Causal Model and extended by Heckman, Imbens and others, CIE underlies most modern program and policy evaluation practice.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 · Difference-in-Differences. Izgūts 2026-06-17 no https://scholargate.app/lv/compare