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Salīdzināt metodes

Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.

Daudzperiodu saskaņošanas novērtētājs×Diferenču starpībām (Diff-in-Diff)×
NozareCēloņsakarību secināšanaEkonometrija
SaimeRegression modelRegression model
Izcelsmes gads20051994
AutorsAbadie (2005); Imbens & Wooldridge (2009)Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TipsQuasi-experimental / causal inferenceCausal inference / panel regression
PirmavotsAbadie, A. (2005). Semiparametric Difference-in-Differences Estimators. Review of Economic Studies, 72(1), 1-19. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Citi nosaukumipanel matching estimator, longitudinal matching, multi-wave matching, repeated-cross-section matchingdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Saistītās65
KopsavilkumsThe multi-period matching estimator extends the standard matching framework to settings with multiple time periods, pairing each treated unit to similar untreated units based on pre-treatment covariates or propensity scores, then using within-pair before-after differences to estimate the average treatment effect on the treated (ATT). Leveraging repeated observations, it simultaneously controls for observed confounders and time-invariant unobserved heterogeneity.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: Multi-period Matching Estimator · Difference-in-Differences. Izgūts 2026-06-17 no https://scholargate.app/lv/compare