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Hausmanov test špecifikácie (FE vs RE)×Hierarchical Linear Modeling (HLM / Multilevel Modeling)×Model fixných efektov pre panelové dáta×
OdborEkonometriaŠtatistikaEkonometria
RodinaRegression modelHypothesis testRegression model
Rok vzniku197819862014
TvorcaJerry A. HausmanRaudenbush & Bryk (popularized); Goldstein (parallel development)Hsiao (textbook treatment); within transformation of panel data
TypSpecification test for panel data modelsParametric nested-data regressionPanel data regression
Pôvodný zdrojHausman, J. A. (1978). Specification Tests in Econometrics. Econometrica, 46(6), 1251–1271. DOI ↗Raudenbush, S.W. & Bryk, A.S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. ISBN: 978-0761919049Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗
Ďalšie názvyHausman specification test, FE vs RE test, Durbin-Wu-Hausman test, Hausman Spesifikasyon Testi (FE vs RE)HLM, MLM, multilevel modeling, multilevel analysisfixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli
Príbuzné545
ZhrnutieThe Hausman test is a specification test, introduced by Jerry A. Hausman in 1978, that decides between the fixed-effects (FE) and random-effects (RE) estimators in panel data models. The null hypothesis is that the random-effects estimator is consistent and efficient and should be preferred; the alternative is that random effects is inconsistent and fixed effects is required because the unit-specific effects are correlated with the explanatory variables.Hierarchical Linear Modeling (HLM), also known as Multilevel Modeling (MLM), is a parametric statistical method for analyzing nested or clustered data — for example students within classrooms, patients within hospitals, or employees within organizations. Formalized by Raudenbush and Bryk in their 2002 seminal text (building on work from the mid-1980s), HLM simultaneously estimates individual-level and group-level effects while correctly partitioning variance across levels.The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014).
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ScholarGatePorovnať metódy: Hausman Test · Hierarchical Linear Modeling · Panel Fixed Effects. Získané 2026-06-18 z https://scholargate.app/sk/compare