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Model slučajnih učinaka za panel podatke×Regresija običnih najmanjih kvadrata (OLS)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka19782019
TvoracBaltagi (textbook treatment); Hausman specification testWooldridge (textbook treatment); classical least squares
VrstaPanel data regressionLinear regression
Temeljni izvorHausman, J. A. (1978). Specification Tests in Econometrics. Econometrica, 46(6), 1251-1271. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Drugi nazivirandom effects panel regression, RE estimator, GLS panel estimator, Panel Rassal Etkiler Modeliordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Srodne55
SažetakThe random effects model is a panel data estimator that explains an outcome using both within-unit and between-unit variation, treating the unobserved unit-specific heterogeneity as a random, normally distributed term rather than a fixed parameter. Its validity is judged with the Hausman (1978) specification test, and it is developed in standard treatments such as Baltagi's Econometric Analysis of Panel Data.Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).
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ScholarGateUsporedite metode: Random Effects Panel Model · OLS Regression. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare