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Model Kesilahan Rawak (Random Effects Panel Model)×Ordinary Least Squares Terpukal untuk Data Panel×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal19782010
PengasasBaltagi (textbook treatment); Hausman specification testJeffrey Wooldridge (treatment)
JenisPanel data regressionLinear regression on stacked panel observations
Sumber perintisHausman, J. A. (1978). Specification Tests in Econometrics. Econometrica, 46(6), 1251-1271. DOI ↗Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0-262-23258-8
Aliasrandom effects panel regression, RE estimator, GLS panel estimator, Panel Rassal Etkiler ModeliPooled OLS, Pooled Ordinary Least Squares, Simple Panel OLS, Havuzlanmış EKK
Berkaitan52
RingkasanThe 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.Pooled OLS applies standard ordinary least squares to panel data by stacking all cross-sectional and time observations into a single dataset and ignoring the panel structure during estimation. It is the most transparent starting point for panel data analysis, widely used in economics, finance, and social sciences when researchers wish to estimate average partial effects across individuals and time periods without imposing strong distributional assumptions about unobserved heterogeneity.
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ScholarGateBandingkan kaedah: Random Effects Panel Model · Pooled OLS. Dicapai 2026-06-17 daripada https://scholargate.app/ms/compare