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Regresia metódou najmenších štvorcov (OLS)×Systémová GMM (Arellano-Bover / Blundell-Bond)×
OdborEkonometriaEkonometria
RodinaRegression modelRegression model
Rok vzniku20191998
TvorcaWooldridge (textbook treatment); classical least squaresArellano & Bover (1995); Blundell & Bond (1998)
TypLinear regressionDynamic panel data estimator
Pôvodný zdrojWooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860Arellano, M. & Bond, S. (1991). Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. Review of Economic Studies, 58(2), 277-297. DOI ↗
Ďalšie názvyordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonuArellano-Bover estimator, Blundell-Bond estimator, dynamic panel GMM, Sistem GMM (Arellano-Bover / Blundell-Bond)
Príbuzné54
ZhrnutieOrdinary 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).System GMM is a generalized method of moments estimator for dynamic panel models that contain a lagged dependent variable. Introduced by Blundell and Bond (1998), building on Arellano and Bover, it augments the differenced equation of the earlier difference GMM (Arellano-Bond) with the equation in levels to deliver consistent estimates when N is large and T is small.
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ScholarGatePorovnať metódy: OLS Regression · System GMM. Získané 2026-06-18 z https://scholargate.app/sk/compare