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Mínims Quadrats Ordinaris Agrupats per a Dades de Panell×Regressió per Mínims Quadrats Ordinàris (MQO)×
CampEconometriaEconometria
FamíliaRegression modelRegression model
Any d'origen20102019
Autor originalJeffrey Wooldridge (treatment)Wooldridge (textbook treatment); classical least squares
TipusLinear regression on stacked panel observationsLinear regression
Font seminalWooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0-262-23258-8Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
ÀliesPooled OLS, Pooled Ordinary Least Squares, Simple Panel OLS, Havuzlanmış EKKordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Relacionats25
ResumPooled 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.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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ScholarGateCompara mètodes: Pooled OLS · OLS Regression. Recuperat el 2026-06-17 de https://scholargate.app/ca/compare