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Econometrics Assumptions of Classical Linear Regression Model

Econometrics I Summer 2011/2012 Course Guarantor :  prof. Ing. Zlata Sojková, CSc ., Lecturer : Ing. Martina Hanová, PhD. . Econometrics Assumptions of Classical Linear Regression Model. 7) Calculation of standardized coefficients or beta coefficients βj adj . = βj * R 2 *100 [%].

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Econometrics Assumptions of Classical Linear Regression Model

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  1. Econometrics I Summer 2011/2012 Course Guarantor:  prof. Ing. Zlata Sojková, CSc., Lecturer: Ing. Martina Hanová, PhD. EconometricsAssumptions of Classical Linear Regression Model

  2. 7) Calculation of standardized coefficients or beta coefficients βjadj. = βj * R2 *100 [%]

  3. Assumption of Ordinary Least Squares • Remember that OLS is not the only possible estimator of the βs • ButOLS is the best estimator under certain assumptions…

  4. Model is linear in parameters Assumption 1

  5. E(Y | Xi ) = β1 + β2Xi LRM E(Y | Xi) = β1 + β2 X2i E(Y | Xi ) = β1 + β22XiNRM Linear regression model

  6. Zeromeanvalueofdisturbances - ui. ASSUMPTION 2

  7. Equalvarianceofdisturbences - ui Errors have constant variance “homoskedasticity” Errors have non-constant variance “heteroskedasticity” ASSumption 3

  8. No autocorrelationbetweenthedisturbances The data are a random sample of the population ASSumption4

  9. Construction of var-cov matrix: vector ei * transpose vector ei variationcovariancematrix

  10. Zerocovariancebetweenui and Xi ASSumption5

  11. thenumberof >= thenumberof observationsexplanatoryvariables ASSumption6

  12. The errors are normally distributed Normal Probability Plot Assumption 7

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