1. Økonometri The regression model OLS Regression Ulf H. Olsson Professor of Statistics

2. Ulf H. Olsson Tema Multippel regresjon Hypotesetesting (sannsynlighetsfordelinger) Multikolinearitet og dummy variabler Residualanalyse Asymptotisk teori Instrumentvariabler Kap. 3 –13 (+ en del basics) Murray, Michael P. 2005

3. Ulf H. Olsson Forelesninger – Øvelser - Programvare Forelesninger tirsdager 14.30 – 17.15 (B2 – 060) 2 timer teori 1 time demonstasjon Øvelser I bruk av programvare (Eviews)

4. Ulf H. Olsson Variance, Covariance and Correlation

5. Ulf H. Olsson Covariance Matrix; Correlation Matrix

6. Ulf H. Olsson Regression Analysis

7. Ulf H. Olsson Regression analysis OLS Regression parameter St.error T-value P-value Confidence interval R-sq R-sq.adj F-value The error term

8. Ulf H. Olsson Regression Analysis The error term has constant variance The error term follows a normal distribution with expectation equal to zero The x-variables are independent of the error term The x-variables are linearly independent The dependent variable is normally distributed

9. Ulf H. Olsson Classical Assumptions Y is stochastic, x1, x2,….,xk are not Linearity in the parameters The error term has const.variance The error term is norm. Distributed with expectation equal to zero The error terms are independent The x-variables are linearly independent

10. Ulf H. Olsson GAUSS-MARKOV OLS is BLUE given the Classical Assumptions B = Best L=Linear U=Unbiased E=Estimator

11. Ulf H. Olsson Econometric Model Klein’s Model (1950 )

12. Ulf H. Olsson Making Numbers (OLS and TSLS) CT = 16.237+0.193*PT+0.0899*PT_1+0.796*WT, R² = 0.981 (1.303) (0.0912) (0.0906) (0.0399) 12.464 2.115 0.992 19.933 CT = 15.324+0.0763*PT+0.186*PT_1+0.828*WT, R² = 0.979 (1.453) (0.138) (0.146) (0.0439) 10.546 0.553 1.275 18.844

13. Ulf H. Olsson Estimate Klein’s equations by OLS Regression