MLR model. Inference.

17 Abril 2014, 14:30 • NICOLETTA ROSATI

Adjusted R-squared.

Discussion of exercises n. 3.1, 3.6, C3.2 and C3.3 from exercises sheet on MLR.

Introduction to inference in the MLR. Types of statistical hypotheses.

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Multiple Linear Regression

15 Abril 2014, 12:00 • NICOLETTA ROSATI

Functional form: quadratic terms and interactions. Examples.

Properties of OLS estimator. Gauss-Markov theorem and corollary. Omitted variables. Irrelevant variables. Decomposition of the variance of the OLS estimator.

Discussion of exercises n. 3.5 and 3.8 from exercises sheet on MLR.

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Multiple Linear Regression model

11 Abril 2014, 12:30 • NICOLETTA ROSATI

OLS estimation in the MLR model. Fitted values and residuals. Properties of residuals. R² coefficient.

Functional form: Log-linear and log-log models. Computation of semi-elasticities. Examples.

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Conclusion of SLR. Introduction to MLR.

10 Abril 2014, 14:30 • NICOLETTA ROSATI

Estimation of the error variance in the SLR model.

Discussion of exercises n. 2.1, 2.3, 2.5, 2.10 and 2.11 from exercises sheet on SLR.

Introduction to Multiple Linear Regression: motivation, model specification and matrix notation.

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Simple Linear Regression

8 Abril 2014, 12:00 • NICOLETTA ROSATI

Properties of OLS estimators (cont.). Change of location and scale of variables. Non-linearities. Interpretation of coefficients and their estimates. Examples.

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