In this asignatura present and study the basic results of the model of classical linear regression: supposed, estimate by Ordinary Square Minima, contrasts of hypothesis and prediction. They analyse also some extensions of the Linear Model General (MLG) such as the use of the binary variables and the analysis of specification (errors of specification).
Know the technical econométricas basic for the analysis of data. Formulate relations between economic variables, quantify them and value the results obtained. Know use a model estimated and evaluated to obtain predictions.
1. Model of Linear Regression (MRL): Estimate MCO 1.1. Introduction 1.2. Formulation of the MRL: specification of the model and basic hypotheses. 1.3 Estimate MCO. 1.3.1. Estimate MCO in the model of simple regression 1.3.2 Estimate MCO in the model of multiple regression 1.3.3. Interpretation of the parameters estimated, units of measure and functional form. 1.4. Properties of the adjust MCO.
2. Properties of the estimators MCO 2.1 statistical Properties of the estimator MCO of %u03B2. 2.2 Estimate of %u03C32 and statistical properties of the estimator. 2.3 Matrix of variances estimated and standard errors. 2.4 Distribution of quadratic forms associated to the normal distribution. 2.6 Properties of the estimators MCO with normal errors
3. Contrasts of hypothesis in the MRL 3.1 Contrasts of hypothesis 3.1.1 Contrasts on an only coefficient. 3.1.2 Contrasts of a linear restriction 3.1.3 Contrasts of a group of linear restrictions 3.2 Estimate with linear restrictions. 3.3 Intervals of confidence
4. Binary variables. 4.1 binary Variables. 4.1.1 Models with an only qualitative factor. 4.1.2 Models with several qualitative factors. 4.1.3 Interaction between two fictitious variables. 4.1.4 Interaction between fictitious variables and quantitative variables. 4.2 Contrasts of structural change.
5. Specification and Prediction in the MLG 5.1 Errors of specification; selection of variables. 5.1.1 Inclusion of irrelevant variables. 5.1.2 Omission of notable variables. 5.2 Prediction. 5.2.1 Interval of confidence. 5.2.2 Interval of prediction.
Fernández Gallastegui, To. Econometría. Prentice Hall. 2005 Greene, W. H. Analysis econométrico. Prentice Hall. 1998. Wooldridge, J.M. Introduction to the Econometría -A modern approach-. Thomson Ed, 2006