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Syllabus

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Autores: César Alonso-Borrego, Jesús Carro
Programa de la asignatura: Temas que forman parte de la asignatura.

1. INTRODUCTION.

  • Economic data and econometric modeling. Causality and the ceteris paribus notion in econometric analysis. Observational vs. Experimental data. Consequences on econometric modeling.

 

2. THE SIMPLE LINEAR REGRESSION MODEL.

  • Assumptions. Coefficient interpretation. The OLS (Ordinary Least Squares) estimator and its properties. The variance of the OLS estimator.

 

3. THE MULTIPLE LINEAR REGRESSION MODEL.

  • Assumptions. Relation between the linear simple and multiple regression model: short vs. long regression. OLS estimation of coefficients and variance estimation. Goodness of fit. Coefficient interpretation. Most usual transformations. Calculation of elasticities. Inference. Tests about a single parameter. Tests about a linear combination of parameters. Tests about several linear constraints.

 

4. REGRESSION ANALYSIS WITH QUALITATIVE INFORMATION: BINARY VARIABLES.

  •  Binary variables. A single independent binary variable. Sets of binary variables for multiple categories. Interactions with binary variables. Coefficient interpretation.

 

5. SPECIFICATION ERRORS.

  • Inclusion of irrelevant variables and omission of relevant variables. Consequences on estimation. Measurement errors. Consequences on estimation.

 

6. MODELS WITH ENDOGENOUS EXPLANATORY VARIABLES.

  • The concept of endogeneity and its sources. The method of instrumental variables (IV). Valid instruments. The two-stage least squares estimator (2SLS). Endogeneity tests (Hausman tests). Instrument validation: tests of overidentifying restrictions (Hansen-Sargan tests).

 

7. HETEROSKEDASTICITY.

  • The regression model with heteroskedasticity. Consequences on OLS estimation and 2SLS estimation. Heteroskedasticity—robust inference: White or Eicker-White estimator of the variances.

 

8. AUTOCORRELATION.

  • The regression model with time-series data. Consequences on OLS estimation Autocorrelation-robust inference: Newey-West estimator of the variances. Autocorrelation tests.