Facultades y centros
Otros centros
Servicios administrativos
Servicios generales
Código:
41209
Profesor/a responsable:
COLLADO VINDEL, MARIA DOLORES
Crdts. ECTS:
6,00
Créditos teóricos:
1,60
Créditos prácticos:
0,40
Carga no presencial:
4,00
This is the first course in Econometrics in the master program. Students have taken Statistics in the previous semester.
Competencias Generales del Título (CG)
Competencias específicas (CE)
Sin datos
The objective of this course is to provide an introduction to the application of statistical methods in econometrics. The course covers estimation and inference in linear models, including regression and instrumental variables. The last part of the course is devoted to introduce the students into the analysis of Time Series models.
1. Introduction
1.1 Introduction.
1.2 Conditional expectations. Features and properties.
1.3 Linear projections.
2. The single-equation linear model. OLS estimation.
2.1 The single-equation linear model.
2.2 The OLS estimator.
2.2.1 Asymptotic properties.
2.2.2 Finite sample properties.
2.2.3 Inference.
2.3 Omitted variables.
2.4 Measurement errors.
3. Instrumental variables estimation of single-equation linear models.
3.1 Instrumental variables. The simple IV estimator.
3.1.1 Asymptotic properties.
3.1.2 Inference.
3.2 The generalized method of moments.
3.2.1The two-stage least squares estimator.
3.2.2 Asymptotic properties.
3.2.3 Inference.
3.2.4 The optimal GMM estimator.
3.2.5 Optimal Instruments.
3.3 IV solutions to the omitted variables and measurement errors problems.
4. Additional single-equation topics.
4.1 Generated regressors and instruments.
4.2 Some specification tests.
4.3 Other sampling schemes.
5. Time series models
5.1 Basic concepts in time series.
5.2 ARMA models.
6. Linear Regression with Time Series Data
6.1 Finite Sample Properties of OLS under Classical Assumptions.
6.2 Functional Form and Dummy Variables. Trends and Seasonality.
6.3 Asymptotic Properties of OLS.
6.4 Properties of OLS with Serially Correlated Errors.
6.5 Testing for Serial Correlation.
6.6 Correcting for Serial Correlation with Strictly Exogenous Regressors: GLS and FGLS.
Sin datos
Time Series Analysis | |
Autor(es): | Hamilton, James D. |
Edición: | Princeton : Princeton University Press, 1994; |
ISBN: | 0-691-04289-6 |
Categoría: | Básico |
Econometric analysis of cross section and panel data | |
Autor(es): | Wooldridge, Jeffrey M. |
Edición: | Cambridge : MIT Press, 2010; |
ISBN: | 978-0-262-23258-6 |
Categoría: | Sin especificar |
Students will be given problem sets and will have to hand them in on established dates. The problem sets will be graded, and the solutions to the problem sets will be discussed in class. The grade will be based on a final exam (50%), a midterm exam (40%) and problem sets (10%).
There will be a retake exam in July that will count 90% of the grade. The other 10% are the problem sets.
Descripción | Criterio | Tipo | Ponderación |
Midterm exam | There will be theoretical questions and empirical exercises |
ACTIVIDADES DE EVALUACIÓN DURANTE EL SEMESTRE | 40 |
Problem sets | Students will be given problem sets and will have to hand them in on established dates. The problem sets will be graded, and the solutions to the problem sets will be discussed in class. |
ACTIVIDADES DE EVALUACIÓN DURANTE EL SEMESTRE | 10 |
final exam | There will be theoretical questions and empirical exercises |
EXAMEN FINAL | 50 |
Grupo | Semestre | Turno | Idioma | Matriculados | En matrícula, asignado a |
---|---|---|---|---|---|
Gr. 1 (CLASE TEÓRICA) : 1 | 2S | Todo el día | ANG | 12 |
|
Grupo | Semestre | Turno | Idioma | Matriculados | En matrícula, asignado a |
---|---|---|---|---|---|
Gr. 1 (PRÁCTICAS DE PROBLEMAS / TALLER) : 1 | 2S | Todo el día | ANG | 12 |
|