Facultades y centros
Otros centros
Servicios administrativos
Servicios generales
Código:
41239
Profesor/a responsable:
MORA LOPEZ, JUAN
Crdts. ECTS:
5,00
Créditos teóricos:
1,20
Créditos prácticos:
0,40
Carga no presencial:
3,40
ESTA ASIGNATURA SE IMPARTE EN INGLÉS. LA INFORMACIÓN CONTENIDA EN ESTA GUÍA ESTÁ EN INGLÉS.
This is an optional course on Time Series Analysis in the second year of the Master in Quantitative Economics.
Competencias Generales del Título (CG)
Competencias específicas (CE)
Sin datos
This course builds on an earlier course in univariate time series and has
the following objectives:
1.To introduce the students to the main developments in time series
econometrics which have assumed considerable importance in the last two
decades.
2. To provide the students with an understanding of the relevant concepts
which are fundamental to an understanding of time series econometrics.
3. To examine, in detail, the statistical models that are in use and the
techniques and methods that are used in their analysis and to note their
strengths and limitations.
4. To consolidate the knowledge gained by solving simple problems
5. To provide the student with an ability to critically assess the many
applications of time series eonometrics to problems in economics
1. UNIVARIATE TIME SERIES
Brief review of ARMA models. Maximum likelihood estimation of ARMA
Models.
2. MULTIVARIATE TIME SERIES
Vector Autoregressions. Estimation. The Impulse Response Function. Weak exogeneity. Granger causality. Vector autoregressions and structural econometric models.
3. GENERALISED METHOD OF MOMENTS
Estimation by GMM. Asymptotic distribution of GMM estimators.
Instrumental variable estimation.
4. NON-STATIONARITY
Properties of estimators and tests in non-stationary models. Non-stationary time series. Spurious regressions. Integrated processes. Trend and difference
stationarity. Testing for unit roots.
5. COINTEGRATION AND ERROR CORRECTION MODELS
Testing for cointegration. Estimating the cointegrating vector. Hypothesis
Testing. Cointegration and its implications.
6. COINTEGRATION IN SYSTEMS OF EQUATIONS
Estimating cointegrating vectors in systems. Inference about the cointegration space. Asymptotic distributions of estimators of cointegrating vectors.
7. TIME SERIES MODELS OF HETEROSCEDASTICITY
ARCH and GARCH Models. Maximum likelihood estimation. Testing for
ARCH and GARCH models. Further extensions.
REFERENCES
The most comprehensive textbook in the field is J.D Hamilton (1994). Time Series Analysis, Princeton University Press. Despite being over eleven years old this is still the best book for our course. It will also be important for the follow up course in Semester 2. Numerous references will be made to this text but the more technical material will be avoided at this stage.
Sin datos
Time Series Analysis | |
Autor(es): | Hamilton, James D. |
Edición: | Princeton : Princeton University Press, 1994; |
ISBN: | 0-691-04289-6 |
Categoría: | Sin especificar |
Problem Sets: 50%. Final Exam: 50%. Those students with a final grade below 5 will have a second opportunity in the corresponding exam period, but the grade corresponding to problem sets will be kept.
Descripción | Criterio | Tipo | Ponderación |
Resolución de algunos de los problemas contenidos en las Hojas de Problemas | ENTREGA DE PROBLEMAS |
ACTIVIDADES DE EVALUACIÓN DURANTE EL SEMESTRE | 50 |
Examen sobre todo el contenido del curso | EXAMEN FINAL |
EXAMEN FINAL | 50 |
Convocatoria | Fecha | Hora | Grupo - Aula(s) asignada(s) | Observaciones |
(C2) Periodo ordinario para asignaturas de primer semestre | 20/12/2017 | 10:00 - 13:00 |
0031P2050 |
Grupo | Semestre | Turno | Idioma | Matriculados |
---|---|---|---|---|
Gr. 1 (CLASE TEÓRICA) : 1 | 1S | Todo el día | ANG | 10 |
Grupo | Semestre | Turno | Idioma | Matriculados |
---|---|---|---|---|
Gr. 1 (SEMINARIO / TEÓRICO-PRÁCTICO / TALLER) : 1 | 1S | Todo el día | ANG | 10 |