Checking date: 06/05/2019


Course: 2019/2020

Econometric Techniques
(13650)
Study: Bachelor in Economics (202)


Coordinating teacher: GONZALO MUÑOZ, JESUS

Department assigned to the subject: Department of Economics

Type: Compulsory
ECTS Credits: 6.0 ECTS

Course:
Semester:




Competences and skills that will be acquired and learning results. Further information on this link
The goal of this course is understand the time evolution of the most relevant economic time series (GNP, Unemployment, inflation, interest rates, exchange rates, financial asset prices, etc.) and the analysis of the dynamic causal relationships existing among those variables in order to perform forecasts and economic policy analysis. To achieve this goal, the student must acquire knowledge, abilities (specific and general) and attitudes. Knowledge: At the end of the course the student will be able to: - Construct adequate models to obtain forecasts - Construct adequate models to analyze causal relationships between economic variables - To analyze the growth of economic variables and their long-term relationship. In term of concrete questions, the student will learn to answer in a quantitative and synthetic way, via an empirical project, to questions of this type: - How interest rates affect economic growth, employment level, prices, etc.? - How economic growth affects C02 levels, and those affect temperature? - Is it possible to forecast the returns of financial assets? Specific abilities: - Isolate and analyze the main characteristics of the evolution of economic data. - Distinguish different types of data and the components of a time series. - Build appropriate models for testing economic hypotheses and forecasting. - Evaluate and criticize different approaches for dealing with an applied problem. General skills - Solve complex problems. - Discrimination of relevant information contained in economic data on a problem. - Relate different description measures of data and diagnostics on the validity of a model. - Flexibility on the use of a model for different goals. - Use of computer packages of econometric modeling. - Analysis and synthesis. - Group work. - Oral, written and graphical communication skills. Attitudes: - Critic attitude on solutions and models provided by alternative analysts. - Constructive attitude based on partial information and approaches.
Description of contents: programme
The basic contents of the course are: - Characteristics of time series data. - Univariate statitionary models. - Forecasting and model selection. - The linear regression model with autocorrelated error: robust inference. - Dynamic single-equation econometric models: endogeneity problems. Instrumental variables solutions (Two Step Least Squares). Endogeneity tests. - Dynamic multi-equation models (VAR) and causality analysis. - Non stationary processes: trend-cycle decomposition. - Regression with nonstationary variables: testing different economic theories.
Learning activities and methodology
The teaching methodology minimizes the formal aspects, focusing on the intuitive discussion of concepts and intensive work with real data sets, aiming that the student reaches a practical mastering of econometrics with time series economic data. The course comprises lectures, and problem and practical classes: Lectures and problem classes: - They will use both blackboard and computer with projector. - Each section contains a typical empirical application. - The applied data analysis is performed with the packagae E-Views (or alternatively with the free software GRETL) and the database HIS Global Insight (reachable online through library). Computer practical classes: - Every week there will be a session in the computer room to solve applied empirical problems related with the empirical course project.
Assessment System
  • % end-of-term-examination 60
  • % of continuous assessment (assigments, laboratory, practicals...) 40
Basic Bibliography
  • Brockwell, P. & R. Davis. Introduction to Time Series and Forecasting (segunda edición). Springer-Verlag.
  • Enders, W. Applied Econometric Times Series (segunda edición). John Wiley.
  • Lectures Notes. http://www.eco.uc3m.es/~jgonzalo/teaching/TecnicasEconometricas.html. -. -
  • Notes de Clase. http://www.eco.uc3m.es/~jgonzalo/teaching/TecnicasEconometricas.html. -. -
  • Stock, J. & M. Watson. Introduction to Econometrics. Addison-Wesley.
  • Thomas Nechyba,. Intermediate Microeconomics an intuitive approach with calculus,. CENGAGE,. 2018
  • Wooldridge, J.. Econometrics: A Modern Approach (segunda edición) [Versión en español: Introducción a la Econometría: un enfoque Moderno]. South-Western.
Recursos electrónicosElectronic Resources *
Additional Bibliography
  • Aznar, A. y F.J. Trivez. Métodos de Predicción en Economía (vols 1 y 2). Ariel.
  • Diebold, F.. Elements of Forecasting (segunda edición). South-Western.
  • Koop, G.. Analysis of Economic Data. John Wiley.
  • Mills, T.C.. The Econometric Modelling of Financial Time Series. Cambridge UP.
  • Otero, J.M.. Econometría (Series Temporales y Predicción). AC.
  • Perez, C. Econometría de las Series Temporales. Pearson Prentice.
  • Perez, C. Problemas Resueltos de Econometría. Thompson.
  • Peña, D. Análisis de Series Temporales. Alianza Editorial.
(*) Access to some electronic resources may be restricted to members of the university community and require validation through Campus Global. If you try to connect from outside of the University you will need to set up a VPN


The course syllabus and the academic weekly planning may change due academic events or other reasons.


More information: http://www.eco.uc3m.es/~jgonzalo/teaching/TecnicasEconometricas.html