Dates: 8 - 26 July, 2013
This is a introductory econometrics course combining an orthodox technical treatment of the subject with a presentation which makes extensive use of state-of-the-art computer video graphics. The aim of the course is to provide the basic knowledge of econometrics that is now essential equipment for any serious economist, with the development of an intuitive understanding of the material being a major objective. Although the course is challenging, the mathematical demands on the student have been kept to a minimum.
The first part of the course introduces the statistical tool known as ordinary least squares (OLS) regression analysis as applied to cross-sectional data. It begins with the use and properties of the classical linear regression model and then discusses the handling of extensions and violations of the assumptions. Among these are:
■tests of linear restrictions
■heteroscedasticity, tests and remedial measures
■consequences of measurement errors
■instrumental variables estimation
■use of finite-sample simulation to complement asymptotic analysis
■simultaneous equations estimation
The second part of the course discusses the application of the regression model to time series data, covering the following topics:
■autoregressive distributed lag models; properties of OLS estimators
■autocorrelation, tests and remedial measures
■specific-to-general and general-to-specific model specification
The course concludes with an optional, non-examinable section on three relatively advanced topics:
■panel data. models: fixed effects (within-group, first differences, and least squares dummy variables) and random effects;
■binary choice models (probit, logit, tobit, sample selection bias);
■introduction to nonstationary time series models, unit roots, cointegration, and error correction models.
Although the course does not make use of matrix algebra, it is ambitious in content and technically rigorous, giving emphasis to the analysis of the finite sample and asymptotic properties of least squares and instrumental variables estimators under different assumptions concerning the data generation process and to the accompanying implications for statistical inference. Examples of simple applications in economics are used throughout. In addition to the formal theory sessions, participants take part in daily workshops using Stata to fit educational attainment and wage equation models with cross-sectional data and EViews to fit demand functions with time series data. Technical support is provided for the use of these applications.
C. Dougherty, Introduction to Econometrics, Oxford University Press, (4th edition) 2011.
Lectures: 36 hours Classes: 12 hours
Assessment: Two written examinations
Contenido del curso: 12 horas de clase semanales por las mañanas y conferencias y seminarios por las tardes en función del curso elegido.
Precio total: 3.980 €