Running?

Not running 2005/06

Module leader

Dennis Leech

Context

In addition to your degree course regulations, see pages 21–22. The module provides the theoretical basis for all work in econometrics, which is not provided elsewhere in the degrees. The module complements the other core module EC226 Econometrics 1 by providing the theoretical foundations of the methods taught there. The prerequisite is a pass in EC124 Statistical Techniques B.

Teaching format

Two lectures per week and tutorials to be arranged

Assessment methods

3 hour final examination (80%) and two problem sets (20%)

Academic aims

To introduce basic econometric theory and provide students with a foundation for advanced study in econometrics in their third year.

Learning objectives

By the end of the module students will be able to understand the theoretical background to and the use of the general linear model in econometrics; be familiar with classical methods for testing statistical hypotheses derived from economic theory; and be able to apply the theory to the analysis of statistical and econometric data.

Learning methods

Attending lectures and completing problem sets

Syllabus

The first term covers basic statistical theory and matrix algebra essential for econometric theory. Estimation and inference in the general linear model is considered based on the least squares principle. The second term is primarily concerned with maximum likelihood. Restricted least squares, generalised least squares and simultaneous equation techniques are used as illustrations.

• Statistics: moment generating functions, properties of estimators, estimation, hypothesis testing.
• Matrix algebra: basic concepts, least squares estimation of the general linear model.
• Econometrics: maximum likelihood estimation, generalized least squares, estimation subject to linear restrictions, testing linear restrictions in the general linear model, identification and estimation of simultaneous equation models.

Illustrative reading

Hogg, R.V., and A.T. Craig, Introduction to Mathematical Statistics, Prentice Hall, 1995, (Fifth Edition)

Johnston, J., and J. DiNardo, Econometric Methods, McGraw Hill, 1997, (Fourth Edition)

Judge, G.G., et al., Introduction to the Theory and Practice of Econometrics, John Wiley, 1988.

Maddala, G.S., Introduction to Econometrics, Macmillan, 2001, (Third Edition).

Mood, A.M., et al., Introduction to the Theory of Statistics, McGraw Hill, 1974, (Third Edition).