Module code: ECN216 and ECN308

Econometrics provides the methodology and statistical techniques to test empirically the validity of economic hypotheses and to construct models to explain the evolution of the economic environment. An appreciation of econometrics is essential to understanding most current research work in economics.

There are also wide-ranging applications in related fields such as finance, marketing and forecasting.

Aims of the module

The aims of the module are:

  • to consolidate the statistical theory met in the prerequisite module(s)
  • to provide an introduction to econometric theory and practice
  • to give an introduction to empirical work in econometrics

Learning objectives

On completion of the course students will have:

  • an overview of econometric methodology
  • an understanding of basic econometric techniques, examining both their theoretical justifications and limitations, and their practical application
  • understanding of how econometric techniques may be applied to investigate issues in economic theory


Use of econometric software. Methodology. Review of statistical inference and simple regression. The General Linear Model. Linear probability model. Introduction to time series analysis. Applications to economics.

Teaching methods

Lectures plus workshops; exercises are set regularly, most of which involve use of econometric software


An unseen examination (50%), a class test (20%) and an individual assignment involving use of econometric software (30%)

Basic reading

We advise you not to buy books before the module begins, as the reading list may change. If you wish to read in advance, look for these texts in the University library

Wooldridge, J (2014) Introduction to Econometrics, Cengage (course text)

Gujarati, D and Porter, D (2009) Basic Econometrics, McGraw-Hill

Kennedy, P (2003) A Guide to Econometrics, 5th edition, Blackwell

Prerequisites ECN130 and either ECN120 or equivalent MAS units

Restrictions Cannot be taken with ECN219, ECN308 or ECN309

Module leader Simon Tebbutt

Please note that the leader may change before the module begins

Semester Academic year

Credits 20