Further Econometrics

Module code: ECN340

This module is designed to introduce students to a number of important topics in econometrics.

Aims of the module

The aims of the module are:

  • to provide an introduction to further econometric techniques
  • to give an overview of modern econometric methodology
  • to give an introduction to applied econometric research methods

Learning objectives

By the end of the module students should have:

  • the skills required to employ a broad spectrum of econometric techniques
  • an appreciation of recent methodological issues in econometrics
  • the ability to undertake applied econometric work

Syllabus

Regression analysis: regression analysis, simultaneous equation, Generalised Method of Moments (GMM) model of expectations, applications

Introduction to time series: introduction and basic concepts, non-stationary series and integrated processes, co-integration

Introduction to panel data: simple regression models with variable intercept, dynamic models with variable intercept

Teaching methods

Lectures and workshops

Assessment

An unseen examination (75%) plus an individual computing project (25%)

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

There is no set text for this module, as it is very difficult to find a book that covers all the different topics.

Greene, W (2008) Econometric Analysis, 6th edition, Prentice Hall is very thorough but advanced and covers many topics we will not look at

Maddala, GS (2001) Introduction to Econometrics, 3rd edition, John Wiley & Sons

Hamilton JD (1994), Time Series Analysis, Princeton University Press

Johnston, J; DiNardo, J (1997), Econometric Methods, 4th edition, McGraw-Hill

Prerequisites ECN216 or ECN219. For students who have taken ECN219, a minimum mark of 60 is required. Students who obtain a mark below 60 for ECN216 must discuss this with the Module Leader.

Module leader Kostas Mouratidis

Please note that the leader may change before the module begins

Semester Autumn

Credits 20