Authorised by Academic Registrar, April 1996
Objectives On completion of this subject students should feel confident about undertaking straightforward empirical work with economic and accounting data, and have a preparation for more advanced study of the techniques of applied econometrics; understand the properties and limitations of classical multiple regression analysis; understand the role of tests which can be applied to an estimated regression model in order to determine its usefulness in explaining a relationship between variables; understand the role of procedures which can be followed to overcome limitations of the classical model.
Synopsis An introduction to linear multiple regression techniques; properties of least squares estimators; probability distributions and their applications to hypothesis testing; an introduction to the generalised least squares estimator; the problems of serial correlation, heteroscedasticity and multicollinearity; the use of dummy variables; the choice of an appropriate functional form; study of the application of the techniques and tests, through the study of published empirical work and the data sets used in them.
Assessment Test on matrices (45 minutes): 10% + Written (1 assignment [computing and report]): 30% + Examination (2 hours): 60%