Durham University
Programme and Module Handbook

Postgraduate Programme and Module Handbook 2012-2013 (archived)

Module ECON41515: ECONOMETRICS I

Department: Business School (Economics and Finance)

ECON41515: ECONOMETRICS I

Type Tied Level 4 Credits 15 Availability Available in 2012/13
Tied to N3K109
Tied to N3K209
Tied to N3K309
Tied to N3K409
Tied to N3K509
Tied to N3K609
Tied to N3K709

Prerequisites

  • One module at a level equivalent to a second year British Honours Degree standard, covering statistics and in particular covering at least probability theory and distributions as well as hypothesis testing.

Corequisites

  • None

Excluded Combination of Modules

  • None

Aims

  • to provide students with some of the econometrics skills necessary to pursue empirical research in finance;
  • to provide a basis for understanding more advanced econometric techniques to be taught in the second term of the MSc.

Content

  • Note: the following list is indicative and not all topics may be covered each year.
  • Introduction: what is Econometrics?
  • distribution theory and hypothesis testing;
  • three bases for choosing an estimation method: residual sum of squares, MLE and GMM;
  • bivariate regression analysis: the population regression function and its stochastic specification; the sample regression function;
  • the multivariate model: derivation, and contrast with the bivariate model;
  • specification testing;
  • misspecification testing, including heteroskedasticity, normality and serial correlation;
  • generalised method of moments.

Learning Outcomes

Subject-specific Knowledge:
  • By the end of the module students should:
  • have a thorough knowledge of the key econometrics principles and methods.
Subject-specific Skills:
  • By the end of the module students should:
  • have the ability to apply econometric methods and interpret the results at an advanced level;
  • be able to use a range of econometric tools to conduct their own empirical investigations into financial issues;
  • have practised problem solving skills and the use of econometric software.
Key Skills:
  • Written Communication;
  • Planning, Organising and Time Management;
  • Problem Solving and Analysis;
  • Using Initiative;
  • Numeracy;
  • Computer Literacy.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • A combination of lectures, lab (computer) classes, problem-based workshops and guided reading will contribute to achieving the aims and learning outcomes of this module. The summative assessment comprises a two-hour examination to test students' knowledge of key econometrics methods and principles, and problem-solving skills, plus a short project to test their ability to apply these methods and interpret the results.

Teaching Methods and Learning Hours

Activity Number Frequency Duration Total/Hours
Lectures 9 1 per week 2 hours 18
Workshops 8 1 per week 1 hour 8
Lab classes 4 1 per week 1 hour 4
Preparation & Reading 118
Revision Sessions 2 1 hour 2
Total 150

Summative Assessment

Component: Examination Component Weighting: 75%
Element Length / duration Element Weighting Resit Opportunity
Written Examination 2 hours 100% Same
Component: Project Component Weighting: 25%
Element Length / duration Element Weighting Resit Opportunity
Econometrics project 1000 word (maximum) excluding equations, tables and graphs 100% Same

Formative Assessment:

Multiple-choice test. Students also receive feedback on work undertaken in workshops and lab classes.


Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University