Durham University
Programme and Module Handbook

Postgraduate Programme and Module Handbook 2016-2017 (archived)

Module ECON47815: Econometric Methods

Department: Business School (Economics and Finance)

ECON47815: Econometric Methods

Type Tied Level 4 Credits 15 Availability Available in 2016/17 Module Cap None.
Tied to L1T109
Tied to L1T209
Tied to L1T309
Tied to L1T409
Tied to N3K109
Tied to N3K209
Tied to N3K309
Tied to N3K409
Tied to N3K509
Tied to N3K609
Tied to N3K709
Tied to N3K809

Prerequisites

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

Corequisites

  • None

Excluded Combination of Modules

  • Econometrics I (ECON41515) and Econometrics II (ECON41615)

Aims

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

Content

  • Linear Regression Model using some Matrix Algebra, Gauss-Markov, Identification, OLS, finite sample properties of the OLS estimator
  • Hypothesis testing and Confidence intervals
  • Asymptotic properties of the OLS estimator
  • Misspecification and dummy variables
  • GLS, autocorrelation and heteroskedasticity
  • Endogeneity, Simultaneity, Instrumental Variables (IV) estimation
  • Maximum Likelihood (ML)
  • Binary Choice Models (Logit/Probit)

Learning Outcomes

Subject-specific Knowledge:
  • By the end of the module students should:
  • have a thorough knowledge of the key econometric concepts, 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;
  • have problem solving skills and have practised 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, seminars, computer classes 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, concepts and principles, and their 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 10 1 per week 2 hours 20
Seminars 8 1 per week 1 hour 8
Computer classes 4 1 hour 4
Preparation & Reading 118
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:

Work prepared by students for seminars; answers to questions either discussed during a seminar, or posted on DUO; feedback on discussions with teaching staff during consultation hours, or via e-mail.


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