Durham University
Programme and Module Handbook

Postgraduate Programme and Module Handbook 2024-2025

Module ECON41515: ECONOMETRIC ANALYSIS

Department: Economics

ECON41515: ECONOMETRIC ANALYSIS

Type Tied Level 4 Credits 15 Availability Available in 2024/2025 Module Cap
Tied to L1T109
Tied to L1T409
Tied to L1T609
Tied to N3K709

Prerequisites

  • One econometrics module or equivalent quantitative module covering basic statistics and probability theory including distributions as well as hypothesis testing.

Corequisites

  • None

Excluded Combination of Modules

  • Econometric Methods (FINN41715); Financial Modelling and Business Forecasting (FINN41615)

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 programme.

Content

  • Linear Regression Model using Matrix Algebra, Gauss-Markov, Identification, OLS, finite sample properties of the OLS estimator
  • Hypothesis testing and Confidence intervals
  • Asymptotic properties of the OLS estimated
  • Misspecification and dummy variables
  • GLS, autocorrelation and heteroskedasticity
  • Endogeneity, Simultaneity, Instrumental Variables (IV) estimation
  • Generalized Methods of Moments (GMM)
  • Maximum Likelihood (ML)

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, Organisation 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, workshops, 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 rest students' knowledge of key econometrics concepts, methods 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 9 1 per week 2 hours 18
Revision 1 Once 2 hours 2
Workshops 4 2 hours 8
Computer classes 4 2 hours 8
Preparation and reading 114
Total 150

Summative Assessment

Component: Examination Component Weighting: 75%
Element Length / duration Element Weighting Resit Opportunity
One in-person written examination 2 hours 100% Same
Component: Project Component Weighting: 25%
Element Length / duration Element Weighting Resit Opportunity
Project 1000 words (maximum) 100% Same

Formative Assessment:

One formative assessment to prepare students for the summative examination.


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