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ECON41515: ECONOMETRIC ANALYSIS

It is possible that changes to modules or programmes might need to be made during the academic year, in response to the impact of Covid-19 and/or any further changes in public health advice.

Type Tied
Level 4
Credits 15
Availability Available in 2023/24
Module Cap
Location Durham
Department Economics

Prerequisites

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

Corequisites

  • None

Excluded Combinations 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 empirival 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, 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 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

ActivityNumberFrequencyDurationTotalMonitored
Lectures91 per week2 hours18 
Revision1Once2 hours2 
Seminars/workshops42 hours8Yes
Computer classes42 hours8Yes
Preparation and reading114 
Total150 

Summative Assessment

Component: ExaminationComponent Weighting: 75%
ElementLength / DurationElement WeightingResit Opportunity
On campus written examination2 hours100Same
Component: ProjectComponent Weighting: 25%
ElementLength / DurationElement WeightingResit Opportunity
Project1000 words (maximum)100Same

Formative Assessment

One formative assessment to prepare students for the summative examination.

More information

If you have a question about Durham's modular degree programmes, please visit our Help page. If you have a question about modular programmes that is not covered by the Help page, or a query about the on-line Postgraduate Module Handbook, please contact us.

Prospective Students: If you have a query about a specific module or degree programme, please Ask Us.

Current Students: Please contact your department.