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Durham University

Postgraduate Module Handbook 2022/2023

Archive Module Description

This page is for the academic year 2021-22. The current handbook year is 2022-23
No such Code for pgprog: N3KA09

Department: Economics and Finance


Type Tied Level 4 Credits 15 Availability Not available in 2021/22
Tied to N3KA09


  • 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.


  • None

Excluded Combination of Modules

  • Econometrics (Online) - ECON45315


  • The syllabus examines the area of statistics and econometrics and develops the skills necessary to pursue empirical research in finance;. This syllabus focuses on the respective role of using econometrics in analysing data and presenting the results. In addition the syllabus explores problem solving and analytical skills necessary to the understanding of data trends and correlation and the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation;
  • To provide students with the econometrics skills necessary to pursue empirical research in finance and economics, and provide the opportunity to apply those in a project;
  • To provide students with an advanced understanding of empirical research


  • The content focuses on how to approach empirical research questions methodologically, and covers in particular the following methods: 
  • 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. 
  • in doing the above, students will make use of databases and software

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: 
  • report and interpret financial information in a logical and clear way 
  • apply appropriate methods of data analysis 
  • be able to operate independently, using a range of econometric tools and exercise appropriate judgment to conduct their own empirical investigations into a relevant topic 
  • have practised advanced problem solving and research skills and the use of econometric software 
  • have the ability to apply econometric methods and interpret the results at an advanced level 
  • be aware of, and familiar with, the facilities available for obtaining relevant data to facilitate empirical investigation
Key Skills:
  • select and apply a range of numerical techniques to present and interpret financial information in a recognised format;
  • work independently and with others to solve problems within a specified time constraint
  • use IT to assemble, analyse and communicate financial information;
  • manage and organise study time and utilise a range of study skills so that knowledge and subject-specific skills can be applied to solve problems in a selective and critical manner;
  • reflect on the learning process so that it can be applied in the context of the world of work.

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

  • Learning outcomes will be met through a combination of taught input, groupwork, case studies and discussion, supported by guided reading and specially-written self-study material.
  • The summative assessment of the module is a case study based assignment which builds throughout the module and is designed to test students' knowledge of key econometrics methods and principles, and their ability to apply relevant tools and problem-solving skills and interpret the results. Students practise and learn quantitative techniques, which are also used in experimental research, and apply them in a project, which forms part of the summative assessment of the module.

Teaching Methods and Learning Hours

Activity Number Frequency Duration Total/Hours
Workshops (a combination of taught input, groupwork, case studies and discussion), timetabled in blocks 24
Preparation and reading 126
Total 150

Summative Assessment

Component: Assignment Component Weighting: 100%
Element Length / duration Element Weighting Resit Opportunity
Written assignment 3000 words 100% Same

Formative Assessment:

Short-answer questions and case study exercises.

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