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Durham University

Postgraduate Modules 2019/2020

Module Description

Please ensure you check the module availability box for each module outline, as not all modules will run in each academic year. Each module description relates to the year indicated in the module availability box. Please be aware that modules may change from year to year, and may be amended to take account of, for example: changing staff expertise, disciplinary developments, the requirements of external bodies and partners, and student feedback.

Department: Economics and Finance

ECON47515: Advanced Research Methods - Part I

Type Tied Level 4 Credits 15 Availability Available in 2019/20
Tied to L1I101 with Integrated Studies (Economics) (Last intake of students October 2016)
Tied to N3I101 with Integrated Studies (Finance) (Last intake of students October 2016)
Tied to N3I201 with Integrated Studies (Islamic Finance) (Last intake of students October 2016)
Tied to N4I101 with Integrated Studies (Accounting) (Last intake of students October 2016)

Prerequisites

  • None

Corequisites

  • None

Excluded Combination of Modules

  • None

Aims

  • To provide a rigorous treatment of advanced statistics and econometrics and their applications to modelling and testing;
  • To give students advanced knowledge in conducting various types of statistical analyses;
  • To give students important conceptual information about issues underlying the use of a variety of quantitative techniques in research;
  • To ensure that students are aware of neighbouring methods that they can take advantage of for advanced quantitative study and data analysis;
  • To develop students’ ability to identify suitable analytical methods to answer their research questions.

Content

  • The core content of this module will be topics in advanced statistics and econometrics.
  • Indicative topics are : • Probability theory • Sampling statistics and distribution • Asymptotic theory • Nonparametric tests • Bayesian analysis • Panel data analysis

Learning Outcomes

Subject-specific Knowledge:
  • Have advanced and up-to-date knowledge of the principles and methods of modern financial econometrics and data analysis;
  • Have a comprehensive understanding of neighbouring analytical methods and the ability to robustly argue for and against the use of a particular approach;
  • Have advanced understanding of quantitative analytical techniques and interpretation of the results;
  • Have a comprehensive understanding of key methodological considerations and challenges for quantitative data generation or collection required for a particular analysis method to be potent;
  • Have extended their understanding of the use of econometric tools to conduct advanced empirical investigations into complex specialised issues.
Subject-specific Skills:
  • Ability to skilfully conduct quantitative research and statistical analysis;
  • Ability to understand state of the art econometric tools for analysing data;
  • Ability to defend chosen methods and objectively critique the application of alternative quantitative methods of research and analysis.
Key Skills:
  • The ability to organize research and analyze data to answer a particular research question;
  • The ability to appropriately model and analyze complex data generating characteristics;
  • The ability to design the data analysis;
  • The ability to carefully evaluate the data requirements underpinning particular quantitative methods and to consider the actions needed to execute complex studies.

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

  • The module will be delivered in a series of 10 lectures and 10 seminars during Term 1.
  • Learning will also occur through tutor-supported, as well as self-support learning groups thus enabling students to develop their own effective research methods strategies.
  • The assessment of the module is by a 3,500 word written assignment based on evaluating critical success factors tied to the successful acquisition of robust data for advanced quantitative data analysis and the selection and execution of appropriate analysis techniques.

Teaching Methods and Contact Hours

Activity Number Frequency Duration Total/Hours
Lecture 10 Weekly 2 hours 20
Seminars 10 Weekly 1 hour 10
Self-supported learning groups (students are expected to form their own discussion groups to reflect on and share their learning about the issues raised in the module) 10 Weekly 1 hour 10
Independent study, preparation and reading 110
Total 150

Summative Assessment

Component: Written assignment Component Weighting: 100%
Element Length / duration Element Weighting Resit Opportunity
Individual written assignment 3,500 words 100% same

Formative Assessment:

Students will be required to submit a 1,000 word planning document outlining aspects of advanced quantitative research methods and data analysis relevant to their research area.


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


    If you have a question about Durham's modular degree programmes, please visit our User Guide. If you have a question about modular programmes that is not covered by the User Guide, or a query about the Postgraduate Module Handbook, please contact us using the Comments and Questions form below.