Durham University
Programme and Module Handbook

Postgraduate Programme and Module Handbook 2019-2020 (archived)

Module ECON47615: Advanced Research Methods - Part II

Department: Economics and Finance

ECON47615: Advanced Research Methods - Part II

Type Tied Level 4 Credits 15 Availability Available in 2019/20
Tied to L1I101
Tied to N3I101
Tied to N3I201
Tied to N4I101

Prerequisites

  • • Advanced Research Methods – Part I

Corequisites

  • None

Excluded Combination of Modules

  • Microeconometrics (ECON47715) and the sub-area 'Estimating Treatment Effects using Microeconometric Data'

Aims

  • To acquire and demonstrate a specialist knowledge and understanding of quantitative aspects in the various areas of research;
  • To develop a critical understanding of empirical methods used in various areas of research;
  • To give students ‘hands-on’ experience with different analytic softwares such as STATA, SAS and Matlab;
  • To give students enough theoretical foundations so that they can perform various types of analyses on their own or with minimal guidance;
  • To give students important conceptual information about issues underlying the use of a variety of quantitative techniques in various topics in Accounting, Economics, Finance, and Islamic Finance.

Content

  • Students will be required to take any four of the sub-areas listed below based on their research orientation.
  • An indicative list of sub-areas to be offered is: • Economics of Accounting I • Economics of Accounting II • Asset Pricing Theory • Islamic Finance Research • Using Experimental Methods in Business Research • Estimating Treatment Effects using Microeconomic Data • DSGE modelling and its applications • Special topics and applications in game theory • Using SAS in Research • Using STATA for Econometric Analysis • Programming in Matlab

Learning Outcomes

Subject-specific Knowledge:
  • Have specialist knowledge and critical understanding of the on-going quantitative research in specified sub-areas.
  • Have advanced and up-to-date knowledge of relevant quantitative research methods and their accompanying analytical methods used in research;
  • Have advanced understanding of quantitative analytical techniques for handling complex quantitative data analysis.
Subject-specific Skills:
  • Ability to skilfully conduct quantitative research and data analysis in specific sub-areas;
  • Ability to critically assess quantitative existing research and analytical methods used in existing studies;
  • Ability to apply state of the art research methods to generate and analyse data;
  • Ability to defend chosen approaches 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 manage and maintain a complex dataset;
  • The ability to design the data analysis;
  • The ability to carefully evaluate the data requirements underpinning particular quantitative data analysis 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

  • This module will be run during Terms 2 and 3. The students are required to take any four of the sub-areas offered according to the training-needs identified by their supervisor(s).
  • Each of the sub-areas will be delivered in 7 contact hours (Lectures totalling 5 contact hours and Seminars totalling 2 contact hours).
  • 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.
  • By engaging with the recent debates in the literature, students will acquire both the capability and the attitude to critically evaluate and improve their research methods.
  • The assessment of the module is by a 4,000 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. The assignment will consist of parts that are based on all the sub-areas chosen.

Teaching Methods and Learning Hours

Activity Number Frequency Duration Total/Hours
Lectures 4 5 hours 20
Seminars 4 2 hours 8
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) 8 1 hour 8
Independent study, preparation and reading 114
Total 150

Summative Assessment

Component: Written assignment Component Weighting: 100%
Element Length / duration Element Weighting Resit Opportunity
Individual written assignment 4,000 words 100% same

Formative Assessment:

No specific formative assessment. Tutor-supported and self-supported learning will enable students to monitor their progress.


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