MSc Development Finance

Year of entry: 2024

Course unit details:
Research Skills for Economic Development 1 (Quantitative Methods)

Course unit fact file
Unit code MGDI60301
Credit rating 15
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 1
Available as a free choice unit? No


The course unit covers theory, relevant applications and practical exercises in computer workshops. Much emphasis is placed on developing experience and confidence in the use of statistical software. Empirical work, using alternative forms of regression analysis, forms an increasingly important foundation for policy analysis and evidence based policy advice in economics and other branches of the social sciences. Therefore, acquiring competence in this field through the course will be of great value to development practitioners as well as those aiming for academic and other development-related careers.


The unit aims to enable students through development of theoretical insights and practical skills to become:

  • Competent users of statistics and econometrics methods.
  • Able and critical readers of academic articles with empirical contents

Learning outcomes

On completion of this unit successful students will be able to:

Knowledge and understanding

  • Explain the theoretical foundation of multiple regression analysis and effectively address common violations of the standard assumptions of the classical regression model.
  • Explain the techniques for econometric analysis of cross sectional data analysis.

Intellectual skills

  • Apply concepts in statistics and econometrics and critique statistical and econometric results presented in published articles and journals.
  • Employ concepts in statistics and econometrics to examine and analyse cross-section and time series data.

Practical skills

  • Produce empirical work, using alternative forms of regression analysis.
  • Analyse and interpret regression results.

Transferable skills and personal qualities

  • Use STATA software package for conducting multivariate regression analysis, interpreting results, and testing for violations of the assumptions of the classical linear regression model.
  • Examine published empirical work with statistical and econometric contents.
  • Apply skills acquired in the module in quantitative dissertation writing.

Employability skills

Analytical skills
Analyse data and interpret results for policy decision making.
Collect relevant empirical data and organise them using appropriate tools.
Develop skills that are relevant and needed in research institutes, financial institutions, Ministries, NGOs etc.

Assessment methods

Method Weight
Written exam 70%
Set exercise 30%

Feedback methods

Feedback on the assessments via Blackboard within SEED’s guidelines.

Study hours

Scheduled activity hours
Lectures 20
Practical classes & workshops 10
Tutorials 10
Independent study hours
Independent study 110

Teaching staff

Staff member Role
Lawrence Ado-Kofie Unit coordinator

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