MSc Development Finance / Course details

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

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

• 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.

• 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 data.

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

• 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.

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