MSc Development Finance

The course unit aims to equip students with knowledge of and experience with conducting empirical research in which they apply data analysis to a research topic related to their programme(s). It also helps prepare students for their dissertations.

After completing the module, students are expected to develop an understanding of the steps and issues in conducting an applied quantitative research examining causal relationships, and have a hand-on experience with undertaking an empirical research using real-world data on a topic related to economic development. Students will develop familiarity with the most common forms of identification problems in empirical research and with the main econometric methods to address them (e.g., basic panel data methods and instrumental variables estimation), providing students with an understanding of the advantages and challenges posed by each method. By the end of the course, students should have acquired sufficient knowledge to apply cross-section data and panel data analysis to a range of macro- and micro-economic problems in development research and obtained a basic understanding of conducting quantitative research for their dissertation.

Lecture 1: Assumptions and properties of OLS estimation.

Lecture 2: Internal and external validity of a statistical study. Identification problems. Lecture 3: Natural experiments and IV estimation.

Lecture 4: Panel methods and identification.

Lecture 5: Natural experiments and panel methods.

Lecture 6: Applied quantitative research: research question(s) and research hypothesis Lecture

7: model specification

Lecture 8, 9 and 10: issues in the execution of data analysis

The course will be taught via a mix of lectures, computer lab sessions and independent learning.

• develop an understanding of the steps and issues in conducting an applied quantitative research examining causal relationships, and have a hand-on experience with undertaking an empirical research using real-world data on a topic related to economic development.
• obtain a basic understanding of conducting quantitative research for their dissertation

• demonstrate they have developed the ability to identify an empirical research question based on the existing literature.
• demonstrate they have developed the ability to design an empirical strategy which is appropriate to address the research question(s).
• show they have acquired familiarity with regression analysis (identification, execution and interpretation).

• demonstrate they have acquired skills to use econometric software.
• demonstrate they have acquired skills to write up a research report for an empirical project.

Written feedback on the research project report through Turnitin.

There are no textbooks that cover all aspects of the module, and specific readings may be given at each lecture. However, students may find the following books useful.

.• Wooldridge, Introductory Econometrics: A Modern Approach, 6th Edition, 2016, South-Western – Cengage Learning. Standard reading for intermediate econometrics courses, good background for advanced ones.

• J.H. Stock and M.W. Watson, Introduction to Econometrics, 3nd ed. 2014, Pearson-Addison Wesley. Very readable, more than Wooldridge; overall, it is as advanced as Wooldridge.

• Måns Söderbom, Francis Teal, Markus Eberhardt, Simon Quinn, Andrew Zeitlin (2014), Empirical Development Economics, Routledge. A good guide on conducting econometric analysis on topics in development economics.

• Mukherjee, C., While, H. and Wuyts, M. (1998) Econometrics and Data Analysis for Developing Countries, Routledge, London and New York. This book is old but it contains some examples of econometric analysis using data of developing countries and the issues to be considered when doing applied quantitative research.

For students who struggle with econometric METHODS and STATA commands, it is advisable to refer to the reading list and other learning materials given for lectures and lab sessions in MGDI60301 RSED I.