Dr Diana Weinhold CON 7.10

This course is available on the MRes/PhD in International Development. This course is not available as an outside option.

Enrolment will be controlled through the use of a pre-quiz (see DV490 Moodle page for details).

This course explores the foundations of applied macroeconomic policy analysis by combining a rigorous but intuitive introduction to advanced econometric methods with applications to the theory and empirics of long-run growth in developing countries. Throughout the course, lectures provide analytical but non-technical overviews of broad themes in long-run growth and development policy, including growth theory, institutions and history, economic geography, globalization, inequality, balance of payments and financial crises, debt, environmental policy and international aid. There is a strong emphasis on how the body of knowledge has evolved over time via the synthesis of theoretical advances and rigorous empirical testing.

Seminars in the first half of term will introduce students to the statistical foundations of econometric analysis and build analytical skills to read, interpret, and critique econometric approaches to causal identification commonly used in the academic development literature. We engage directly with quantitative methodology and regression analysis, developing rigorous intuition rather than learning technical formulas, with the focus on teaching students from a broad range of backgrounds to understand and critically consume high-level applied research in a sophisticated manner.  The seminars in the second half of term give students an opportunity to repeatedly practice and improve their analytical skills by working through methodologically-focussed problem sets based on top academic journal articles addressing issues from the lectures on macroeconomic development.

While some background in economics and/or statistics is helpful, the course is designed to be engaging and challenging for students from a broad variety of backgrounds, from those with no economics and statistics to those with more advanced skills in either one or both areas.  Strong analytical skills (whether quantitative or not) and a sturdy work ethic are the best predictors of success.

20 hours of lectures and 15 hours of seminars in the AT.

This course is delivered through a combination of lectures and seminars in the MT.

Student on this course will have a reading week in Week 6.

Students will be expected to produce 1 piece of coursework in the WT.

A plan for the research paper (1500-2000 words) on which the student will receive feedback and topic approval

The bulk of the course will be taught using journal articles. A reading list will be handed out by the lecturers at the beginning of their sessions. Useful reference texts include Mastering ‘Metrics:the Path from Cause to Effect, by Angrist & Pischke, Princeton University Press (2014); and The Quest for Growth by W. Easterly, MIT Press (2001)

Essay (100%, 5000 words) in the ST.