Data and Development

Course Level: 
Master’s
Campus: 
Vienna
Course Open to: 
Students on-site
Academic Year: 
2020-2021
Term: 
Winter
US Credits: 
2
ECTS Credits: 
4
Course Code: 
SOPP5394
Course Description: 

Mandatory/Elective course for 1YMAPP and MPA 1Y students (Students have to complete 2 credits of either this course or
Economics of Higher Education (2); or Political Economy of Reforms (2); or Institutional and Behavioral Economics (2))

Development specialization

Relation to other courses:
This course is at the intermediate level and will require that the student has taken previous
courses in empirical methods, covering fundamental concepts such as Ordinary Least
Squares (OLS) and Maximum Likelihood Estimation (MLE) and an exposure to causal inference
methods such as Randomized Control Trials, Instrumental Variables (IV), and Differencein-
Difference estimation, which we will review and further build upon.


Background and Overall Aim of the Course:
The primary goal of this course is twofold (1) an introduction to persistent and emerging
issues in development (2) applied training in using data (experimental, observational, survey)
to analyze problems of development. The course will not go in depth in regard to any particular
econometric method, but will instead aim to provide you skills to know when, and when not,
to use it in your empirical research. We will focus on the role of individuals, households,
institutions, and policies briefly in theory and in detail by empirically engaging with (recent)
journal articles.

Learning Activities and Teaching Methods:
The class will mostly center around two activities: (1) close reading and discussion of seminal
and recent papers and (2) the analysis of real data to estimate causal relationships. Students
will be learning-by-doing analysis along with interactive lectures and classroom discussions.
Students can expect to spend 20 - 30% of class time on statistical software (STATA/R).
The assignments are designed to facilitate a deeper understanding of issues in development
by analyzing real data.

Learning Outcomes: 

At the end of the course, students should be able to


1. use economic concepts to critically evaluate development policies
2. make careful inferences from empirical papers in development for designing policy in
specific contexts
3. implement core empirical tools to analyze and synthesize development issues

Assessment: 

The course requirements are satisfactory completion of the assignments, short tests, quizzes,
class discussion notes and submission of the final paper. The problem sets will be provided a
letter grade.


Assignments: 30%
Class discussion and notes: 20%
Outline of final paper: 20%
Applied paper: 30%


One student will be chosen at random to lead the discussion on the required reading (in
bold) and a second to comment. Each student is required to submit at least 6 discussion notes
(approx. half a page, but no more than one page; bullet points will suffice) and can pass the
opportunity to lead the discussion or comment on two occasions.