This course is based on "Development Research in Practice: the DIME Analytics Data Handbook" and it teaches how to handle large datasets effectively, efficiently, and ethically, as well as each stage of the data workflow in an empirical research project: from design, to analysis, to publication.

• Structure data work for effective team collaboration

• Acquire high-quality data reproducibly and ensure data subject privacy 

• Process data efficiently, from constructing “tidy” datasets, to checking data quality, and cleaning data in preparation for analytical tasks 

• Analyze data effectively, from creating analytical datasets and derived indicators to writing analytical code for generating reproducible research outputs 

• Data publication, preparation of dynamic documents using data outputs, and compiling research outputs and reproducibility packages 

Link to the course: Development Research in Practice (worldbank.org) 

Course content:

• How to effectively manage, clean and tidy raw datasets.

• Best practices for coding, indicator construction and data analysis.

• How to keep record of your data analysis in a team environment. 

• How to create reproducible research outputs.

Link to the course: 

Reproducible Research Fundamentals (worldbank.org) 

This course presents recent developments in the microeconomic analysis of impact evaluation, with courses taught by experts in their fields. The course “Methods of policy evaluation” introduces the main methods currently used for program evaluation, while the course “Machine learning for policy evaluation” presents recent advances in machine learning techniques for policy analysis. 

Course content:

1. Introduction: setting and real world experiments

2. Comparing similar individuals
a. Regression models
b. Matching models
c. Regression discontinuity

3. Simulating unobserved outcomes
a. Instrumental variables
b. Selection models

4. Intertemporal comparisons
a. Before-After
b. Difference-in-Differences and extensions
c. Synthetic controls

5. Summarizing methods

Link to the course: MICROECONOMETRICS AND POLICY EVALUATION - Modern Estimation Methods and Machine Learning - Paris School of Economics 

The program aims at providing an overview of the challenges that researchers face when they do field work in the Global South. These challenges range from methodological questions about research design to ethical considerations. While these issues are central to the research carried out by development economists, they are rarely covered in traditional courses. Our program builds on the wide-ranging experience of PSE researchers doing field work. We will present practical and methodological tools that researchers can use to overcome those challenges. 

Course content: 

• Survey questionnaire design (Sylvie Lambert, 4.5 hours)

• Designing and implementing experiments (Karen Macours, 4.5 hours)

• Designing and implementing lab in the field experiments (Suanna Oh, 4.5 hours)

• Measurement issues (Karen Macours and Denis Cogneau, 4.5 hours)

• Collecting and using administrative data (Oliver Vanden Eynde, 3 hours)

• Ethics (Sylvie Lambert, 3 hours)

• Conducting evaluation in a development bank (Pierre Bachas, World Bank, 1.5 hours)

Link to the course: DEVELOPMENT ECONOMICS IN THE FIELD - Surveys, Measurement, and Experiments - Paris School of Economics 

This course is designed the skills and knowledge of field research practitioners, familiarizing them with best practices, critical issues in research implementation, recurring challenges, and cutting-edge technologies. Through the course, participants will gain practical skills to prepare and ensure high-quality fieldwork research, and communication with a strong emphasis on data privacy and research ethics.  

Course content:
Plan and supervise field research and acquire high-quality data
Design and program electronic survey instruments
Develop a data quality assurance strategy
Monitor implementation to ensure fidelity to research design
Assess research data quality and provide real-time feedback
Integrate monitoring and evaluation systems with research data

Link to the course: Manage Successful Field Research 2023 (worldbank.org)  

The Program for Advanced Studies on Latin American Economies is an opportunity to discuss development issues in-depth while respecting the pluralism inherent to development studies. During the Program, theoretical and empirical issues are addressed, emphasizing the experience of the countries of Latin America and the Caribbean.

The Program is aimed at young researchers from around the world. Classes are taught by the School team and ECLAC staff, and also by prominent external teachers invited each year. The course is structured in four modules: economic history and political economy, structuralist macroeconomics, evolutionary microeconomics, and development. 

Link to the course: ECLAC School of Latin American Development Studies | CEPAL 

The main goal of this course is to learn techniques for presenting data visually using the open source language R.  

Course content:

Bar Charts, histograms, pie charts, scatterplots, line plots, regressions, word clouds, radar charts, waffle charts, box plots and maps. 

Link to the course: 

Data Visualization with R course | Cognitive Class