DIME Analytics

DIME Analytics creates tools that improve the quality of impact evaluation research for all. We take advantage of the concentration and scale of research at DIME to develop and test solutions to ensure the credibility and quality, and to make public training and tools available to the larger community of development researchers who might not have the same capabilities. The team offers a variety of services for high-quality, reproducible research to all World Bank staff. All of our tools and resources are open-source and open-access, and our virtual courses are open to the global community of development researchers.

Research Tools

We take advantage of the scope and scale of DIME research to develop and test econometric and technical solutions and develop public tools. 

  • DIME Wiki
    One-stop shop for impact evaluation research solutions. The DIME Wiki is a resource focused on practical implementation guidelines. It is open to the public, easily searchable, and suitable for users of varying levels of expertise.
  • Development Research in Practice: the DIME Analytics Data Handbook
    Development Research in Practice leads the reader through a complete empirical research project, providing links to continuously updated resources on the DIME Wiki as well as illustrative examples from the Demand for Safe Spaces study. The handbook is intended to train users of development data how to handle data effectively, efficiently, and ethically.
  • Stata Tools:
  • Data Visualization Libraries:


  • Manage Successful Field Research
    This week-long course covers all aspects of implementing development research in the field. Researchers and implementing partners learn best practices for field research, critical issues in research implementation, recurring challenges, and cutting-edge technologies.
    2023 Course Materials | 2022 Course Materials | 2021 Course Materials | 2020 Course Materials
  • Reproducible Research Fundamentals Course
    This week-long course teaches best practices for reproducible analytics, from data processing to publication. Participants learn to implement transparent and reproducible workflows, to effectively code in a team environment, and to keep personal data secure throughout the lifecycle of an analytical product.
    2023 Course Materials | 2022 Course Materials | 2021 Course Materials
  • Development Research in Practice Course
    This course is based on Development Research in Practice: the DIME Analytics Data Handbook. It teaches all users of development data how to handle data effectively, efficiently, and ethically. The course covers the data workflow at each stage of an empirical research project, from design to analysis to publication.
    Course Content
  • DIME Continuing Education Series
    DIME Analytics offers regular trainings on technical topics for World Bank Staff. Recent topics include: Data Processing in Python Using Pandas, Introduction to APIs, Writing reusable code in Stata using programs and adofiles, Spatial Data in Stata, Optimizing Survey Length, GitHub Pull Requests, and Introduction to Python for Stata users. All Continuing Education materials are publicly available.
  • R for Advanced Stata Users
    This course teaches the R programming language and software environment, focusing on common tasks and analysis in development research. 
  • Foundations of Python for Data Science
    This course lays the foundations for conducting data science in Python, covering its basic syntax, data types, and control flow; and building upon them to introduce essential libraries for data processing and exploration.


  • Reproducible Research Repository
    The Reproducible Research Repository is a one-stop shop for reproducibility packages associated with research authored by World Bank staff and consultants. To enhance the credibility, transparency, and impact of World Bank research, this platform publishes reproducibility packages that fully document the data and code on which research findings are based.
  • Computational Reproducibility Assessment  (code review)
    DIME Analytics conducts computational reproducibility verification for World Bank research. The checks verify that a third-party, using the same materials and procedures used by the research team, can exactly reproduce the tables and figures in the research paper. Verified packages are published to the Reproducible Research Repository. 
  • Measuring Development Conference
    DIME Analytics organizes an annual conference on innovations in data and measurement in partnership with the World Bank’s Development Data Group, the Center for Effective Global Action (CEGA) at UC Berkeley, and the Development Innovation Lab at the University of Chicago. 
    2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018