Designing and Running Randomized Evaluations

This course equips students with the practical skills for running evaluations in the field. Students will learn the foundations of randomizations and research design, as well as practical tips and skills for collecting high quality, reliable data in the field.

start date
February 1, 2022
length
Estimated 12 Weeks
effort
12–14 hours per week

About this course

This course is part of the MITx MicroMasters program in Data, Economics, and Development Policy (DEDP), which provides a path towards MIT’s Master’s in DEDP. To enroll in the courses, remain on this site and click the “enroll now” button. If you want to earn a certificate for the courses or start your path towards a MicroMasters program credential, please visit the MicroMasters portal after you enroll.

A randomized evaluation, also known as a field experiment or randomized controlled trial (RCT), is an impact evaluation that uses random assignment to minimize bias, and strengthen our ability to draw causal inferences.

This course will provide step-by-step training on how to design and conduct an RCT. You will learn how to build a well-designed, policy relevant study, including why and when to conduct RCTs.

Additionally, this course will provide insights on how to implement your RCT in the field, including questionnaire design, piloting, quality control, data collection and management. The course will also introduce common research transparency practices.

No previous economics or statistics background is needed.

Course Previews:

Our course previews are meant to give prospective learners the opportunity to get a taste of the content and exercises that will be covered in each course. If you are new to these subjects, or eager to refresh your memory, each course preview also includes some available resources. These resources may also be useful to refer to over the course of the semester.

A score of 60% or above in the course previews indicates that you are ready to take the course, while a score below 60% indicates that you should further review the concepts covered before beginning the course.

Please use this link to access the course preview.

What you’ll learn

  • Designing a Randomized Evaluation
  • Selecting a sample
  • Measurement of outcomes
  • Collecting and managing your data
  • Research Integrity, Transparency, and Reproducibility

Prerequisites

Although not required, prior familiarity with basic statistical concepts is recommended.

Meet your instructors

  • Esther Duflo

    Esther Duflo is the winner of the 2019 Nobel Prize in Economic Sciences. She is also the Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics in the Department of Economics at MIT. She was educated at the Ecole Normale Supérieure, in Paris, and at MIT. She has received numerous honors and prizes including a John Bates Clark Medal for the best American economist under 40 in 2010, a MacArthur “Genius” Fellowship in 2009. She was recognized as one of the best eight young economists by The Economist magazine, one of the 100 most influential thinkers by Foreign Policy since the list exists, and one of the “Forty under 40” most influential business leaders under forty by Fortune magazine in 2010.

    To learn more, please click here.

  • Rachel Glennerster

    Rachel Glennerster is on leave as J-PAL Executive Director. Currently Chief Economist of the UK Department for International Development.