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Introduction
Randomization is now an integral part of a development economist’s toolbox. Over the last ten
years, a growing number of randomized evaluations have been conducted by economists or with
their input. These evaluations, on topics as diverse as the effect of school inputs on learning
(Glewwe and Kremer 2005), the adoption of new technologies in agriculture (Duflo, Kremer, and
Robinson 2006), corruption in driving licenses administration (Bertrand, Djankov, Hanna, and
Mullainathan 2006), or moral hazard and adverse selection in consumer credit markets (Karlan
and Zinman 2005b), have attempted to answer important policy questions and have also been
used by economists as a testing ground for their theories.
Unlike the early “social experiments” conducted in the United States—with their large bud-
gets, large teams, and complex implementations—many of the randomized evaluations that have
been conducted in recent years in developing countries have had fairly small budgets, making
them affordable for development economists. Working with local partners on a smaller scale has
also given more flexibility to researchers, who can often influence program design. As a result,
randomized evaluation has become a powerful research tool.
While research involving randomization still represents a small proportion of work in de-
velopment economics, there is now a considerable body of theoretical knowledge and practical
experience on how to run these projects. In this chapter, we attempt to draw together in one
place the main lessons of this experience and provide a reference for researchers planning to con-
duct such projects. The chapter thus provides practical guidance on how to conduct, analyze,
and interpret randomized evaluations in developing countries and on how to use such evaluations
to answer questions about economic behavior.
This chapter is not a review of research using randomization in development economics.
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Nor is its main purpose to justify the use of randomization as a complement or substitute to
other research methods, although we touch upon these issues along the way.
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Rather, it is
a practical guide, a “toolkit,” which we hope will be useful to those interested in including
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Kremer
(2003) and Glewwe and Kremer (2005) provide a review of randomized evaluations in education;
Banerjee and Duflo (2005) review the results from randomized evaluations on ways to improve teacher’s and
nurse’s attendance in developing countries; Duflo (2006) reviews the lessons on incentives, social learning, and
hyperb olic discounting.
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We have provided such arguments elsewhere, see Duflo (2004) and Duflo and Kremer (2005).
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