Research Resources

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Research Resources

Our library of practical resources is available for researchers undertaking randomized evaluations and those teaching the technique to others. The resources presented here are curated by J-PAL in partnership with Innovations for Poverty Action (IPA).

The Danger of Underpowered Evaluations

A one-page document that highlights the risks associated with running an evaluation that is not designed to detect a meaningful impact of a program.

Impact Evaluation Methods

A table that describes and compares different evaluation methodologies and indicates when each one is valid.

Real-World Challenges to Randomization and Their Solutions

A guide to help researchers and implementing partners develop evaluation designs that fit their program’s context. Using real examples from ongoing and completed randomized evaluations, the document describes multiple research designs that accommodate existing programs, mitigate foreseeable implementation challenges, and demonstrate the flexibility of randomized evaluations across contexts.

Why Randomize

A one-page document that summarizes the rationale behind why randomized evaluations are a powerful way to credibly evaluate the impact of a policy or program.

Household Poverty Measurement

The PPI is a leading household poverty measurement tool, used by more than 500 organizations around the world, to measure household poverty, improve targeting and social performance, and track changes in welfare. It is a country-specific ten-question scorecard that estimates whether a particular household is living below the poverty line. The PPI provides a consumption-based measure of poverty relative to widely-recognized poverty lines – both national and international.  Scaled by Grameen Foundation over a ten year period, the PPI is currently housed at IPA (since July 2016). The scorecards, documentation and user guides are available for free download.

Power calculations in Stata

Power calculations in Stata: A Guide. This step-by step guide uses data and an annotated Stata do-file to illustrate how power calculations can be carried out using Stata. It provides an example of both a conventional parametric and a non-parametric simulation method of calculating power.

Exercise B: Randomization Mechanics