Research Resources

PDF version

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).

Featured

  • Resources on How to Obtain and Use Nonpublic Administrative Data

    J-PAL North America developed this pair of resources to support the use of nonpublic administrative data for randomized evaluations. The guide provides general tips on how to obtain and use these data. The catalog of key US data sets provides agency-specific information on how to request data.

  • J-PAL Costing Guidelines

    This document provides an outline on how to approach collecting cost information, what costs to include and exclude, and how detailed cost data should be.

  • Guide: Writing Randomization Code in Stata

    This step-by-step guide uses data and an annotated Stata do-file to illustrate how a simple randomization can be carried out using Stata.

  • IPA's Best Practices for Data and Code Management.

    IPA's data publication guideline covers the principles of organizing and documenting data and code – illustrated using examples from Stata – at all steps of the project lifecycle with the goal of making research reproducible.

  • 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.

Guide: Writing Randomization Code in Stata

This step-by-step guide uses data and an annotated Stata do-file to illustrate how a simple randomization can be carried out using Stata.

View Resource

Case Study: Developing a Theory of Change and Logical Framework (Log Frame).

Using the example of a J-PAL evaluation in India, this case study illustrates how to construct a log frame and use one's theory of change to pick appropriate outcomes and indicators for measurement.

View Resource

IPA's Best Practices for Data and Code Management.

IPA's data publication guideline covers the principles of organizing and documenting data and code – illustrated using examples from Stata – at all steps of the project lifecycle with the goal of making research reproducible.

Slides: How to Randomize

Learn about randomization methods in these slides from J-PAL's Executive Education Course.

View Resource

Stata 101

The Stata 101 Module is designed for users with little or no knowledge of Stata.

View Resource

PDF: Intro to Evaluations

A Randomized Evaluation is a type of Impact Evaluation that uses random assignment to allocate resources, run programs, or apply policies as part of the study design. This PDF contains all the information in the Introduction to Evaluations web page formatted into a single printable document.

View Resource

Slides: Threats and Analysis

Learn about threats to inference and ways to design field experiments to guard against them in these slides from J-PAL's Executive Education Course.

View Resource