Replication of ‘Remedying Education’

Replication Researcher: Stephen Gorard (with Patrick White)
Original Paper Title: Remedying Education: Evidence from Two Randomized Experiments in India
Original Researchers: Abhijit Banerjee, Shawn Cole, Esther Duflo, and Leigh Linden
Original Publication: Quarterly Journal of Economics
Replication Plan: Not Applicable
Current Status: Grant Cancelled

The Original Study

Education policies in developing countries have focused on increasing school enrolment but have paid less attention to quality. This study evaluates whether supplementary school inputs improve school outcomes in Gujarat, India. In the first intervention, the weakest children worked with young women (balsakhi) for tutoring. In the second program in Vadodara, children played computer games solving math problems 2 hours per week. Change in students’ test scores was regressed on treatment status and pretest score to measure the impact of the intervention. To determine if the impact of the remedial education was direct (that is, due to working with balsakhi) or indirect (that is, due to a reduction in class size), an instrumental variable (IV) regression was run in which predicted probability of being assigned to balsakhi was used as an instrument for actual assignment.

The Replication

Banerjee et al. (2007) "Remedying education: evidence from two randomized experiments in India" is an important study because it addresses an issue of concern to all governments - identifying the potential for literacy and numeracy ‘catch-up’ among young students living in disadvantage or otherwise under threat of not reaching expected levels of attainment. It is crucial that the stated ‘effect’ sizes in Banerjee et al. (2007) are accurate because it is these that will form the basis for calculations of cost-effectiveness (or dollar cost per long-term unit of improvement). The replication study will calculate differences between treatment and control groups at school level (using both change between pre- and post-test scores, and post-test scores only, as dependent variables), and associated p-values. This analysis will also investigate the impact of any drop-out from the intervention by estimating how different drop-outs would have had to be from others in their allocated groups for the difference in groups to be zero. A variety of sensitivity tests will determine to what extent developing countries might wish to use their resources for either intervention, and at what grade and learning level each intervention is most cost-effective.

Photo © Ray Witlin / World Bank

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