Estimating Treatment Effects with Big Data When Take-up is Low: An Application to Financial Education. (14th December 2019)

• Record Type: Journal Article
• Authors: Lara Ibarra, Gabriel; McKenzie, David; Ruiz-Ortega, Claudia
• Is Part Of: World Bank economic review. Volume 35:Number 2(2021)
• Page Start: 348
• Page End: 375
• Publication Date: 2019-12-14
• Subjects: financial literacy -- credit-card behavior -- low take-up; Economic development -- Periodicals; Developing countries -- Economic conditions -- Periodicals; Developing countries -- Economic policy -- Periodicals; 330.91724
• DOI: 10.1093/wber/lhz045
• Languages: English
• ISSNs: 0258-6770

Abstract

Abstract: Low take-up of interventions is a common problem faced by evaluations of development programs. A leading case is financial education programs, which are increasingly offered by governments, nonprofits, and financial institutions, but which often have very low voluntary participation rates. This poses a severe challenge for randomized experiments attempting to measure their impact. This study uses a large experiment on more than 100, 000 credit card clients in Mexico. The study shows how the richness of financial data allows combining matching and difference-in-difference methods with the experiment to yield credible measures of impact, even with take-up rates below 1 percent. The findings show that a financial education workshop and personalized coaching result in a higher likelihood of paying credit cards on time, and of making more than the minimum payment, but do not reduce spending, resulting in higher profitability for the bank.