Lara Ibarra, GabrielMcKenzie, DavidRuiz-Ortega, Claudia2023-12-202023-12-202019-12-14The World Bank Economic Review0258-6770 (print)1564-698X (online)https://openknowledge.worldbank.org/handle/10986/40781Low 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.en-USCC BY-NC-ND 3.0 IGOFINANCIAL LITERACYCREDIT-CARD BEHAVIORLOW TAKE-UPEstimating Treatment Effects with Big Data When Take-up is LowJournal ArticleWorld BankAn Application to Financial Education10.1596/40781