Mobile banking and related digital financial technologies can make financial services cheaper and more widely accessible in low-income economies, but gender gaps persist. We present evidence from two connected field experiments in Bangladesh designed to encourage the adoption and use of mobile banking by poor, illiterate households. We show that training can dramatically increase adoption and usage by women. At the same time, women on average persist in using mobile banking at a lower rate than men. The study focuses on migrants and their families in Bangladesh. Despite large differences between female and male migrants in income and education, the first experiment shows that a training program led to a similarly large, positive impact on mobile banking usage by female and male migrants, increasing usage rates for both by about 45 percentage points. That led to increases in remittances sent to rural areas, reduced rural poverty, and increased rural consumption. Both female and male migrants in the treatment group, however, reported worse physical and emotional health, adding to health challenges reported by women across treatment and control groups. A second experiment explores whether the way that the technology was introduced and explained made an additional difference in narrowing gender gaps. Despite the lack of statistical power to detect small treatment impacts, we find suggestive evidence that the treatment increased mobile banking adoption by female migrants.
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Do Interest Rates Matter? Credit Demand in the Dhaka Slums
"Best practice" in microfinance holds that interest rates should be set at profit-making levels, based on the belief that even poor customers favor access to finance over low fees. Despite this core belief, little direct evidence exists on the price elasticity of credit demand in poor communities. We examine increases in the interest rate on microfinance loans in the slums of Dhaka, Bangladesh. Using unanticipated between-branch variation in prices, we estimate interest elasticities from -0.73 to -1.04, with our preferred estimate being at the upper end of this range. Interest income earned from most borrowers fell, but interest income earned from the largest customers increased, generating overall profitability at the branch level.