Using random forest estimation, we identify 14 key predictors out of 190 variables with the largest predictive power for MSMR adoption and usage of digital payments. Using conditional inference trees, we study the importance of sequencing and interactions of various factors such as public sector initiatives, technological advancements, and private...

The provision of retail payment services is complex with many participants engaging in a series of interrelated bilateral transactions and subject to large economies of scale and scope along with strong adoption, usage and network externalities. This makes sound public policy difficult. We focus on three types of market interventions...

Using a unique administrative level dataset from a large and diverse U.S. financial institution, Agarwal, Chakravorti, and Lunn test the impact of rewards on credit card spending and debt. Specifically, we study the impact of cash-back rewards on individuals before and during their enrollment in the program. We find that...

Bolt and Chakravorti study the ability of banks and merchants to influence the consumer's payment instrument choice. Consumers participate in payment card networks to insure themselves against three types of shocks - income, theft, and their merchant match. Merchants choose which payment instruments to accept based on their production costs...