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...
Carbó, Chakravorti, and Rodriguez study the impact of lowering interchange fees on consumer and merchant adoption and usage along with bank revenues during a ten-year period in Spain using bank-level data. Using cutting-edge econometric techniques, they are able to test two-sided market model predictions about payment card pricing policies. They...
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...
Chakravorti and Roson construct a model to study competing payment networks, where networks offer differentiated products in terms of benefits to consumers and merchants. We study market equilibria for a variety of market structures: duopolistic competition and cartel, symmetric and asymmetric networks, and alternative assumptions about consumer preferences. We find...