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...
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...
Chakravorti and Emmons model side payments in a competitive credit‐card market. If competitive retailers absorb the cost of accepting credit cards by charging a higher goods price to everyone, then someone must subsidize convenience users of credit cards to prevent them from defecting to merchants who do not accept cards...
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...