The availability of digital payment technologies (such as internet banking, mobile money, and credit/debit cards) has rapidly increased in the developing world, and is a cornerstone for financial inclusion initiatives in developing countries. Despite significant efforts to promote digital payments, rates of adoption remain modest in some low-income countries. In particular, the rate of adoption in India remains low despite significant efforts to promote adoption. In this paper, we consider possible reasons for the low rates of adoption among merchants in Jaipur, India with small fixed-location store enterprises. Using survey data for 1,003 merchants, we find little evidence that supply-side barriers to obtaining necessary infrastructure or meeting prerequisite requirements to adopt digital payments explain the low level of adoption. Merchants are able to obtain infrastructure to transact digitally (such as bank accounts and smart phones), fees on digital platforms are affordable, and merchants are sufficiently literate to be able to use digital payment systems. We conclude that adoption is both feasible and inexpensive. Therefore, low rates of adoption do not appear to be the result of supply-side barriers, but due rather to demand-side factors or taxes. We find direct evidence of such demand-side factors, such as a perceived lack of customers wanting to pay digitally, and concerns that records of mobile payments might increase tax liability. Our results thus suggest that simply lowering the costs associated with adopting these technologies is unlikely to be successful in increasing adoption of digital payments.
We thank the editor Daniel Petrolia and an anonymous referee for helpful suggestions as well as participants of the 2020 AAEA meeting in the invited paper session titled BERCKnomics (Bonding over Environment, Resources, Coffee and Kindness). We thank CalRecycle for financial support via the California Department of Resources Recycling and Recovery (CalRecycle), Award No. DRR15053. This paper was finished after the passing of Peter Berck, the lead author of this paper. We thank the editor Daniel Petrolia and an anonymous referee for helpful suggestions as well as participants of the 2020 AAEA meeting in the invited paper session titled BERCKnomics (Bonding over Environment, Resources, Coffee and Kindness). We thank CalRecycle for financial support via the California Department of Resources Recycling and Recovery (CalRecycle), Award No. DRR15053. This paper was finished after the passing of Peter Berck, the lead author of this paper.
To solicit information from a social network in urban Monrovia, Liberia, we ask community members to assess their neighbors' poverty and assist in targeting a cash transfer. We find little evidence that local leaders, randomly selected neighbors, or neighbors nominated by fellow community members can accurately assess whether others in their community are among the poorest. Yet, all three groups target transfers to the poor modestly better than would be attributable to chance but worse than proxy-means-test-based targeting. We conclude that community advice provides some information for targeting but there are significant information frictions in networks in Monrovia.
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