With DBTs credited directly to the bank accounts, there is no incremental cost of availing these benefits. Thus, more households will now receive and avail of DBTs than those who deserve them.
The tremendous success of digital payments in India is a case of demand and supply reinforcing each other. The demand was largely government-induced, based on twin goals: financial inclusion and last-mile delivery. First, India linked Jan Dhan accounts, mobile numbers and Aadhaar cards to open accounts for the financially excluded. Then, direct benefit transfers (DBTs) were made in the beneficiary accounts that plugged most leakages (around Rs 2 lakh crores) between 2014 and 2022. It is argued that DBTs can successfully replace some existing programmes. However, there is little clarity regarding how to "target" intended beneficiaries effectively.
Any disbursement will have Type 1 and Type 2 errors (i.e., many disbursements may not reach the intended beneficiaries and might reach some who are not the intended beneficiaries) because we lack any authentic methodology to identify and target such families precisely. One way to solve this targeting problem is by imposing a small cost to anyone who wishes to avail of such benefits. For example, the fact that one must stand in a queue to receive subsidised grains from PDS (Public Distribution System) shops may be costly enough to dissuade many families who can afford food grains from the market at nonsubsidised rates. However, what happens when DBTs substitute PDS? With DBTs credited directly to the bank accounts, there is no incremental cost of availing these benefits. Thus, more households will now receive and avail of DBTs than those who deserve them. One way to stop this is opting out. How does one opt out of receiving DBTs? There are two ways. One involves voluntarily giving up subsidies by opting out of such schemes, and two, by declining to receive DBTs as and when they are made.
The Give Up LPG was one such opt-out scheme. The campaign was launched in March 2015 by the GoI to motivate LPG users who can afford to pay the market price to surrender their subsidy voluntarily. The number grew to 11.3 million as of April 2023. However, given that the number of income taxpayers now exceeds 22.4 million, many individuals can still give up the LPG subsidy. The fact that half of all individuals who could have given up the subsidy did so is a remarkable feat, while equally interesting are the possible reasons why the other half did not.
Many possible hypotheses are there. Many may be typical self-maximising neoclassical agents. The subsidy is vital for many despite being in a higher income bracket. Some fear the exclusion ("I can give up the subsidy today, but if I need it tomorrow, will I get it?"). Indeed, experience with government machinery in the past may prompt individuals to think that way. However, the most interesting cases will be those where there are administrative or transaction costs of giving up subsidies. Such costs often act as a barrier for many to give up such subsidies. The cost of opting out also entails "remembering to opt-out"—a significant cost for many. Consider an individual who no longer needs the DBT. If there are forms to be filled out to opt out of the process, individuals may be far less willing to give up these subsidies than to stay opted in. Therefore, to encourage individuals to opt out of subsidies, we must make the relative cost of opting in for subsidies higher than opting out for individuals who do not need the subsidy. However, at the same time, we should make the relative cost of opting in for subsidies much lower than opting out for individuals who need the subsidy. We propose a simple solution based on the crucial role played by the default option and an opt-in versus opt-out approach. We propose that the default setting for all government payments should be "opted in".
Any payments made by the government into accounts are automatically credited without any approval/authentication by the recipients. However, we propose a two-stage process. In the first stage, while the default option is opted in, should any account holder no longer wish to receive these DBTs, they can opt for a service requiring them to approve such payments every time they are credited. In the second stage, when a DBT is made to the account, the payment is credited to the account if they approve the payment within a stipulated time (say 48 hours). After the stipulated time, the payment goes back to the government. The approval can be based on OTP. Individuals must have the option to choose this process rather than opting out of the DBT scheme entirely. By not opting out of the DBT process, individuals no longer have to fear that the cost of joining in the future will be high. For example, a household that temporarily feels financially secure may opt for this service whereby they can refuse to accept the DBT payment and even other government transfers until they think they don't need them. They simply must ignore the receipts every time they are due. However, there is also a safety net for them in the event of future shocks, and they need the payments again. In that case, they will approve the transactions. Because of the safety net, we expect more individuals to give up such subsidies in the short run.
Apart from the payment systems and fintech innovations, India can be a pioneer in trying to establish a simple OTP-based process to authenticate the transaction by the receiver. This service must be optional; not opting for it would mean the status quo. The option to accept inward remittances and payments should be extended to DBTs and private-party transactions. Failure to accept a payment within a stipulated time would automatically mean the payment is credited to the sender. This will help the government save precious resources as more and more individuals can safely give up subsidies, not fearing that they will be excluded should they need the subsidies in the future.
This piece has been co-authored by Bappaditya Mukhopadhyay, Professor, Data Analytics and Economics and Jayatu Sen Chaudhury, Professor, Data Analytics and Finance, Great Lakes Institute of Management Gurgaon.