Issues with JAM (JanDhan-Aadhaar Mobile) and BAPU model

JAM refers to Jan Dhan, Aadhaar and Mobile. There are three ingredients that help policymakers to decide where next to spread JAM. They are:

• The first-mile is identification of beneficiaries.
• The middle-mile is transfer of money to beneficiaries.
• The last-mile is beneficiaries must be able to access their money from banking channel.

Failure in first-mile leads to inclusion errors and leakages as benefits intended for poor reaches to rich and “ghost” households. Failures in middle and last-miles lead to exclusion errors i.e. genuine beneficiaries being unable to avail benefits.

What are the first-mile challenges?

To identify beneficiaries, the government needs databases of eligible individuals. Beneficiary databases have existed for long before Aadhaar, but their accuracy and legitimacy have been hampered by the administrative and political discretion. Ghost and duplicate names crept into beneficiary lists, leading to leakage.

Aadhaar by using technology replaced human discretion, while keeping the system simple enough – fingerprints and iris scans – for citizens to understand. Over 75 percent of the population and nearly 95 per cent of the adult population now holds Aadhaar card. Nearly one-third of all states have coverage rates greater than 90 percent; and only in 4 states—Nagaland (48.9), Mizoram (38.0), Meghalaya (2.9) and Assam (2.4)—is penetration less than 50 per cent.

What are the middle-mile challenges?

For transfer of money, each beneficiary needs a bank account and the government needs their account numbers. This is being achieved through Jan Dhan Yojana. Nearly 120 million accounts were created in the last year alone under the Jan Dhan Yojana. But the basic savings account penetration in most states is still relatively low – 46 per cent on average and above 75 per cent in only 2 states (Madhya Pradesh and Chattisgarh). Comparing the reach of Jan Dhan with that of Aadhaar suggests that the unbanked are more likely to constrain the spread of JAM than the unidentified.

What are the last-mile challenges?

In urban areas, people live near banks, even though financial literacy remains a concern. In rural areas, however, there is a “last-mile” problem of getting money from banks into household’s hands. Only 27 per cent of villages have a bank within 5 km. To help address this problem, the RBI in 2015 licensed 23 new banks – 2 universal banks, 11 payment banks and 10 small finance banks.

In India, there is high mobile penetration. Only in Bihar (54%) and Assam (56%) is penetration lower than 60 per cent. India should take advantage of its deep mobile penetration and agent networks by making greater use of mobile payments technology. Mobiles can not only transfer money quickly and securely, but also improve the quality and convenience of service delivery. For example, they can inform beneficiaries that food supplies have arrived at the ration shop or fertiliser at the local retail outlet.

What are the varieties in JAM?

Over 20 per cent of India’s population received a cash transfer from the government in FY14-15. JAM was involved in distributing benefits across a range of government programs—from education and labour schemes (scholarships and MGNREGS) to subsidies and pensions (NSAP).

JAM and Direct Benefit Transfer of LPG (DBTL) or PAHAL

The union government launched the Pahal scheme in late 2014 and early 2015. Currently over 151 million beneficiaries receive LPG subsidies via DBT, and R29,000 crore have been transferred to beneficiaries to date.

Before the DBT scheme was introduced, households could buy LPG cylinders at subsidised prices (~Rs 430). Commercial establishments are ineligible for the subsidy and must pay market prices plus central and state taxes of about 30 per cent on average. This violation of the One Product One Price principle provides strong incentives for distributors to create ‘ghost’ household accounts and sell subsidised LPG to businesses in the black market. Now, with DBT in place, the government identifies beneficiaries by linking households’ LPG customer numbers with Aadhaar numbers to eliminate ‘ghost’ and duplicate households from beneficiary roll. After introduction of Pahal scheme, there is a 27 per cent reduction in sale of subsidised cylinders. It is estimated that the potential annual fiscal savings of Pahal will be Rs.12,700 crore in a subsequent FY.  However, it is important to check that the success of Pahal scheme is not due to exclusion errors i.e. lower consumption by genuine beneficiaries who do not have bank accounts and therefore cannot access the subsidy under the JAM arrangement. Data suggested that JAM in LPG has succeeded in reducing leakages rather than excluding the poor.

What are the lessons from the LPG experience?

After the introduction of DBT in LPG, commercial establishments are force to buy commercial cylinders. Data shows that commercial LPG sales increased when DBT was introduced and fell back when DBT was suspended. But the effect is surprisingly small (6 per cent). Why? Sales of non-subsidised domestic cylinders shot up. While households can buy only 12 subsidised cylinders a year, they can buy an unlimited number of unsubsidised cylinders. However these cylinders are still 30 per cent cheaper than commercial cylinders due to differential tax treatment of household and commercial LPG. Commercial LPG is subject to customs and excise duties of 13 per cent and state taxes of between 5 per cent (Assam) and 20.5 per cent (Bihar) over-and-above domestic LPG.This is a violation of the One Product One Price principle and creates another source of leakage – a shortfall of tax revenue in this case rather than excess subsidy burden. Diversion could be further reduced by equalising taxes across end-uses.

Another reform that could further reduce LPG leakages with limited genuine exclusion is lowering the household cap from 12 to 10. Data shows that even the richest households – the top 10 per cent – typically do not consume more than 10 cylinders per year, so reducing the household cap will be unlikely to hurt the poor.

Where next to spread JAM?

The policymakers should decide where next to JAM based on two considerations:

Size of leakages

JAM significantly reduced leakages in LPG and MGNREGS with limited exclusion of the poor. The returns from pursuing JAM in other areas depend on the size of leakages in those sectors. Subsidies with higher leakages have larger returns from introducing JAM.

Central government control

When introducing JAM, policymakers will confront administrative challenges in coordinating central and state government departments, and political challenges in bringing the supply chain interest groups like Fair Price Shops on board with DBT.

Based on the above considerations, the two sectors which are conducive to JAM are:

• Fertiliser sector which is facing huge leakages.
• Within-government fund transfers where Central government has complete control.

What is BAPU (Biometrically Authenticated Physical Uptake) model?

Under BAPU model, beneficiaries certify their identity through scanning their thumbprint on a POS machine while buying the subsidised product – say kerosene at the PDS shop. This reduces leakages considerably.

Presently, the JAM agenda is facing the last-mile challenge of getting money from banks into beneficiaries’ hands, especially in rural India. Until Business Correspondent (BC) network is developed and mobile banking spreads, the BAPU model can be used to reduce leakages without the risk of exclusion errors. The shift to BAPU will not be easy. Fair price shop owners stand to lose out from the reduced avenues for diversion and strongly resist this system. State governments have to provide adequate incentives which allow shop owners to make up for the loss in revenue from diversion.

What is JAM preparedness index?

The JAM preparedness index uses the indicators such as Aadhaar penetration, basic bank account penetration, and BC density. The JAM preparedness index is constructed to measure state’s preparedness to implement (i) DBT in urban areas, (ii) DBT in rural areas, and (iii) BAPU.

In case of Urban DBT index, there is a significant variation across states. Some, like Madhya Pradesh and Chhattisgarh, show preparedness scores of about 70 per cent. Others, like Bihar and Maharashtra, have scores of only about 25 per cent. The binding constraint here is basic bank account penetration – paying beneficiaries is the issue, not identifying them.

The DBT rural preparedness scores are significantly worse than the urban scores, with an average of 3 per cent and a maximum of 5 per cent (Haryana). Comparing the rural and urban indexes, it is clear that last-mile financial inclusion is the main constraint to make JAM happen in much of rural India.

BAPU preparedness is much better than for Rural DBT preparedness. The average state preparedness is 12 per cent, but there are some states – like Andhra Pradesh (96 per cent), Chattisgarh (42 per cent) and Madhya Pradesh (27 per cent) – that with some policy push could be well-prepared for BAPU in the near future.