The much discussed JAM (Jan-Dhan+Aadhaar+Mobile) trinity holds great promise for India, in our view
Neelkanth Mishra | Last Updated at February 6, 2017 23:05 IST
(This was published in the Business Standard: link)
The much discussed JAM (Jan-Dhan + Aadhaar + Mobile) trinity holds great promise for India, in our view. When everyone has bank accounts, can be uniquely identified, and can access their money without any intermediary, subsidies can be delivered leakage free and at low cost of administration.
However, these are necessary but not sufficient for a robust subsidy delivery system, for how would you select your beneficiaries? Announce beforehand that a card would be the basis of some subsidy, and the better-off find ways to get it despite being ineligible, and to restrict the needy from accessing it. Field workers know that getting a BPL (below poverty line) card required to access many subsidies can be “influenced”; or that when the Sarpanch decided who got the rural housing subsidy, he demanded a meaningful part of the grant.
It is here that we believe the government’s decision to use the 2011 Socio-Economic Caste Census (SECC) promises to bring about a dramatic improvement: The JAM trinity becomes the JAMS (i.e. JAM + SECC) quaternity. When this survey was being conducted, neither the enumerators nor the citizens knew it would be used to target subsidies, reducing data fudging: Being called a ‘Census’ may have helped. More importantly, it uses objective exclusion criteria (for example, owners of two-wheelers and other vehicles, are automatically excluded), and multiple observed measures of deprivation for inclusion (like type and size of house, nature of occupation, presence of adults in house, etc.). Further, unlike the Population Census, data collected in the SECC (over 2011-13) need not be kept confidential and are open to use by government departments.
The rural housing scheme, the Pradhan Mantri Awas Yojana–Gramin (PMAY-G), has used it to identify the first 3.3 million households that are to receive the subsidy: These met the largest number of deprivation criteria. The disbursal process is rigorous: Households need to link their Aadhaar and bank accounts (so there are no intermediaries), geo-tag it (so multiple claims are not registered for the same building), and then upload a picture of their current house, before the first sum is disbursed. While the PMAY-G targets appear rather ambitious, the process is scalable, which typically has been the bane of such schemes.
Over time, the intent is to use SECC data in other schemes as well. Staying one step ahead of those who find loopholes to exploit the system and keeping the data updated without losing the objectivity of responses are likely to be ongoing challenges. But this is a very important step forward, not just in improving and tracking the efficacy of government schemes, but also monitoring economic change.
The SECC data in aggregate, however, also provide some troubling insights and trigger difficult questions. For example, they show evidence of significant income inequality in rural India: That this is not surprising does not make it any less undesirable. The 30 per cent of households reliant on cultivation is broadly similar to the 29 per cent share of agriculture in rural gross domestic product (GDP), implying the “average” income from agriculture is broadly similar to the “average” rural income. That averages can be very misleading is well acknowledged (there are poor farmers and rich farmers), but the truly distressing statistic is the 51 per cent of households doing manual labour and accounting for a very small share of rural GDP.
Some have challenged the accuracy of these data, but observed deprivation suggests the data may be in the right ballpark as nearly half the households had one or more of deprivation characteristics: One or less room in a kuccha house (13 per cent), landless households reliant on manual labour (30 per cent), those with no literate member above the age of 25 (24 per cent), etc. Less than 10 per cent of the nearly 180 million rural households had salaried jobs, and worryingly nearly two-thirds of these were in government; only 3.5 per cent of rural households had private sector salary income. Only 1.6 per cent of the households ran their own non-agricultural enterprises. Not only does this explain the perennial attraction of reservations in government jobs, it also underlines the limited reach of the Indian corporate sector in rural India. As rising agricultural productivity meets slowing food demand growth, the long-awaited exodus of workers from agriculture is starting. Does the government have a role in encouraging in situ enterprise creation in rural areas, given the inability of our cities to absorb this scale of inward migration? Even if the government has the intent, what is its capability in influencing job creation on this massive scale? Floundering skilling schemes that have anyway struggled to scale may not be the answer.
For now, the best approach may be to improve basic rural infrastructure and then wait for human ingenuity and ambition to do the rest. Investments in hard infrastructure like rural roads (50,000km each to be built in this financial year and the next), household electrification (43 per cent higher budgetary allocation in the next year) and telephony (private sector driven) are necessary, but so is the need to improve law and order, the availability of data, access to credit (needs to be more market driven to avoid distortions), and markets (even export markets, for agricultural processing).