The All India Democratic Women’s Association has been at the forefront of the struggle for food security for all in India. In this connection it has over the years been actively engaged with the question of identification of beneficiaries for government schemes which is the responsibility of rural development ministry.

AIDWA has serious concerns with the methodology adopted using the findings of the Socio Economic Caste Census data for inclusion, exclusion and gradation of rural households. Following is the memorandum it submitted to the MORD in this regard on August 21.

WE would like to express our strong disquiet at the state of affairs surrounding the Socio Economic Caste Census (SECC) 2011. The SECC was supposed to collect data on caste, urban socio-economic status and rural socio-economic status. The clearly stated aim was to improve the identification of beneficiaries of welfare schemes.  Unfortunately, the process thus far has belied this hope and gives rise to concerns that the resulting identification of “the poor” will let down the people of the country.

The release of the data has been painfully delayed and as yet only the incomplete rural data have been partially released. The urban and caste data are still pending. The government, on July 28 2015, revealed that the data include over 8 crore mistakes, of which 1.46 crores were yet to be rectified. Why and how did so many errors creep into this state-of-the-art survey? We would also like to be informed about the exact nature of these errors.

The most striking finding from the data is that 92 percent of rural India earned less than Rs 10,000 per month and 75 percent heads of households earned less than Rs 5000 per month. This reinforces the argument for universalising government programmes for food security, employment, health, etc. 

The data is to be verified by the households themselves, as also by gram sabhas after putting up the data in public places with specific timelines to raise objections. The verification process is not yet complete and it is not clear how much longer it will take. Reports from the field suggest that special provisions need to be made to ensure that the poorest and most vulnerable sections such as single women, dalits and adivasis have access to the lists. It should be done in the local language. There is no appropriate mechanism for urban areas. 

Several analysts have pointed to concerns that the Survey many not have captured the full extent of deprivation, for example, by underestimating the number of households with workers involved in manual scavenging, or the number of homeless households or households without an adult male worker.

But the greater issue of concern is the use that is sought to be made of these data. The methodology for identification of the poor is extremely dubious and likely to lead to significant errors of underestimation. Regrettably, while the criteria to exclude are extremely liberal and extensive, perversely the criteria to include are too narrow and restricted. The criteria for compulsory exclusion are many and very broad and do not take account of multiple vulnerabilities that rural people face that may involve deprivation on several counts, leading to  as many as 40 percent of rural households (70.5 million) being compulsorily excluded.

Many of the exclusion criteria are perverse and unfair, with income tax payment being the least problematic. The two criteria which have resulted in the greatest exclusion are ownership of a motorised 2/3/4 wheeler or fishing boat, and pucca house with 3 plus rooms.  17.43 percent of all rural households own motorised 2 wheelers. How can ownership of a motorised 2 wheeler or a motorised fishing boat (that may in any case be necessary for livelihood in certain activities) be put on the same footing as a motorised 4 wheeler (which only 2.46 percent of rural households have)?  The housing indicator is also not very appropriate because in rural India many nuclear families occupy a single dwelling with more rooms. Furthermore it has been clearly established that some caste and religious groups, like Muslims, have larger joint households and therefore more rooms (with many nuclear households in a single homestead) but are actually still very poor.

The requirements for automatic inclusion are extremely stringent, such that only 0.96 percent (1.65 million households) meet the criteria.

We strongly feel that some of the deprivation indicators qualify far more to be treated as parameters for automatic inclusion, especially the following three: single room kucha dwelling (13.25 percent of rural households), SC-ST households (21.53 percent of rural households), and landless households primarily dependent on manual labour (30 percent of rural households).

Thus, this methodology for identifying eligible households for welfare schemes is deeply flawed, quite apart from the inadequacies and gaps in the data. In this situation welfare schemes and benefits to the poor cannot become dependent on this selection process and must not become the basis for targeting government schemes, in particular the NFSA. The government would do well to only exclude income tax payers, and provide benefits to everybody else. Further, insofar as the government wishes to use these data in the most effective way, it should recognise the evidence of multiple deprivations persisting widely among the population, expressed through poor housing, lack of employment, absence of basic amenities, inadequate social services, etc, and seek to address these by extending and improving universal provision.