Each government scheme, then, is free to dip into this list to come up with a list of beneficiaries depending upon the criterion it wishes to use.
The Bibek Debroy committee on using SECC data to identify the number of urban households who are eligible for ‘automatic inclusion’, going by a report in Hindustan Times, has pruned the number from 18.1 million to 7.2 million—while the SR Hashim committee was first asked to do this, Debroy’s job was to ensure the methodology used was similar to the one used for rural areas. The exercise is a useful one, and the best thing about SECC data is that it is a list of the poor that both the central and state governments agree upon; to that extent, it is the best list to use for all government programmes, though it has to be ensured the census is updated regularly since the current data pertains to 2011. But what matters more than the number of households that are ‘automatically included’ in the list of deprived, is the number that are considered to be deprived using various criterion. So, in the case of rural India, while a mere 1.7 million households are ‘automatically included’ in the list of deprived households, the total ‘considered for deprivation’—to use the government’s terminology—is a much larger 10.7 crore. Of this, for instance, 2.8 crore households are to be considered deprived if you’re looking at those who have just one room or kuccha walls/roof while another 4.2 crore are deprived if you consider the number that don’t have any literate adult above the age of 25 years, and the number is a much higher 5.4 crore if you consider those who derive much of their income from manual labour. Each government scheme, then, is free to dip into this list to come up with a list of beneficiaries depending upon the criterion it wishes to use.
While that is a good thing, a situation in which 60% of the population—10.7 crore of a total of 17.9 crore rural households—is considered deprived using one or the other yardstick is problematic since there is no way the government can afford to devise schemes to meet their needs. SECC data, in any case, vastly overstates poverty—while SECC says 51% of rural households get most of their income from casual labour, the NSS puts this at a much lower 35%; in overall terms, the NSS has a mean household income that is around 45% higher than that in the SECC data. In which case, while the government goes about updating the SECC data for various types of deprivation, it needs to examine just how good the SECC data really is and make the necessary corrections. If it does not, the bill for the government will be very steep.
