Neither BPL nor APL
Socio-Economic and Caste Census can help identify welfare beneficiaries without falling into a binary trap.
The last BPL census had been conducted in 2002 and the procedure then adopted was to collect information on 13 indicators for every rural household and assign a mark for each of these.
The release earlier this month of the Socio-Economic and Caste Census (SECC) has been followed by much media analysis. Some have expressed scepticism about what it shows and others have treated it as yet another set of numbers on how many are poor in India. It has also been variously hailed as revolutionising benefit transfers and slammed mainly on the absence of the caste data. However, no one has really discussed what this data enables and what still remains to be done. Also, after the big-bang release, the government has not elaborated on how it intends to use this data or on the timelines involved. My aim here is to congratulate the present government for taking ownership of the SECC, and also point out that there are still pending matters.
Not many know that the SECC grew from an almost routine exercise to perhaps one of the most ambitious of its kind ever conducted anywhere. The original intent was to simply update existing BPL (below poverty line) lists. The last BPL census had been conducted in 2002 and the procedure then adopted was to collect information on 13 indicators for every rural household and assign a mark for each of these. Households were ranked on the basis of their total marks, and the cut-off for BPL selection was the mark at which the total number of BPL households in a state was equal to the Planning Commission’s poverty estimate for that state. Since the latter was based on surveyed per capita consumption, completely different from the BPL census indicators, the result was a conceptual hotchpotch. It also lacked transparency — no one really knew why they had or had not been classified as BPL — and was therefore subject to manipulation. The outcome, as is well known, was that many relatively rich persons were included and many genuinely poor people were left out of the BPL list. This list, moreover, was mindlessly binary since it determined eligibility to either none or several welfare benefits, each of which sought to address a different need.
The committee appointed by the ministry of rural development, under the chairmanship of N.C. Saxena, to suggest the broad design of the new BPL census noted all of the above and proposed a radical departure: A three-fold classification of households between “excluded”, “automatically included” and “others”. The first of these, to be identified on the basis of assets and income, would be excluded from welfare benefits. The second, to be identified on the basis of acute social destitution, would be eligible without any further condition. “Others” would be ranked on the basis of indicators of deprivation and would, resources permitting, be eligible for suitable benefits. Further, noting problems of manipulation, it recommended both gram sabha oversight and a national data registry.
The implementation of this was led by B.K. Sinha, then secretary, rural development, who took a number of pathbreaking steps. Conscious of possible data misreporting, he set up a small core group of officials and academics and, taking the states on board, conducted a detailed pilot census in 250 villages across the country to test the reliability of the indicators before finalising the questionnaire. He coordinated with the registrar general who, in the meantime, had been asked to conduct a caste census. So both exercises could be done through the same questionnaire, riding on house-lists prepared for the 2011 Population Census and the National Population Register. He also got public-sector undertakings to provide over six lakh handheld electronic devices and operators who worked with state officials to conduct a paperless census, household data from which was uploaded in near real time on to a central server. The core group at the Centre analysed this data against the Population Census and other sources, requesting resurveys in cases of gross mismatch. In addition to this and other supervisory checks, he also got the states to agree that, in the interest of transparency, the preliminary data uploaded would be final only after every household had the chance to see their data, file objections and subject it to public audit in the gram sabha.
The data now released is mainly the preliminary upload for rural areas, which was already in place by end-2013. The final lists after public audit are complete only for half the rural districts, and progress has been even slower in urban areas, where the urban development ministry is implementing a different methodology, devised by a committee chaired by S.R. Hashim. On caste data, the registrar general’s office still awaits inputs from the states on how to classify the very large number of castes reported.
There is, therefore, much to be done before the SECC is completed. Nonetheless, having examined the rural data as chair of an expert committee on the use of SECC data for rural development, I am convinced that it amounts to an online national registry of good-quality household-level data that can be used to identify beneficiaries for each of the many government welfare programmes separately, without falling into the binary BPL trap. Most of the data are robust and consistent with those available from other sources, at least up to the state level. Also, there is no evidence of large data misreporting, except possibly on land, and if anything, richer respondents could hide much less wealth in the SECC than assessed in the pilot census. The pilot-based exclusion criteria, which eliminate households that meet any one of 14 exclusion indicators, exclude 40 per cent of households in the full data, against only 28 per cent in the pilot.
Besides considering possible specific criteria for social pensions and the Indira Awaas Yojana, our committee recommended relaxing the exclusion criteria so that a household would be excluded either if it had any one of five specified indicators or if it possessed any two of the remaining exclusion indicators. This would bring the rural exclusion criteria conceptually closer to those recommended by the Hashim Committee for urban areas and, by reducing the excluded proportion from 40 per cent to about 25 per cent, also be consistent with the National Food Security Act (NFSA). Of course, other options exist, but consistency in exclusion across rural and urban areas and with the NFSA may help the states to complete the already delayed final stage and proceed to the actual use of the data.
The writer is professor, Jawaharlal Nehru University, Delhi, and former member, Planning Commission.
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