Socio Economic Caste Census (SECC) | Everything you need to Know

• SECC began as a routine exercise. 
• Original intent to simply update existing BPL lists 
• Last BPL census was in 2002 - procedure then adopted was to collect information on 13 indicators for every rural household and assign a mark for each of these and then give them ranking on the basis of the 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.
• Hotchpotch - But the PC's estimate was based on surveyed per capita consumption, completely different from the BPL census indicators
• It also lacked transparency --> Scope for manipulation
• Final outcome - Relatively rich persons were included and many genuinely poor people were left out of the BPL list. 
• The committee was 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”, 
• to be identified on the basis of assets and income, would be excluded from welfare benefits. 
• “automatically included”
• To be identified on the basis of acute social destitution, would be eligible without any further condition
• “others”. 
• Ranked on the basis of indicators of deprivation and would, resources permitting, be eligible for suitable benefits. 
• For avoiding manipulation, it recommended both gram sabha oversight and a national data registry. 
• The implementation of above was led by B.K. Sinha, who took a number of pathbreaking steps. 
• Made sure that data is not misreported
• 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. 
• Data was uploaded in near real time and then analysed this data against the Population Census and other sources, requesting resurveys in cases of gross mismatch. 
• 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. 
• This above has come out now
• The data now released is mainly the preliminary upload for rural areas, which was already in place by end-2013. 
• But the data that has come is incomplete - only for half the rural districts
• 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. 
• Abhijit Sen says 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. 

Now for further details like - The need, details of above mentioned methodologies, advantages, criticism follow this article by Mrunal Patel Sir

Key Takeaways from rural SECC

1. Total rural deprivation 48.5%
1. state wise highest share of deprived rural people (descending)
1. Chhatisgarh - 70%
2. Meghalaya
3. Odisha
4. Nagaland
5. West Bengal
2. Excessive reliance on land
1. will have bearing on policy and poverty alleviation and also on Land bill
3. The seven criterion of deprivation as explained on mrunal are highly stressed
1. nearly 50% hosue holds have some deprivation
4. financial status - 75%households have highest /month income <5k
1. reasons
1. Lack of skills
1. landless households heavily dependent on casual labour (~40% - highest in TN and PB is in top 5)
2. low level of non-farm activity
3. Missing private sector jobs
4. Govt and public sector not doing well either
5. landed still highly depended on grains - 30% landowners have unirrigated land
6. high level of illeteracy (36% illiterate)
5. Nearly 70% own a mobile
6.