Column: How bad is the SECC data? Very bad

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Published: July 23, 2015 12:31:26 AM

The SECC data proves the old adage—garbage in, garbage out.

Lalu Prasad Yadav: We demand release of the caste data as per the socio-economic caste census (SECC).

Mainstream media (English) and the Congress party: More than 50 % of the households in rural areas are landless. The grim rural picture revealed by the SECC data show that the NDA has contempt for the poor. Congress party spokesperson Rajiv Gowda (Zee News, July 4): “SECC 2011 reveals that there is tremendous work to be done in rural India; further that past Congress governments had made huge efforts in transforming rural India via programmes like green revolution, white revolution and MGNREGA.” As twitterati would post, LOL.

The Modi government, which the Congress is attacking for SECC “revelations”, came to power in May 2014. One has come to accept Lalu’s clownishness, and he sometimes manages to be funny. But the grim-faced Congress, and its feigned “concern” for the poor, is both funny and tragic. The census in question started its operations in June 2011, when the Sonia Gandhi-led Congress was in power. The census was to be completed by December 2011, but only got completed sometime in 2013. Over these two years, the survey operations were done with hand-held computers using state of the art technology.


So, three questions arise: Why were the data not released by the Congress government? The reason hand-held computers were used was to allow faster processing and hence, faster release of the data. Second, why was the census done by the ministry of rural development (MRD) rather than by the Registrar General, Census,or by the NSS? Both organisations have been doing survey/census work for the last sixty-five years; MRD is rather late in this game, and has a reputation akin to the CBI rather than the NSS, i.e., it is prone to political compulsions rather than act as an objective, quasi-academic unit.

But one need not jump to conclusions. Before proceeding with Congress hyperbole and hyper-ventilating reactions, let us try and first assess the accuracy of the SECC data. There is a close benchmark NSS survey year to the SECC census; comprehensive data were collected by the NSS between July 2011 and June 2012 in two surveys—the Consumer Expenditure Survey (CE), which collected detailed data on consumer expenditures, and the Employment Unemployment (EU) survey, which collected detailed data on landholdings, individual wages and earnings, as well as the age and education structure of the population.

A detailed comparison of the SECC and the NSS is reported in the table. For all indicators except education, the SECC data seem to be compellingly bad, i.e., not worth discussing, let alone deriving any policy conclusions. But you judge for yourself. A caveat—the released SECC data are based on a total of 299 out of 640 districts. According to MRD and its advisers, the data have been only released after a thorough vetting, cross-checking, verification, etc. (see “Neither BPL nor APL”, The Indian Express, July 22, for details). So, even though incomplete, one can assume that the SECC data are representative and robust.

Education: This is the good news—SECC educational attainment data almost exactly match NSS data. For example, the proportion of illiterate in the rural population (SECC 35.7%, NSS 39%), or graduates in the rural population (3.5% SECC versus 2.4% NSS). Since Congress has been ruling India and formulating its education policy for 55 of the last 68 years, including the last 10, this is about as damning an indictment as one can obtain for the in-the-name-of-the-poor party. Fortunately for the Congress, the situation is not as bad—only 10.6 % of the rural households have zero literacy (NSS data). And 46.6 % of rural households have at least one member of the family with greater than 0 and less than 5 years of education, and 11.1 % of households have at least one member who has at least 14 years of schooling.

Given that the population education numbers match, one would expect that strong correlates of education, such as income, would match. This is where the SECC data fails big time. In its enthusiasm, MRD decided to go for the big enchilada—incomes of rural India rather than the more prosaic consumption data canvassed by the NSS. The NSS does collect income data, but the data collected are only for wages and salaries, and data omitted are for profits, rent, interest income, pension, etc. Hence, a conservative interpretation is that the NSS understates true rural income for the people whose incomes are reported.

Contrastingly, the SECC data are likely to overstate household income because it reports only the earnings of the highest-earning member in the household. One further overstatement in the SECC relative to NSS—the former is average for the period July 2011 to 2013, while the latter is for the agricultural year July 2011-June 2012. On average, the SECC 2011-2013 income data are likely to be 14% higher (9% inflation and 5% real growth) than the NSS 2011-12 data.

Despite the considerable overstatement involved in the SECC, it still reports lower rural incomes than the NSS. On a comparable basis (like with like, household with household, and all in 2012-13 prices), mean average household income is about 70 % of mean NSS income. (If we go into comparison with household income as compared to national accounts (NA), a rough guess-estimate is that SECC incomes are only a quarter of that revealed by NA!) One other clue to the badness of the SECC data—mean rural SECC household incomes are only 85 % of mean rural NSS consumption.

Land distribution: According to SECC, 56 % of the households are landless i.e. have ownership of land less than 0.01 hectare. The NSS estimate? A considerably lower figure—26.3%. Actually, the SECC estimate is almost identically half that yielded by the NSS!

Casual labour: NSS and SECC are very far apart on landless casual labour. SECC has more than half of the rural population whose major source of income is from casual labour—NSS has 35 %. SECC has 30% of households with income from casual labour and not possessing any land (<0.01 hectares), while NSS has only 1.8 % of such households.

The only fair conclusion is that MRD’s SECC data are not worth discussing, let alone analysing. What about the caste data? Release it if you must, but only after processing it and, more importantly, validating it. A true picture of Indian caste distribution will have to await a Census conducted exercise, and not one processed by MRD.

Bhalla is contributing editor, The Financial Express, and, along with Ankur Choudhary, the co-author of Criconomics

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