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Sunday, June 26, 2022

Counting those who qualify as EWS

Shamika Ravi, Mudit Kapoor write: Study reveals that more than 90 per cent of rural and urban non–SC/ST/OBC households will meet the government’s criteria for economically weaker sections

Written by Shamika Ravi , Mudit Kapoor |
Updated: March 8, 2022 12:58:58 pm
Given the sensitive nature of the issue, it is essential to highlight the limitations of the earnings data from the PLFS. (Illustration: C R Sasikumar)

On January 31, 2019, the Government of India (GoI) issued a circular, which guaranteed 10 per cent reservations in civil posts and services of the GoI to the Economically Weaker Sections (EWS) of the society, who were not covered under the reservation scheme for Scheduled Castes (SCs), Scheduled Tribes (STs), and Other Backward Classes (OBC). The GoI used two criteria for the definition of the EWS: One, the gross family income from all sources — agriculture, business, professional, etc. — for the financial year preceding the application should be less than Rs 8 lakh; Two, if the family owned or possessed assets, such as five or more acres of agricultural land, or residential flat of 1,000 square feet or more, or a residential plot of 100 square yards or more in notified municipalities, or a residential plot of 200 square yards or more in non-notified municipalities, then irrespective of the income criteria, the family would be excluded from the definition of EWS. The family includes those who seek the benefit, their spouse, parents, siblings, and children below 18 years.

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However, the Rs 8 lakh cut-off has come under the scrutiny of the Supreme Court (SC). The SC has sought clarification from the GoI regarding the basis for the income cutoff. We explore this issue using earnings data from the Periodic Labour Force Survey (PLFS) from July 2018 to June 2019. The GoI conducts the PLFS to measure labour force participation, employment status, hours worked, and earnings for the usual and the current weekly status (CWS). The geographical coverage of the PLFS is the entire country, except for villages in Andaman and Nicobar Islands that are difficult to reach. The PLFS covers all sectors of the economy, agriculture, secondary, and tertiary, and employment status, whether individuals are self-employed, have a regular wage/salaried job, or are casual workers. In addition, it also collects data on earnings based on the CWS. The ultimate stage units of the PLFS were households, where information on employment and unemployment is sought from all family members of the household. In addition, data is also collected on socio-demographic characteristics of the household, such as the religious and social status of the household, whether it belonged to SC/ST/OBC or the general category. Our analysis is based on the PLFS conducted between July 2018 and June 2019, covering 101,579 households, of which 31,796 (31 per cent) households did not belong to SC/ST/OBC. In addition, we exploit the sampling methodology to arrive at the estimates.

Based on data on non-SC/ST/OBC, we found that 99 per cent of rural households and 95 per cent of urban households had monthly earnings less than Rs 66,667, which would translate to approximately Rs 8 lakh annually. Moreover, the median household monthly earnings in rural areas were Rs 9,000, which was about seven times less than the earnings cutoff for EWS, while in urban areas, it was Rs 15,000, which was approximately four times less than the earnings cutoff for the EWS set by the GoI.

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Empirical Cumulative Distribution Function of monthly household earnings of General category

However, suppose we were to exclude households with zero earnings. In that case, our analysis reveals that for non-SC/ST/OBC households, 99 per cent of rural households and 94 per cent of urban households had monthly earnings less than Rs 66,667, which would translate to approximately eight lakh rupees annually. Moreover, the median household monthly earnings in rural areas were Rs 10,000, which was about six and a half times less than the earnings cutoff for EWS, while in urban areas, it was Rs 20,000, which was approximately three and a half times less than the earnings cutoff for the EWS set by the GoI.

Given the sensitive nature of the issue, it is essential to highlight the limitations of the earnings data from the PLFS. First, the PLFS data is based on the current weekly status; there is a possibility that the household had positive income at other times of the year but not the week preceding the survey. Therefore, the earnings data is an underestimate. To overcome this limitation, we did the second analysis of including only those households with positive earnings and found that the underlying results did not change significantly; that is, more than 90 per cent of rural and urban non- SC/ST/OBC households had monthly earnings less than the cutoff set by the GoI for EWS income criteria. The second limitation of the study is the definition of family. The PLFS defines a household as a group of persons who usually stay together and take food from a shared kitchen. It is hard to assess how differences in the definition of family would impact the analysis. Our guess is that household or family definition in PLFS is more inclusive than GoI definition of family for the EWS criteria, which would suggest that these estimates are likely to overestimate the distribution of household monthly earnings.

In the absence of any objective data on the family’s earnings, we use the PLFS data from 2018-2019 to estimate the distribution of monthly family earnings from all sources (self-employment, regular wage/salary, and casual work). Our primary objective was to compare the EWS cutoff of income criteria set by the GoI at Rs 8 lakh annual income (approximately Rs 66,667 monthly income) with the distribution of household monthly earnings from the PLFS data. Our analysis reveals that more than 90 per cent of rural and urban non–SC/ST/OBC households will meet the EWS criteria.

This column first appeared in the print edition on March 4, 2022 under the title ‘Counting the EWS’. Ravi is Vice President, Observer Research Foundation, and Kapoor is Associate Professor, Indian Statistical Institute.

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