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On this statistical vacuum, all eyes are on the Centre for Monitoring Indian Economic system (CMIE) and its Client Pyramids Family Survey (CPHS). CMIE is a personal company engaged within the assortment and compilation of Indian statistics, on the market. CPHS is a periodic survey, carried out 3 times a 12 months in successive four-month ‘waves’ since January 2014. It’s primarily based on ‘an all-India consultant pattern of over 170,000 households’ in line with CMIE’s web site. Additional, that is meant to be a panel dataset, largely monitoring the identical households over time, although response charges range, and new households are incessantly added to compensate for attrition.
Apart from its hefty value, the CPHS dataset is – or, at the least, sounds — like a researcher’s dream. It has turn out to be a veritable barometer of the Indian economic system, intently watched for information on earnings, expenditure and employment specifically. Analysis papers primarily based on CPHS information are additionally mushrooming. CPHS even stayed the course, we’re informed, in the course of the Covid-19 disaster. The nation owes a good-looking debt to CMIE for coming to the rescue of its battered statistical system.
Is it actually true, nevertheless, that CPHS is a ‘strong, nationally consultant and panel survey of households,’ as a June 2021
World Financial institution dialogue paper places it, echoing many comparable descriptions of this survey in influential articles?
Take into account this: in line with CPHS, grownup literacy (15-49 years) was 100% in city areas and 99% in rural areas in late 2019. That’s too good to be true. It means that CPHS is biased in direction of better-off households.
The plot thickens after we evaluate literacy charges at completely different factors of time. 4 years earlier, in late 2015, the literacy price in the identical age group was solely 83% in line with CPHS information. May it actually be that grownup illiteracy was worn out inside 4 years? Appears unlikely.
We are able to pursue this matter by taking a look at literacy for a similar cohorts over this era. For example, we are able to evaluate the 15-49 age group in late 2019 with the 11-45 age group in late 2015. These two teams correspond to the identical cohort. If CPHS is generally a panel dataset, the literacy price of this cohort needs to be a lot the identical in 2015 and 2019. However, in reality, it rises in successive waves, from 84% in 2015 to 99% in 2019. This implies that the CPHS pattern turned
The bias already utilized in late 2015, judging from a comparability with the sooner NFHS-4. The CPHS estimate of grownup literacy (15-49 years) at the moment is 6 proportion factors greater than the NFHS-4 estimate for 2015-16, for each women and men. The bias can also be evident from information on family belongings. In accordance with CPHS, as an illustration, 98% of households had electrical energy in late 2015, 93% had water inside the home, 89% had a tv, and 42% had a fridge. The corresponding figures from NFHS-4 are a lot decrease: 88%, 67%, 67% and 30% respectively.
There is no such thing as a assure that NFHS-4 is extra dependable than CPHS. However at the least we all know that it’s a nationally consultant survey, and the NFHS-4 figures additionally look extra believable than their CPHS counterparts. Additional, the NFHS-4 literacy figures are in line with 2011 census information for a similar cohorts, however CPHS literacy figures should not — they’re too excessive.
As said earlier, it appears the CPHS bias in direction of better-off households elevated over time. By 2019, the bias was actually embarrassing, judging from comparable comparisons with NFHS-5 information for the 11 main states the place that survey is on monitor. Take into account Bihar. In accordance with CPHS, 100% of households in Bihar had electrical energy in late 2019, 100% had water inside the home, 98% had a rest room, and 95% had a TV. Paradise! The corresponding NFHS-5 figures are a lot decrease, and way more believable (96%, 89%, 62% and 35% respectively). Bihar is only one state. However an identical distinction emerges for these 11 states collectively (see desk).
One other clue emerges from comparisons with the Periodic Labour Drive Survey (PLFS) 2018-19 offered within the Azim Premji College State of Working India 2021 report (bit.ly/2SQvcqO). These recommend that CPHS overestimates common labour earnings by an extended margin — maybe 50% or so in rural areas.
In brief, removed from being nationally consultant, the CPHS pattern is closely biased in direction of better-off households, and fairly possible, the bias is rising over time. The bias is, maybe, not stunning, for the reason that sampling methodology apparently consists of surveying the ‘predominant avenue’ first in every pattern village or enumeration block, and continuing to interior streets provided that the pattern measurement requires it. If solely because of this, poor households are certain to be under-represented.
By the way, we observed this
bias in CMIE information in a latest evaluation of proof on the financial impression of Covid-19. A sequence of family surveys specializing in casual sector employees and their households strongly recommend that employment, earnings, expenditure and meals consumption remained effectively beneath pre-lockdown ranges all through 2020. CPHS, in contrast, suggests pretty speedy restoration quickly after the nationwide lockdown. This obvious contradiction is instantly resolved if we keep in mind that poor households are grossly under-represented in CPHS information.
All that is only a pattern of statistical points that decision for pressing scrutiny, given the outstanding function of CMIE information in financial discussions in the present day. Step one is for CMIE to reassert or retract its declare that CPHS is a nationally consultant survey (a good expectation, certainly, from an company that fees $180,000 per wave for including a one-minute query within the survey). After that, let 100 voices growth.
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