View: There are practical limitations in CMIE’s CPHS sampling, but no bias – The Economic Times

Clipped from: https://economictimes.indiatimes.com/opinion/et-commentary/view-there-are-practical-limitations-in-cmies-cphs-sampling-but-no-bias/articleshow/83788605.cmsSynopsis

CPHS is a household survey of a nationally representative sample in the sense that it is selected through a process of multistage stratification and random sample selection over 98.5% of India’s population with no bias in sample selection or survey execution.

Mahesh Vyas

Mahesh Vyas

MD-CEO, Centre for Monitoring Indian EconomyIn their article (bit.ly/35HtxH8) on this page earlier this week, Jean Drèze and Anmol Somanchi critically examine the Centre for Monitoring Indian Economy’s (CMIE) Consumer Pyramids Household Survey (CPHS). They suggest CMIE ‘reassert or retract its claim that CPHS is a nationally representative survey’.

CPHS is a household survey of a nationally representative sample in the sense that it is selected through a process of multistage stratification and random sample selection over 98.5% of India’s population with no bias in sample selection or survey execution. Limitations with respect to national representation include the exclusion of four border states and Union territories (UT) of the northeast, some islands and one small UT on the mainland. We hope to expand into these regions eventually.

Our concern is of security of the team given that we do not carry the imprimatur or power of the state. Purists can disqualify CPHS as a ‘nationally representative sample’ because of these exclusions. But practical users accept these, as the rest of the nation is sampled well. Drèze and Somanchi say that a bias is inevitable because of the way households are selected from villages in which CMIE begins its selection from the main street, and then proceeds to the outskirts only if the sample size requires it to do so. As a result, they say, ‘poor households are bound to be under-represented’.

CPHS sampling begins at one end of a main street but ends in an inner street. Often, the starting of the main street is on the outskirts. It is not easy to avoid the outskirts in the CMIE sampling system. The average village in India has 300 households. The systematic random sampling exercise of CPHS requires the selection of every nth household in the village, where n is a random number between 5 and 15 and the sample size required is 16. If the random number is 5, then CMIE would exhaust the selection of 16 households on the main street only if the main street contained at least 80 households.

80 households cannot be found easily on just one street of a village. Access to inner streets is inevitable. If the random number is 10, then we need 160 households, and if the number is 15, we need 240 households on the main street for CMIE to exhaust the sample selection on the main street itself. Evidently, the CPHS sample cannot escape including households from the outskirts.

Our first choice was to enumerate all households like the National Sample Survey Office (NSSO) and do simple random selection. But this is not possible without local state support in all the 12,000 primary survey units because of security concerns. We have tried enumeration repeatedly, and have been stopped midway by the local arms of government or, in some cases, non-government forces. So, we are compelled to use the next best option — systematic random sampling.

Nevertheless, we take the criticism of the authors seriously enough to undertake a thorough study of the sample, and measure its distribution over the main area (street, circle or square) as against the outskirts. Wherever necessary, we will expand the sample to the outskirts. We hope to complete this exercise by April 2022. We are committed to creating and maintaining a robust and representative sample to the extent possible, without the luxury of the heft of sarkar with us. Drèze and Somanchi say that estimates based on CPHS claiming that adult (15-49 years) literacy was 100% in urban India in late 2019 are too good to be true. First, CPHS does not give ‘100% adult literacy’. The number is 99.6%. The (legitimate) rounding carries a misleading connotation. Besides, it is better to use a full calendar year as the census data are.

According to the census, literacy in the 15-49 group in urban India was 81.6% in 2001 and 86.1% in 2011. CPHS shows a rapid increase in literacy in this age group — from 89.4% in 2014 to 98.1% in 2020 in urban India. Note, this is not 100%. The annual CPHS estimates imply that urban adult literacy increased by 3.3 percentage points between 2011 and 2014 — a plausible 1.1 percentage point increase a year. Then, between 2014 and 2020, urban adult literacy increased at the rate of 1.45 percentage points a year.

Is this acceleration in urban adult literacy evidence of limitations of the CPHS sample, or of improvement in literacy among adult urbanites in a period when many were forced into participating in the aggressive digitalisation of India? Literacy is defined as a person’s ability to read. CPHS offers evidence that adult literacy accelerated perhaps because of digitalisation.

The authors state that the CPHS sample is becoming more biased towards the better off. But the reality is that it merely reflects the progress made by Indian households. Household incomes improved between 2014 and 2019. In 2014, households that earned less than Rs 1,00,000 a year accounted for 31% of the sample. By late 2019, their share dropped to 6.6%. But, in 2020, when the economy shrunk, the share of households that earn less than Rs 1,00,000 rose to 9.6% from 6.6% in 2019.

Including the very poor and the very rich adequately is always a challenge. The homeless are systematically missed. The rich are becoming increasingly inaccessible. There are practical limitations in CPHS. But no bias.

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