From UPSC perspective, the following things are important :
Prelims level : Gini
Mains level : Paper 2- Analysing NHFS-5 data
The release of the NFHS data (and the Niti Aayog’s study on developing a multi-dimensional index of poverty — MPI) has led to a considerable amount of discussion, and justifiably so.
Understanding the progress and development: MPI
- The MPI is an Oxford-based initiative that develops an exclusive broadly non-monetary living standard index of poverty.
- MPI indices are the third in the series of global studies on poverty.
- Global studies on poverty: Global studies started with the World Bank’s income/consumption-based measure of absolute poverty.
- The UN expanded the monetary index adding health and education indicators via the Human Development Index (HDI).
Evolution of poverty over time
- Like with the other poverty indices (World Bank and HDI), most information and useful policy analysis comes via a study of the inter-temporal evolution of poverty.
- Regional inequality: Ajit Ranade acknowledges that regional inequality has existed for some time, but he argues that poverty incidence across Indian states even as per the MPI is astoundingly unequal.
- T N Ninan talks about the simultaneous existence of Africa’s Sahel region and the Philippines in India.
- He finds that the two Indias are not getting any closer.
- Indeed, India’s development trajectory has not been uniform, but the regional imbalance of development cannot be viewed at a fixed point in time.
Analysing the NHFS data
- A detailed examination of the summary statistics reported in the NFHS data (large and small states of India for the two years 2015-16 and 2019-21), reveals the opposite result.
- Convergence: The analysis reveals remarkable convergence in living standards, a convergence possibly unparalleled in Indian history and in the space of just five years.
- NFHS reports the averages for all states, and for 131 variables, for two years 2015-16 and 2020-21.
- Seventeen of these 131 welfare indicators are used to construct indices under four classifications.
- Improvement in lives of girls/women: The first classification concerns itself with the improvement in the lives of girls/women (five indicators, for example, sex ratio, fertility, female education).
- Housing conditions: The second bucket consists of housing conditions (three indicators, for example, improved sanitation, clean fuel).
- Children’s welfare: The third list consists of children’s welfare (four indicators such as adequate diet, stunting)
- Women’s welfare: The fourth classification includes women’s empowerment (five indicators, for example, owning a house, less spousal violence).
- Given that Niti Aayog’s report primarily relies on the NFHS-4, these findings can be used as the baseline scenario to evaluate the delta — that is, the per cent change in indicators between NFHS-4 and NFHS-5.
- The table reports the results for several states.
- Seventeen indicators imply a maximum possible score of 1,700.
- Kerala performs the best with an aggregate index of 1,300 in NFHS-5 — a very small 1.5 per cent increase from its 2015-16 value.
- In contrast, Bihar increases its index by 56 per cent.
- Punjab does better than Tamil Nadu and today has a higher index – 1,240 versus 1,178 in 2020-21.
- UP (along with Rajasthan and MP) performs the best — a 60 plus per cent increase in the welfare index, more than five times the increase in the rich states.
Major findings from the NHFS data
- Convergence: Higher improvement by less developed states is evidence in support of catch-up, which suggests that regional imbalances are reducing, and in some indicators, rapidly so.
- States such as UP, Bihar and Jharkhand are fast approaching similar standards for select indicators as some of the “developed” states.
- Result of targeted intervention: This acceleration in catch up is no coincidence, but rather an outcome of an approach that involves targeted interventions to improve developmental outcomes.
- The approach was not just limited to sanitation, proper fuel or electricity — interventions that are targeted to an individual household — but also to the holistic development of an entire region.
Consider the question “What does NHFS-5 data reveal about the inequality in India?”
India has been, and was, not one but several Indias. What is remarkable about its recent history is the rapid process of uneven change — where progress is considerably higher for the poorer states — the convergent, and inclusive pattern of development. That is the real story behind the NFHS-4 and NFHS-5 numbers.
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