India. Craig Jeffrey

India - Craig Jeffrey


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as Bihar, UP, Chhattisgarh and Odisha – have not generally (the exception is Odisha) seen high rates of poverty reduction. Indeed, poverty actually increased in Chhattisgarh between 2004–05 and 2009–10 (Himanshu and Sen 2014: 86). Work by Radhakrishna (2015), using somewhat different measures, reaches the same conclusions for the period since India initiated economic reforms: growth has been pro-rich and urban-biased; welfare improvements would have been better if inequality had not increased; inter-state inequalities increased, and the slowest reduction in poverty has been witnessed in the states with the highest initial incidence of poverty. Growth has certainly not made for ‘inclusive growth’ by reducing the disparities in levels of well-being across the major states.

      The question then arises as to how far the trends that are shown up using conventional poverty measures are qualified when account is taken of a range of direct indicators of well-being. Some of these measures radically qualify the suggestion that deprivation is being very significantly reduced in India, as a result of high rates of economic growth. India’s infant mortality rate in 2012 was 47 per 1,000 births, three times the rates in China, Brazil and Russia, and about 20 per cent higher than the international trend predicts for a country with India’s GDP per capita (Coffey and Spears 2017: 5). According to data from the National Family Health Survey (NFHS) of 2005–06, after twenty years of high rates of economic growth, 48 per cent of Indian children under the age of five were stunted (low height for age), and 43 per cent were underweight. These figures had come down by 2015–16, according to NFHS-4, but there were still more than a third of Indian children who were abnormally short and skinny. The numbers of those who were found to be stunted stood at 38 per cent, and 36 per cent were underweight, while the share of children who were wasted (low weight for height) actually increased from 19.8 to 21 per cent. More than one-third of India’s children were at risk of permanent physical and/or mental impairment as a result of poor nutrition. Indian children are shorter, on average, than children in Sub-Saharan Africa who are poorer; and ‘height is steeply associated with cognitive achievement in a developing country such as India’, as Coffey and Spears explain (2017: 136). These authors point out that while differences in height reflect both genetic differences and differences in the health and nutrition of young children, ‘genetic differences would not cause height and cognitive achievement to be correlated; the correlation is a product of children’s environments’ (2017: 136).

      How, then, does the Multidimensional Poverty Index (MPI) reflect upon trends in the reduction of poverty and on improved well-being in India? This is calculated from the combination of ten indicators, each per household: (i) education: years of schooling; school attendance; (ii) health: under-5 mortality; nutrition; (iii) living standards: access to electricity; to improved sanitation; to piped water; housing quality; cooking fuel used; assets owned. Sabina Alkire and Suman Seth have calculated the MPI for India, and across Indian states, for the period 1999–2006 (Alkire and Seth 2015). Although they report that income poverty – or monetary deprivation – does not generally proxy accurately for other deprivations, their calculations of the reduction in the MPI over this period, across Indian states, do not suggest a very different picture from that based on the conventional poverty measures. They find a statistically significant decline in the MPI nationally – overall, India reduced the proportion of multidimensionally poor (a headcount ratio) by 8.3 per cent over the period, or by 1.2 percentage points per annum – a higher rate, in fact, than that of the reduction in monetary poverty over the period they have studied. In 2006 the headcount MPI for the country as a whole stood at 48.5 per cent. But neither West Bengal nor any of what used to be referred to as the BIMARU states (Bihar, Madhya Pradesh, Rajasthan and Uttar Pradesh) had reduced poverty by very much, whereas the four south Indian states, and Maharashtra, had all experienced very significant reductions. Across the various subgroups Alkire and Seth considered, too, poverty had fallen fastest among the least poor, so that disparities had increased between the groups. The Scheduled Tribes had experienced the slowest reduction in poverty. What is also striking, in the analyses of trends in the MPI, is India’s relatively poor performance by comparison especially with Bangladesh. India’s eastern neighbour has succeeded in reducing the MPI about twice as fast, though with a similar rate of growth of national income (Alkire and Seth 2015).

      We drew attention earlier to the findings from recent research that higher levels of education, urban residence, being engaged in wage work, and belonging to social groups other than Dalit, adivasi or OBC are positively associated with higher-than-average chances of upward mobility. These observations point to the significance in India of what the social historian Charles Tilly (1998) refers to as ‘durable inequalities’ – inequalities, that is, across groups of people defined by relatively rigid social discriminators. This is the case, without question, of distinctions relating to caste, tribe and religion.


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