India. Craig Jeffrey

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СКАЧАТЬ whose recent growth record is no better than India’s, people spend less, incurring fewer debts, for obtaining medical treatment’ (2017: 115). It is to be hoped that a massive new health insurance scheme – known as Ayushman Bharat – announced by the Finance Minister in the Budget of 2018 will serve to correct India’s very poor record in regard to the provision of health care.

      Given Krishna’s well-reasoned arguments, the picture of health in India that comes from recent official studies is quite depressing. A massive report, entitled India: Health of the Nation’s States, was published by the Government of India in November 2017, accompanied by paper published in the medical journal The Lancet (2017), based on studies of a very large number of disease conditions and injuries and risk factors over a 26-year period (Bhuyan 2017). Health is a state responsibility in India, and though some funding, as well as policy and legislation, is provided by central government, states have wide scope in implementation. The largest proportion of health spending comes from the states’ budgets. Over time, each of the states has developed its own health story, and there are very large inequalities. Nine states – Assam, Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Odisha, Rajasthan, Uttarakhand and Uttar Pradesh – have been classified as ‘high focus’, implying that they need special attention. Together they account for disproportionate shares of infant, child and maternal deaths, even while failing to spend the funds that they have allocated for healthcare. In some cases, even when these states have increased spending, outcomes have not improved by as much as might have been expected, because of inadequacies in the existing health infrastructure and personnel (Rao 2017).

The disparities between states in regard to health care, which belie the stated intentions of planners and policy makers to achieve ‘inclusive growth’, are reproduced in comparisons of poverty reduction. Both Himanshu and Sen, and Narayan and Murgai find higher rates of poverty decline in initially richer states, so that there is increasing divergence between all the major states. There is an increased concentration of those who are most vulnerable to poverty in the states that are classified as ‘low income’ (Assam, Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Odisha, Rajasthan and Uttar Pradesh). Given their large populations and their poverty rates, UP, Bihar and MP together account now for 44.2 per cent of all India’s poor people (Narayan and Murgai 2016: fig. 11a). Except in the case of Odisha, poorer states (notably Assam, Bihar, Chhattisgarh and Jharkhand) have shown only marginal decline, or even some increase in the incidence of poverty (Himanshu and Sen 2014: 80). And simplistic arguments about the positive relationship between economic growth and poverty reduction are belied by the observation that the states that have seen the highest rates of growth of net state domestic product, since 2004–05 – states such 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).

Much depends upon whether or not children grow up in a healthy environment, and in India this is profoundly influenced, negatively, by the persistence of open defecation. According to NFHS-4 (2015–16), more than 56 per cent of all households did not have access to improved sanitation (though this was down from 70 per cent in 2005–06); and 52 per cent of all Indian households defecated in the open (63 per cent of rural households). And many of those who do have access to ‘improved sanitation’ continue to defecate in the open (though the Government of India’s Economic Survey for 2017–18 presents data showing that 91 per cent of those with toilets actually use them, suggesting that the Swachh Bharat Mission [SBM] – launched by prime minister Modi in 2015, with the objective of eliminating open defecation by 2 October 2019, the 150th anniversary of Gandhi’s birth – has had some success; and see Joshi 2018 for an upbeat account of the success of the SBM). We will return to the significance of these observations in chapter 4.

      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).

The picture that we take from the work of Himanshu and Sen, and that of Narayan and Murgai, on recent trends in poverty reduction, relating principally to the period of ‘superfast growth’ from around 2003, complemented by the observations of Krishna from empirical research on poverty dynamics, is a distinctly mixed one – an historically fast rate of decline of poverty in the aggregate (according СКАЧАТЬ