The Demographic Deficit
Bibek Debroy November 2007
Section 1: The Demographic Dividend
From 2001 to 2026, India’s population is projected to increase from 1.029 billion to 1.400 billion.[i] The proportion of population in the working-age bracket of 15-59 years will increase from 57.7% in 2001 to 64.3% in 2026. India’s present population is young, 54% of the population is aged 24 years and less.[ii] The 15-24 age-group accounted for 19% of the population in 2001, 195 million people. While the share will drop to 16% in 2026, in absolute terms, the number of people in the 15-24 age-group will increase to 240 million in 2011 and then decline a bit to 224 million in 2026. There is yet another way of looking at it. Between 2001 and 2026, the total population will increase by 371 million and 83% of the increase will occur in the age-group of 15-59 years. The points about a young population, declining dependency ratios and demographic transition are obvious enough and are variously referred to as India’s demographic dividend. The argument is expressed both in relative and in absolute terms, though this is not a neat and water-tight division. In relative terms, one brings in aging populations in the rest of the world, meaning not just developed countries, but also countries like Russia and China. The share of working-age populations will decline in those countries, but increase in a country like India.[iii] This enables India to tap its labour cost advantage, through emigration, temporary exports of skilled personnel (with increased remittance inflows) and off-shored relocation of production to India. Stated in absolute terms, one doesn’t necessarily bring in the rest of the world, but focuses on changes internal to the country. For instance, per capita GDP growth is positively correlated with the relative size of the working population and there are several complicated forces at work.[iv] First, there is the direct impact of a larger quantity of labour input. Second, when dependency ratios decline, savings rates increase, leading to increases in investment rates and higher rates of GDP growth. Third, if the decline in dependency ratios is at the lower end of the age spectrum as a result of fertility declines, female work participation rates increase. That too, increases GDP growth. For East Asia, several studies suggest that between 25 to 40% of the East Asian miracle was due to the demographic dividend.[v] Consequently, the contribution of the demographic dividend to future Indian GDP growth has been discussed quite a bit, not just in the popular press, but also in serious academic work.[vi] That the demographic dividend argument works, is known. Other than East Asia, it has worked in Japan in the 1950s, China in the 1980s and Ireland in the 1980s and 1990s. The problem is that it is virtually impossible to quantify the contribution of this demographic dividend to GDP growth, because that increment to growth requires several preconditions. Having said this, some journalistic-type back of the envelope calculations exist on what this demographic dividend may mean to India. These suggest that since the 1980s, the increment to GDP growth because of this has been of the order of 0.7% and that by 2020, this increment could increase to around 1.5%.
Section 2: The Millennium Development Goals
Let us digress for a while on the Millennium Development Goals (MDGs), to be attained by developing countries by 2015, on a base of 1990. There are eight such goals. (1) Eradicate extreme poverty and hunger; (2) Achieve universal primary education; (3) Promote gender equality and empower women; (4) Reduce child mortality; (5) Improve maternal health; (6) Combat HIV/AIDS, malaria and other diseases; (7) Ensure environmental sustainability; and (8) Develop a global partnership for development. Stated thus, these sound like vague motherhood statements. However, it is targets under these goals that make the goals operationally meaningful and enable one to quantify and measure progress towards the MDGs. There are 18 such targets. The 7 targets under goal 8 of developing a global partnership for development are irrelevant for present purposes. The targets for the other goals are shown in Table 1. One does notice that targets are a bit more precise up to Goal 5. There is a country report on India’s progress towards the MDGs.[vii] Based partly on this, three additional columns have been added in Table 1, showing the 1990 base, the present status and finally, a subjective assessment of whether that particular target can be reached. This subjective assessment is not based on the country report though. The point to be noted is that India seems to be on target on all the MDGs except the health ones (which of course represent a significant component) and the one on gender disparity in education. Three of the eight MDGs have something to do with health. Eight of the eighteen targets have something to do with health. And eighteen out of the forty-eight indicators are health-related. It is of course true that one cannot look at a MDG goal or target or indicator in isolation, since they are linked and improvements in one goal/target/indicator are often contingent on improvements in another.
Table 1: MDG Goals and Targets
|Goal 1 (G1)||Target 1 (T1): Halve between 1990 and 2015, the proportion of people whose income is less than $1 a day||37.5% (1990)||28% (2004)||Yes|
| ||Target 2 (T2): Halve, between 1990 and 2015, the proportion of people who suffer from hunger|| || || |
|Goal 2 (G2)||Target 3 (T3): Ensure that, by 2015, children everywhere, boys and girls alike, will be able to complete a full course of primary schooling||Drop-out rate of 41.96% in 199-92||Drop-out rate of 31% in 2003-04||Barely possible|
|Goal 3 (G4)||Target 4 (T4): Eliminate gender disparity in primary and secondary education, preferably by 2005, and in all levels of education no later than 2015|| || ||No|
|Goal 4 (G4)||Target 5 (T5): Reduce by two-thirds, between 1990 and 2015, the under-five mortality rate||125 per thousand in 1988-92||87 per thousand in 2003||No|
|Goal 5 (G5)||Target 6 (T6): Reduce by three-quarters, between 1990 and 2015, the maternal mortality rate||437 per 100,000 in 1991||407 per 100,000 in 2000||No|
|Goal 6 (G6)||Target 7 (T7): Have halted by 2015 and begun to reverse the spread of HIV/AIDS|| || ||No|
| ||Target 8 (T8): Have halted by 2015 and begun to reverse the incidence of malaria and other major diseases|| || ||No|
|Goal 7 (G7)||Target 9 (T9): Integrate the principles of sustainable development into country policies and programs and reverse the loss of environmental resources|| || || |
| ||Target 10 (T10): Halve, by 2015, the proportion of people without sustainable access to safe drinking water and basic sanitation||12% access in 1990||30% access in 2001||Yes|
| ||Target 11 (T11): Have achieved by 2020 a significant improvement in the lives of at least 100 million slum dwellers|| || ||Yes|
Table 2 expands on Table 1[viii] and reinforces the impression that India isn’t doing well on the health indicators, barring the one on improved access to drinking water. Most of India’s success in moving towards MDGs is growth related, such as reduction in hunger or drop in the percentage of population below the poverty line. But, in addition, education indicators have also tended to improve. Why hasn’t this success in education been replicated in the case of health? For instance, the MDG target requires an under-five mortality rate of 41 (per thousand) by 2015, but present trends suggest an actual figure of around 64 by then.[ix] The infant mortality rate (per thousand) will be around 47 by 2015, as against a target of 28. A diagnosis of what causes health problems is necessary before arriving at policy conclusions. For example, nutrition and anemia account for more than 50% of under-five deaths. High infant mortality is primarily due to pre-mature births, low birth weights, absence of post-partum care, diarrhea, lack of immunization and respiratory infections, not to speak of social problems like female infanticide.[x] More than three-fourths of maternal deaths are due to hemorrhage, sepsis, obstructed labour, abortions, toxemia and abortions, all indicating lack of access to ante-natal health services. The remaining one-fourth of maternal deaths is due to anemia, TB/malaria and viral hepatitis. The 1998-99 National Family and Health Survey reported that only 65% of mothers received ante-natal checkups. Improvements in health indicators are thus more complicated outcome improvements than improvements in education indicators. The National Human Development Report 2001, brought out by the Planning Commission in 2002, had the following.[xi] “The importance of health and longevity in the well-being of an individual and their instrumental significance in attaining other personal and socially valued outcomes is not always easy to present. Often the outcomes and efforts involved may not be quantifiable. For instance, healthy children are more easily able to attend school, pursue education and are likely to be better learners. Healthy adults are, perhaps, more likely to find work and be productively engaged in economic activity. As a result, they are likely to be better off than those who suffer from ill health. There is, however, ample quantitative evidence on the importance of attainments in other aspects of development in improving health sector indicators. The data collected for this Report shows that adult literacy, particularly adult female literacy, as well as average consumption levels are significantly correlated with life expectancy at age one, the correlation increasing between 1981 and 1991. Infant mortality rate is also correlated with adult female literacy rate, though not as significantly as in case of life expectancy at age one. It is also observed that adult literacy has a strong positive correlation with the kind of medical attention that is sought at the time of delivery. Based on analysis of data from 115 low and middle-income countries, it turns out that educational level of adult females as well as generation and utilization of new knowledge has a significant impact on improving health, longevity and demographic indicators. For instance, in explaining the reduction in under-5 mortality rate, improvement in female life expectancy at birth and reduction in total fertility rate (TFR), the percentage contribution of gain in income levels is less than 20 per cent, whereas improvement in educational levels accounts for more than 30 per cent in case of first two indicators and nearly 60 per cent in case of TFR. The contribution of generation and utilization of new knowledge is 45 per cent or above in case of the first two indicators and just under 30 per cent in case of TFR.”
Table 2: MDG Goals, Targets and Indicators Linked to Health
|Goal, target, indicator||Nature of indicator||1990||Latest available year||Whether on target|
|G1, T2.14||Percentage of under-weight children under 3 years of age||52%, 1992-93||47%, 1998-99||No|
|G1, T2.15||Percentage of population below minimum level of dietary energy consumption||25%||21%, 2000||No|
|G4, T5.113||Under-five mortality rate[xii]||109.3, 1992-93||94.9, 1998-99||No|
|G4, T5.114||Infant mortality rate||80||64, 2002||No|
|G4, T5.115||Percentage of one-year olds immunized against measles||32.7%, 1992-93||41.7%, 1998-99||No|
|G5, T6.116||Maternal mortality rate[xiii]||424, 1992-93||540, 1998-99||No|
|G5, T6.117||Percentage of births attended by skilled health personnel||34.2%, 1992-93||42.3%, 1998-99||No|
|G6, T7.118||HIV prevalence between 15-24||Not available ||0.98, 2003||-|
|G6, T7.119||Contraceptive prevalence rate, married women 15-49||2.4, 1992-93||3.1, 1998-99||-|
|G6, T7.120||Number of children orphaned by HIV/AIDS||Not available||1.2 million, 2001||-|
|G6, T8.121a||Malaria prevalence rate per 100,000 population||Not available||7||-|
|G6, T8.121b||Malaria death rate per 100,000 children (0-4)||Not available||6||-|
|G6, T8.123a||Tuberculosis prevalence rate per 100,000||Not available||344, 2002||-|
|G6, T8.123b||Tuberculosis death rate per 100,000||Not available||35, 2002||-|
|G6, T8.124a||Percentage ofestimated new smear positive TBcases detected under directlyobserved treatment short course(DOTS) in a year||Not available||31, 2002||-|
|G6, T8.124b||Percentage ofregistered smear positive TBcases successfully treated underdirectly observed treatment shortcourse (DOTS) in a year||Not available||85, 2002||-|
|G7, T9.129||Percentage of population using solid fuel||Not available||72.3, 2001||-|
|G7, T9.130a||Percentage of urban population with sustainable access to improved water source||81.4, 1991||87.06, 2001||Yes|
|G7, T9.130b||Percentage of rural population with sustainable access to improved water source||55.50, 1991||72.39, 2001||Yes|
Section 3: Inter-State and Inter-Regional differences
In discussing Indian health outcomes, one mustn’t lose sight of the fact that there are considerable inter-State and inter-regional differences. There are different ways to look at the economic geography of a country, depending on the administrative division one has in mind. State administrative boundaries are natural dividing lines to use. Academic work and popular impression have often used the BIMARU (Bihar, Madhya Pradesh, Rajasthan, Uttar Pradesh) nomenclature, with a pun on the word bimar, meaning ill or sick. While this is still useful as a starting-off point, the States of Bihar, Madhya Pradesh and Uttar Pradesh have now been sub-divided and Orissa is often worse than some of these 4 traditional BIMARU States. BIMARU thus becomes BIMAROU, not to speak of deprivation, according to some indicators, in Jammu & Kashmir and the North-East. Although undivided Madhya Pradesh and Rajasthan are no longer as deprived and backward as Bihar and the eastern parts of Uttar Pradesh and Uttarakhand is better off than Uttar Pradesh, many of these traditionally backward areas tend to be concentrated in the Hindi-speaking North. Although not directly linked to health, Table 3 illustrates some of these inter-State differences.[xiv] HDI is the human development index based on three indicators of per capita income, education (literacy rate and gross enrolment ratio) and life expectancy, GDI is the gender-based counterpart. If one takes something specific to health, like the infant mortality rate, the differences across States are stark enough. Despite the dated nature of the data, some quotes from the National Human Development Report are indicative, because the issues continue to be relevant. “The national level health attainments hide the large inter and intra-State differences, as well as persisting vulnerabilities of some segments of the population. For some States, indicators on health attainments are comparable with the middle-income countries, and in parts of others mortality levels are as high as in poorest regions of sub-Saharan Africa. The differences across the rural — urban areas and the gender divide, as well as across population segments on caste and class lines are quite striking….. There are significant differences in life expectancy at birth across States. In Kerala, a person at birth is expected to live for over 73 years (70 years for males and 76 years for females), followed by Punjab at 67.4 years (66.4 years for males and 68.4 years for the females). On the other hand, life expectancy at birth in Assam, Bihar, Madhya Pradesh, Orissa, Rajasthan and Uttar Pradesh has been in the range of 55-60 years…. For the major States, IMR varied between 52 per thousand live births for Kerala to 150 per thousand live births in Madhya Pradesh for the year 1981. Among other States, it was well above hundred for Orissa, Rajasthan and Uttar Pradesh. In 1991, the infant mortality declined to 42 in Kerala. A number of States where the IMR was close to 90 in 1981, brought it, down to around 50 per thousand live births. These included Andhra Pradesh, Haryana and Tamil Nadu. It was close to hundred for Uttar Pradesh and continued to be well above hundred for Orissa and Madhya Pradesh…. The underweight children were in the range of 25-35 per cent in some Northern States, namely, Delhi, Haryana, Jammu and Kashmir, Punjab; most of the North-Eastern States; Kerala and Goa. On the other hand, the proportion was nearly 50 per cent or above in Bihar, Madhya Pradesh, Maharashtra, Orissa, Rajasthan, West Bengal and Uttar Pradesh.”
Table 3: Human Development in India
|State/UT||HDI (1991)||HDI (2001)||GDI (1991)||% below poverty line (1999-2000)||Literacy (%), 2001||Infant mortality rate (per thousand), 1991|
|Arunachal Pradesh||0.328|| ||0.776||33.47||54.74||91|
|Himachal Pradesh||0.469|| ||0.858||7.63||75.91||82|
|Jammu & Kashmir||0.402|| ||0.740||3.48||54.46|| |
|Andaman & Nicobar Islands||0.574|| ||0.857||20.99||81.18||69|
|Dadra & Nagar Haveli||0.361|| ||0.832||17.14||60.03||81|
|Daman & Diu||0.544|| ||0.714||4.44||81.09||56|
|Uttaranchal|| || || || ||72.28|| |
|Jharkhand|| || || || ||54.13|| |
|Chhatisgarh|| || || || ||65.12|| |
All health indicators also vary enormously from State to State, and one should not forget that under the Seventh Schedule to the Constitution, health is a State subject. Table 3 has dated data from 1991. But today, the infant mortality rate is 14 in Kerala and 96 in Orissa. The measles immunization coverage (for children between 12 and 23 months) varies between 16% in Bihar and 90% in Tamil Nadu. There are also variations within States. Indeed, the use of State boundaries to facilitate our understanding is itself somewhat flawed, since development and deprivation do not follow such administrative distinctions. However, there is an in-built bias in favour of using States, since data problems are easier to handle then. Data problems become more difficult to overcome if one thinks of India’s regions, or even districts and villages. Of India’s 600 districts, around 100 are truly backward, by any objective criterion. The National Food for Work Programme had a list of 150 backward districts, the Rashtriya Sama Vikas Yojana (RSVY) increased the number to 167 and the National Rural Employment Guarantee Act has a list of 200 backward districts. Most of these backward districts are geographically contiguous. Similarly, out of India’s 600,000 villages, around 125,000 are truly backward. There are 78 regions in the country, as per the NSS (National Sample Survey) classification. Based on these regions, the World Bank identified 18 regions where human development is low – Central Bihar, Vindhya in Madhya Pradesh, Malwa in Madhya Pradesh, South Madhya Pradesh, Northern Madhya Pradesh, South Eastern Rajasthan, Tripura, Western Uttar Pradesh, Eastern Uttar Pradesh, Southern Uttar Pradesh, Jharkhand, Northern Bihar, Central Madhya Pradesh, Southern Orissa, Central Uttar Pradesh, Southern Uttar Pradesh, South Western Madhya Pradesh and Southern Rajasthan.[xv] Since the visual impact is often much more than mere citing of data, two maps now follow, both based on the infant mortality rate, as a surrogate indicator of health outcomes. To drive home the point about intra-State variations, as well as inter-State ones, these maps are based on regions rather than States. And to differentiate between base levels and changes, there are two maps, the first on the base level of the infant mortality rate, the second on changes. The first map shows the infant mortality rate during 1997-99. The darker the shading, the worse the level of the indicator. Barring some deviations, the concentration of the problem in Central and Eastern India, the Hindi heartland so to speak, is obvious enough. The second map, which shows the changes in the infant mortality rate between 1988-92 and 1994-98, reveals a much more complicated picture. There are regions of India where the base level of the infant mortality rate was high, but where declines have also been high. However, on the flip side, there are also other regions, where despite the initial high base levels of the infant mortality rate, declines have not been commensurate. Even within the Central and Eastern belt, one notices variations in improvements. Against the background of these inter-State and inter-regional differences, there are six points that need to be made. First, even among the poor, and especially in urban areas, there is a de facto privatization of health services that is going on, except that because it is de facto rather than de jure, it functions in the absence of any satisfactory and comprehensive regulation. Second, in rural areas, public sector delivery is often the main recourse even now. Third, it is no longer the case, unlike in the 1950s, that physical access is the problem.[xvi] For example, primary health centers ostensibly exist. Fourth, efficiency of public sector health expenditure is the key constraint and this is particularly acute in the backward States and regions mentioned earlier, highlighting a general governance problem. A recent World Bank report states, “Since the pioneering PROBE report on education in five Northern states raised the issue of teachers’ widespread absence and lack of attention to classroom activity, these findings have been replicated nationwide, extended to health, and confirmed over time…. things were even worse in the health sector, as on average 40 per cent of health workers were absent altogether. One recent study in Rajasthan went further and carried out a continuous facility survey in which each of 143 public facilities was visited weekly during regular hours for an entire year. This study replicated the basics of previous findings—finding 45 per cent of doctors absent from Primary Health Centers—but also found that at sub-centers and aid posts the doors were closed 56 per cent of the time (and field visits do not account for this, as only 45 percent of the time could the researcher find the health worker in the village). Worse, the patterns of absences and facility closures were essentially unpredictable, so people could not even count on facilities being open on certain days or at certain times.”[xvii] To compound matters, “Two World Bank researchers have carried out a painstaking evaluation of the quality of medical care in Delhi. They first identified providers by asking people who they went to for care, so that they could generate not an official list of who was registered, but a roster of those from whom people actually sought care. They measured the competence of those medical providers by presenting these providers with meticulously prepared “cases” of five common and important disease conditions—diarrhea, viral pharyngitis, tuberculosis, depression, and preeclampsia—to see if the people providing medical care knew which questions to ask and examinations to make, how to interpret those to make an accurate diagnosis, and how to recommend the appropriate therapy. The findings are shocking. Averaged over all five conditions, a public sector MBBS doctor in a Primary Health Center (PHC) in one of the three poorer neighborhoods had a greater than 50-50 chance of recommending a positively harmful therapy. What is perhaps even more shocking is that a comparison of Delhi with a national random sample in Tanzania and in Indonesia of the equivalent of MBBS doctors shows that (a) the “less than fully qualified” people providing medical care are strikingly incompetent, (b) the typical MBBS doctor in a Primary Health Center (not hospitals) in Delhi is less qualified than the typical provider in Tanzania and substantially less competent than doctors in Indonesia, and (c) even hospital-based public sector MBBS doctors only about reach the Tanzanian level—and are still below that of Indonesia. In treating diarrhea, a basic health problem that 70 per cent of providers report facing “almost every day,” the typical provider recommended a harmful treatment three-quarters of the time. The same study of medical care providers in Delhi also examined practitioners “effort” by direct observation of their actual clinical practice. The striking finding from observing effort was that, while the private, non-MBBS providers were not very competent in practice, they did what they knew, while the public MBBS doctors did not. In the hypothetical vignettes used to measure competence, about 30 per cent of public sector doctors asked the right questions—but less than 10 per cent did so in observed practice. In contrast, private non-MBBS doctors knew to ask the right question only 20 per cent of the time, but achieved that same level in practice. This low effort becomes even more striking when the public doctors in Primary Health Centers in the poorer neighborhoods in the study are examined—there both competence and effort was below even that of non-MBBS doctors—and both were much worse than in rich neighborhoods. The contrast with the private sector is instructive: since private doctors are directly accountable to the patient, they put in effort, although they tend to over-prescribe medicines that are ineffective (at best) simply to please the client. One does not want to extrapolate from a single city, because Delhi’s Primary Health Center doctors might be much better or much worse than in other parts of the country. We don’t know, and that is itself an important fact.”[xviii] Fifth, there is the associated problem of corruption in public service health delivery. Contrary to what one might a priori assume, a recent study found that 27% of petty and retail corruption is due to the health sector, more than the police, taxation and land administration.[xix] Sixth, the demographic dividend, in terms of additions to the labour force and declines in dependency ratios, is going to occur in these backward regions and States. “Five states with 44% of India's population in 1996 will contribute 55% of population growth in the period 1996 to 2016. Performance of these states will determine the year and size of population at which country achieves the replacement level of fertility and later population stabilization.”[xx] These five States are Bihar, Uttar Pradesh, Madhya Pradesh, Rajasthan and Orissa, the first three standing for the undivided States. Population growth is not the same thing as new entrants into the labour force. But because historical birth rates have been higher in these States, new entrants into the labour force will also be concentrated in these States. Projecting from 2001 to 2020, the India Labour Report[xxi] gives annualized labour force growth rates across States and 2.5%-plus growth rates are expected in Assam, Bihar, Delhi, Haryana, Madhya Pradesh, Rajasthan and Uttar Pradesh. Delhi is different because of in-migration. But other than Delhi, the demographic dividend will accrue in States that are backward. And hence the danger of the demographic dividend turning into a demographic deficit. Shankar Acharya states it thus. “Because the BIMARU states are laggards in the demographic transition, they will see the highest relative and absolute expansion in population and labour force between now and 2051. Their share of India’s population will rise from 41 per cent to 48 per cent, since nearly 60 per cent of India’s population increment will be concentrated in these four states. In a nutshell, the ‘demo-div’ of a transitional labour supply bulge will be focused on four populous, poor, slow-growing northern states, with weak infrastructure, education systems and governance. The chances of translating this ‘potential’ of additional labour supply into a ‘reality’ of employment and high growth, appear slim.”[xxii]
Section 4: The Demographic Deficit
There is no automaticity about changes in age-structures of the population, of which a manifestation is the demographic dividend, resulting in increments to real growth rates. “Nations undergoing this transition have an opportunity to capitalize on the demographic dividend offered by the maturing of formerly young populations. The demographic dividend is not, however, automatic. Given the right kind of policy environment, this demographic dividend can help to produce a sustained period of economic growth, as it did in several East Asian economies. The critical policy areas include public health, family planning, education, economic policies that promote labor-market flexibility, openness to trade, and savings.”[xxiii] There can hardly be any quarrel with that statement. A conducive policy environment, improved governance and flexible labour laws are indeed important. Increasingly, in India, the importance of education and skills are also being recognized, there already being a shortage of some high-value skills. In contrast, the importance of improved health outcomes, both in the mortality and morbidity senses, is perhaps less commonly appreciated. There are some estimates that float around, but these are clearly ad hoc with suspect methodologies. “The World Bank recently estimated that the physical toll of malnutrition alone costs the Indian economy 2-3 per cent of GDP per annum. Malnutrition will continue to be a drag on the Indian economy’s potential for many years. UNICEF describes its lack of progress at reducing malnourishment rates as “staggering”. The point I’m trying to make is that unless India makes a dramatic investment in its human capital, its demographic advantages will turn into a demographic disaster in the form of a massive unemployable labour force. Let’s have a quick look at the public health and education systems. Mr Singh’s government is failing to meet its promise of May 2004 to lift health spending to 2-3 per cent of GDP within five years. Spending on public health has plummeted from 1.3 per cent of GDP in 1990 to 0.9 per cent today, and is among the lowest in the world. Absenteeism among health workers is running at about 40 per cent. With free public primary healthcare available in only 21 per cent of villages, the rural poor generally have to borrow to see private quacks. More by default than design, India now has the largest privatized health system in the world, accounting for 80 per cent of treatments. It is a highly inegalitarian system that imposes crippling financial burdens on the poor.”[xxiv] The World Bank doesn’t seem to have any such estimate and certainly, 2 to 3% of GDP per year seems an over-estimate. Notwithstanding this weakness in estimates, the point remains valid. Section 5: The Policy Issue Since India doesn’t perform that well on the health indicators, the demographic dividend can very easily turn into a demographic deficit. And the policy question remains. What can possibly be done to prevent this from happening? There is a large health infrastructure and there are several government programmes, with or without the involvement of the voluntary and private sectors. The National Health Policy (1983), the Drug Policy (1986), the National Nutrition Policy (1993), the National Population Policy (2000), the Revised National Health Policy (2002), the Policy on Indian Systems of Medicine (2002), the Pharmaceutical Policy (2002) and universal health insurance schemes for the poor (2003), all have something to do with health, directly or indirectly. A quote from the National Common Minimum Programme (NCMP), which drives many of the policies of the present government, may be relevant. “The UPA government will raise public spending on health to at least 2-3% of GDP over the next five years with focus on primary health care. A national scheme for health insurance for poor families will be introduced. The UPA will step up public investment in programmes to control all communicable diseases and also provide leadership to the national AIDS control effort. The UPA government will take all steps to ensure availability of life-savings drugs at reasonable prices. Special attention will be paid to the poorer sections in the matter of health care. The feasibility of reviving public sector units set up for the manufacture of critical bulk drugs will be re-examined so as to bring down and keep a check on prices of drugs.”[xxv] This should be spliced with what the National Human Development Report[xxvi] diagnosed as the Indian health-care problem, since the NCMP is only a general statement of intent at a very generic level and no more. “India has a large network of public, voluntary and private health care infrastructure manned by an equally large number of medical personnel and paramedics. Some ailments of India’s health care system includes: Persistent gaps in manpower and infrastructure, with wide inter-Statedifferences, especially at the primary health care level, disproportionately impacting less developed and rural areas; Sub-optimal functioning of the existing infrastructure, poor referral services; Significant proportion of hospitals not having appropriate manpower, diagnostic and therapeutic services and drugs, particularly in public sector; Increasing dual disease burden of communicable and non-communicable diseases because of persisting poverty along with ongoing demographic, lifestyle and environmental transitions; Increased dependence of people on private health care services, often leading to indebtedness in rural areas; Escalating costs of health care, ever widening gaps between what is possible and can be afforded; Technological advances, though, widen the spectrum of possible interventions but are well beyond the financial reach of majority; Inadequate integration of indigenous and alternative system of medicines with the allopathic stream; Inadequate integration of public interventions in the area of drinking water, sanitation, urban waste disposal with public health programmes thereby failing to exploit potential synergies that reinforce health attainments of people; There is, perhaps, a misplaced emphasis on development and maintenance of private health care services at the expense of a broadening and deepening of public health care system targeted, essentially, at controlling the incidence of communicable diseases in rural areas; In case of preventive health care, among the five levels of prevention, namely — health promotion; specific protection; early diagnosis and prompt treatment; disability limitation; and rehabilitation — there is little that has been done by way of strengthening the institutional and delivery mechanism of public policy and programmes, at least, in case of the last two; and Continuation of a universally free public health care system — preventive as well as curative — is unsustainable in its present form. Moreover, there is inadequate policy movement on creating an alternative, accessible, affordable, viable and dependable health care system for majority of the population.” Having diagnosed the nature of the problem, how does one resolve it? If one uses the National Health Policy (2002) to track what the policy intentions are, one arrives at something like the following agenda. (1) Increase public expenditure on health from 0.9% to 2% by 2010; (2) Allocate public health investment in the ratio of 55% for the primary health sector, 35% for the secondary sector and 10% for the tertiary sector; (3) Barring TB, malaria and HIV/AIDS, converge all health programmes under a single administration; (4) For those who can afford to pay, levy user charges for some secondary and tertiary public health services; (4) Impose a mandatory two-year rural posting before awarding graduate medical degrees; (5) Implement health programmes through institutions of local self-government[xxvii]; (6) Set up a Medical Grants Commission to fund new government medical and dental colleges; (7) Increase post-graduate seats in public health and family medicine; (8) Establish a two-tier urban health-care system through a Primary Health Centre (PHC) for population sizes of 100,000 and a public general hospital for larger populations; (9) Increase government-funded health research to 2% of total health expenditure; (10) Allow private sector entry, with legislation to regulate private clinical establishments; (11) Formulate procedures for accreditation of public and private health facilities; (12) Co-opt NGOs in national disease control programmes; (13) Promote tele-medicine; (14) Operationalize a National Disease Surveillance Network; (15) Notify a code of medical ethics through the Medical Council of India; (16) Promote medical services for overseas users; (17) Encourage and promote Indian systems of medicine; and (18) Encourage private sector entry in medical insurance.
[ii] Census 2001 figures.
[v] See, David E. Bloom, David Canning and Jaypee Sevilla, “Economic Growth and the Demographic Transition,” NBER Working Paper 8685, December 2001.
[viii] Millennium Development Goals and Health, WHO and Administrative Staff College of India, 2005
[xi] National Human Development Report 2001, Planning Commission, Government of India, March 2002.
[xiii] There is inconsistency in this figure across Tables 1 and 2, partly because the time periods are different. The sources are also different, though that should not lead to inconsistencies.
[xiv] National Human Development Report 2001, Planning Commission, Government of India, March 2002.
[xv] Attaining the Millennium Development Goals in India: Role of Public Policy & Service Delivery, Human Development Unit, South Asia Region, June 2004.
[xvi] This is the point made in India, Inclusive Growth & Service Delivery,: Building on India’s Success, World Bank, 2006.
[xix] Ibid, citing a Transparency International report.
[xx] National Commission on Population, http://populationcommission.nic.in/facts1.htm
[xxi] India Labour Report, A Ranking of Indian States by their Labour Ecosystem, TeamLease and Indicus Analytics, 2006.
[xxii] Can India growth without Bharat?, Shankar Acharya, Academic Foundation, 2007.
[xxiii] For instance, The Demographic Dividend, A New Perspective on the Economic Consequences of Population Change, David Bloom, David Canning and Jaypee Sevilla, Rand Corporation, 2002.
[xxiv] “Engaging India: Demographic Dividend or Disaster?” Jo Johnson, The Financial Times, 15 November 2006.
[xxvi] National Human Development Report 2001, Planning Commission, Government of India, March 2002.
About the Author
Bibek Debroy (born 25 January, 1954) is an Indian economist, who is currently a Research Professor at the Centre for Policy Research, New Delhi. He was educated at Presidency College, Calcutta,Delhi School of Economics and Trinity College, Cambridge. Prof. Debroy has taught at Presidency College, Calcutta, the Gokhale Institute of Politics and Economics, Indian Institute of Foreign Trade and National Council of Applied Economic Research. His past positions include the Director of the Rajiv Gandhi Institute for Contemporary Studies at Rajiv Gandhi Foundation, Consultant to the Department of Economic Affairs of Finance Ministry (Government of India), Secretary General of PHD Chamber of Commerce and Industry and Director of the project LARGE (Legal Adjustments and Reforms for Globalising the Economy), set up by the Finance Ministry and UNDP for examining legal reforms in India. Between December 2006 and July 2007, he was the rapporteur for implementation in the UN Commission on Legal Empowerment for the Poor. Prof. Debroy has authored several books, papers and popular articles, has been the Consulting Editor of some of the most prominent financial newspapers in the country and is now Contributing Editor with Indian Express. He is a member of the National Manufacturing Competitive Council. He is also a member of the Mont Pelerin Society.