MAPPING HUMAN DEVELOPMENT

- 105 - MAPPING HUMAN DEVELOPMENT 5.1 WORLD SCENARIO People are the real wealth of nations. As Aristotle argued, Wealth is evidently not the good we are seeking, for it is merely useful and for the sake of something else. Dr. Amartya Sen has written, Development can be seen as a process of expanding the real freedoms that people enjoy. The basic objective of development, wrote Mahbub ul Haq in the first Human Development Report in 1990 is to create an enabling environment in which people can enjoy long, healthy and creative lives. Sixteen years on, that vision retains a powerful resonance. World map indicating Human Development Index (2006) Fig-9 High (0.800 1.000) 0.950 and over 0.900-0.949 0.850-0.899 0.800-0.849 0.750-0.799 Medium (0.500 0.799) 0.700-0.749 0.650-0.699 0.600-0.649 0.550-0.599 0.500-0.549 Low (0.300 0.499) 0.450-0.499 0.400-0.449 0.350-0.399 0.300-0.349 under 0.300 The world is a divided lot by nature into five continents. It is divided based on various other clarifications as well. There are 63 High human development

- 106 - countries having HDI 0.800 and above, where as majority of 83 countries fall between 0.500 0.799 medium human development category (Fig-9). Then 31 states are low human development countries holding HDI value below 0.500 excluding 17 states where HDI couldn t be captured. When it comes to income criteria (GNI/capita) then world s 41 countries are in high-income bracket ($10065 or more). People living in 93 countries have GNI/capita $826 - $10065 that is middle income group, where as 59 countries qualify for low-income award of $ 825 or less. (Annexure H ) The same world is again divided on the lines of high Income, OECD countries, CIS, developing countries and 50 least development countries. Last but not the least for political, economical, development and academic purpose the earth is classified into six regions, 20 Arab states, 28 East Asia and Pacific which includes China. India is among 9 states of South Asia. Then world has 33 countries in Latin America and Caribbean, 2 in South Europe and 45 in Sub Sahara Africa. 5.1.1 One World Different HDIs The HD trends are upward but uneven. Since the mid-1970s almost all regions have been progressively increasing their HDI score. CIS following a catastrophic decline in the first half of the 1990s have also recovered strongly (Graph-7). The major exception is Sub-Saharan Africa. Graph-7

- 107 - Eighteen countries have a lower HDI score today than in 1990 most of these are in Sub-Saharan Africa. 28 of the 31 low human development countries are in Sub- Saharan Africa. (Graph-7) (Source: UNDP, HDR 2006) In 1975, 6.26% of world population was tagged as having lowest HDI, today it has increased to 8.95% and worst, in 2015 10.21% people will have HDI less than Table-1 Region/Group HDI High Human Development 0.923 Medium Human Development (Including India) 0.701 Low Human Development 0.427 High income 0.942 Middle income 0.768 Low income(including India) 0.556 0.500. Similarly in 45 years 2.04% more people will be in medium HDI group than in 1975 (Table-1&2). Measured on income scale, in 2015 about 5% people will move out of high income bracket, where as about 4% more population will be in middle income group. Maximum change will be in lower income club where from 30.37% in Table-2 Region/Group HDI 1975, the number of people will jump to 39.56% in 2015. Within high HDI the income poverty levels have also wide variation. The Graph-8 of 17 countries shows for near same HDI of 0.942 to 0.913, HPI-2 varies from as low as 6.8 for Sweden to 15.8 for UK. World 0.741 Developing countries (Including India) 0.679 Least Developed Countries 0.464 Arab states 0.680 East Asia and the Pacific 0.760 Latin America and the Caribbean 0.795 South Asia (Including India) 0.599 Sub-Saharan Africa 0.472 Central & Eastern Europe & CIS 0.802 OECD 0.923 European Union N/A

- 108 - Graph-8 (Source: HDR 2002) 5.1.2 Poverty vs. HD Income poverty has fallen in all regions since1990, except in Sub-Saharan Africa. The share of the world s people living on less than $1 a day has fallen from 28% to 21%. Still global economy reflects the extreme disparities in wealth and the small shares of world income captured by the poor. Nine of 10 people in high-income (OECD) countries are in the top 20% of the global income distribution. At the other end of the scale one person in two in Sub-Sahara Africa is in the poorest 20%. Average income for the world as a Graph-9 whole, is $5533 (PPP) but 80% of the world lives on less than this average. The world s 500 richest people have an income of more than $100 billion, not taking into account asset wealth. That exceeds the combined incomes of the poorest 416 million. (Graph-9, 10 & 11)

- 109 - Graph-10 Graph-11 Income distribution patterns directly affect opportunities for nutrition, health and education. The HDI by income group points to stark inequalities in human development. Children born into the poorest 20% countries as per income distribution, such as Bolivia, Indonesia and South Africa face a risk of dying before their fifth birthday. Both girls and boys in the poorest 20% of the income distribution in Burkina Faso are far less likely to live counterparts, though the disparity between girls and boys are equally marked. Reasonable high disparity in HDI exist with in all countries with respect to the income/poverty level is clear from Graph-12. For US the HDI is highest but varies from Graph-12 approx 0.83 to 0.9. The dispersion is highest in South Africa and Bollvia where average HDI of 0.7 is shared by more number of poor people. The Gini coefficient, a measure of inequality calibrated on a scale from 0

- 110 - (perfect equality) to 100 (perfect inequality), ranges from 33 in South Asia to 57 in Latin America and to more than 70 in Sub-Saharan Africa. There is no automatic link between HDI and poverty. This can be seen by looking at the distribution of HD achievements with in countries and HPI. For example Tanzania and Uganda are having similar HDI ranking (140 & 141) but Uganda has much higher human poverty (Fig-10). (Source: HDR 2002) Fig-10 5.1.3 GDP vs. HDI Many scholars have argued that Economic Growth (EG) is main engine and have shown relation between HD and EG. Then, there is a need to explain the wide Fig-11 difference in HDI for same GDP.

- 111 - Jamaica and Morocco are both high HDI and GDP countries but for near same GDP they have HDI of 0.724 and 0.640 (Fig-11).A simple look at their Life Expectancy Index (LEI), Education Index (EI) and GDP Index (GDPI) clearly shows that it is the education level in Morocco, which has pulled down its HD. (Source: HDR 2005) Similarly some other cases can also be analysed which are summarised below:- Case I: - Case II: - HDI LEI EI GDPI HDI LEI EI GDPI Jamaica.724.76.79.62 Vietnam.709.76.83.60 Morocco.640.75.54.63 Pakistan.539.64.46.57 Case III: - Case IV: - Philippines.763.76.89.64 Botswana.570.16.78.77 Thailand.784.75.86.73 Swaziland.500.10.72.67 Phenomenon of wide disparity in GDP for similar HDI exists in all income levels. As per HDI calculation of 2004 published in HDR 2006, widely different GDPs in a high-income group (US $ 10,000 to 22000 at PPP) converge to same HDI (Chile, Bahrain). It is true for UAE and Czech Republic also (Fig-12). Even in middle income or low income groups Namibia / Egypt or Angola / Tanzania clearly defy any linkage between HDI and GDP. Perhaps the answer for this is somewhere else, Education Index (refer case study above). Fig-12

- 112 - Fig-12 (Source: UNDP, HDR 2006) Human Development and Economic Growth: The first HDR stated, The basic objective of development is to create an enabling environment for people to enjoy long, healthy and creative lives. EG, long considered as the ultimate objective, should instead be viewed as a necessary instrument for the achievement of advances in HD. In order to achieve human development progress, and as the global HDR 1996 argues, the quality of growth matters, or else the following policy failures may occur:- Jobless growth: That does not expand the opportunities for employment Graph-13

- 113 - Ruthless growth: Voiceless growth: The fruits of growth mostly benefit the rich Growth has not been accompanied by expansion of democracy, empowerment Rootless growth: Futureless growth: Causes people s cultural identity to wither Where present generations squander resources needed by future generations. There clearly exist strong two-way connections between EG and HD. On the one hand, EG provides the resources to permit sustained improvements in HD. On the other, improvements in the level of education and health, key ingredients of HD, are an important contributor to EG. One-way of classifying countries into these four categories is to compare their performance on HD and EG (1960-2001) with the average performance of all developing countries (Graph-13). Most developing countries appear on either virtuous (NE quadrant) or vicious (SW quadrant), a significant number show on HD-lopsided pattern and only one on EG-lopsided one. A strong regional pattern emerges, with East Asia heavily represented in the virtuous cycle and sub-saharan Africa in the vicious cycle quadrant. Latin America is heavily represented in the HD-lopsided quadrant. (Source: Causal Chain between HD EG, Gustav Ranis, Department of Economics, Yale University, Mar 2007) 5.1.4 Gender Bias Gender is one of the world s strongest factor for disadvantage. This is especially the case in South Asia. The large number of missing women in the region bears testimony to the scale of the problem. Disadvantage starts at birth. In India the

- 114 - death rate for children ages 1-5 is 50% higher for girls than for boys. Expressed differently, 130000 young lives are lost each year because of the disadvantage associated with being born with two X chromosomes. Women are the primary breadwinners in many economies, which include 3 billion of the world's 6.5 billion people. Research shows that they work longer hours and devote a larger share of their earnings to support their families than men do. Yet women's efforts to support their children are all too often stymied. Gender bias ranges from wage discrimination, to exclusion from development programs, to legal barriers to owning land, to systemic violence against women. This discrimination aggravate poverty by preventing hundreds of millions of women from obtaining the credit, education, training, health services, child care, and legal status needed to improve their prospects. As a result, not only do families remain poor, but the economies of many Third World Nations lag far below their economic potential. Rising female literacy rates are directly linked to declines in births. But girls and women are less likely to attend school than boys and men. While overall literacy rates rose between 1970 and 1985, the gender gap in literacy actually widened. The number of women unable to read rose by 54 million, illiterate males increased 4 million. Today, the gap continues to grow. In sub-saharan Africa, women grow 80 percent of the food destined for their kitchen tables. Women's labour produces 70 to 80 percent of food crops grown on the Indian subcontinent, and 50 percent of the food domestically consumed in Latin America. In addition to food production, women are responsible for gathering fuel and water. Yet conventional development strategies grant males disproportionate access to land, credit, and farm machinery,

- 115 - and deliver education and training primarily to boys and men. Development strategies typically exclude women except as targets for population control. A 1982 study, for example, estimated that only 0.5 percent of all UN allocations to agriculture went to programs for rural women. Men are more likely to earn cash income than women, but are less likely to spend their earnings on family maintenance like food, shelter, clothes, health care and therefore less likely to pull their families out of poverty. Research shows in Mexico that women contribute 100 percent of their earnings to the family budget, while men contribute at most 75 percent of theirs, and often less. Women effectively provide the largest share of the family's basic needs while the incomes of men often are siphoned off by the purchase of alcohol, tobacco, or other consumer products. Studies from throughout the developing world show that the mother's income or food production and the degree of control she maintains over that income determine the relative nutrition of children. Unfortunately, over the last decade the status of women has actually declined they have less control than ever before over their land, cash and other resources. As a result, all over the developing world, women find themselves working longer hours to make ends meet. The increased workload ensures that birth rates stay high since women depend on children particularly girls to lend a hand. (Source: Jodi L. Jacobson, Gender Bias: Roadblock to Sustainable Development, World Watch Institute) Inequities, driven by overwhelming poverty, affect both male and female children in the developing world. Yet cultural traditions, scant economic resources and limited opportunities marginalise young girls. Young boys have better access to health care,

- 116 - nutrition and education. Gender bias is reinforced throughout adulthood as men retain economic and political power. Few countries guarantee women equal rights within marriage, divorce and family property. Governments and nongovernmental organizations must continue social and political efforts to ensure gender equality, provide better opportunities for, and facilitate the education of young women. Male Preference Starts before Birth: In South Korea, nearly 80,000 female foetuses were aborted from 1986 to 1990, about 5% of all female births. In China, the number of male births per 100 female births had increased from 108.0 in late 1986 to 109.7 in 1991. A study in rural Punjab revealed that between the age of one and 23 months, female mortality rates are nearly twice those of males. Girls born to mothers who already have one or more surviving daughters experience 53% higher mortality. The same study revealed that although both sexes receive the same number of calories, girls are given more cereals, while boys receive more highly valued milk and fats. For sons, expenditure on medical care in the first two critical years of life is more than two times higher than for daughters. Economic, Political and Legal Policies Perpetuate Lower Status of Women: In Java, girls spend 33 to 85% more hours per day working at home and in the market as compared to boys of the same age. Most of women's time is spent in the non-wage economy, creating a social misperception that women's work

- 117 - has no economic value. In parts of East Africa, women work up to 16 hours a day in the home, and grow 60 to 80% of the family's food. In rural Punjab, less than 1% of girls aged 10 to 14 yrs earn wages, compared to 4 % boys of the same age. Three percent of women aged 15 to 39 earn salaries or are self-employed compared to 41% of men. Dowry murder is commonly practiced in India to free men from their current wives to arrange a more profitable marriage. Women are set on fire and then reported to have died accidentally. In 1990, the police recorded 4,835 dowry deaths, although this is thought to be an underestimate. In both urban Maharashtra and greater Bombay, one of every five deaths among women aged 15 to 44 is due to "accidental burns." For the younger age group 15 to 24, the proportion is one in four deaths. Young Women Face Educational Inequities: Of the nearly one billion illiterate adults, two-thirds are women living in South Asia, sub-saharan Africa and the Middle East. In more than 29 countries, less than 30% of women are literate. Younger girls and boys are likely to have similar primary school enrollment rates. By age 16, fewer girls then boys are in school in nearly every country in sub-saharan Africa, Asia and the near East. In Yemen, only 14% of 16-20 yrs age girls attend school compared to 61% of their male peers. Female literacy in Pakistan improves about 5% per decade, at this rate it will take 60 years to raise the literacy rate of teenage women age 15-19 to 70%.

- 118-5.1.5 Infant Mortality The improvement and set back to Infant Mortality Rate (IMR) globally in last century is very clear from above (Fig-13). In year 2000, world IMR was 56/1000 live births. This has been reduced to 51 in 2004. The changes however are significant in many regions as can be seen from Table-3, which is self-explanatory and thought provoking. Fig-13 Countries Table -3 2000 2001 Developing Countries 61 57 LDC 98 94 Arab States 46 38 East Asia & Pacific 33 28 Latin America & Caribbean 30 26 South Asia (Includ ing India)68 62 Sub Sahara Africa 107 103 H HDI countries 07 09 M HDI countries 46 45 L HDI countries 99 106 High Income countries 06 06 Fig-14

- 119 - Medium Income countries 31 27 Low Income countries 80 77 Under-Five Mortality: Survival rates for children are among the most sensitive indicators of human well-being. There were 2.1 million fewer deaths in 2004 than in 1990. Survival prospects are improving in all regions. Child death rates in all developing regions are rising when expressed as a multiple of the rate in highincome countries (Graph-14). Perhaps more powerfully than any other indicator, child mortality demonstrates that increases in income are not equivalent to improvements in HD. (Source: UNDP, HDR 2006) Graph-14 5.1.6 Life Expectancy Global snap shots at different periods (Fig-15) clearly reflect improving LE over regions. However even at turn of century wide difference of LE (<45 to >75) is clearly visible marked by different shades of colours (Fig-15).

- 120 - Fig-15 HDRs launched in 1990 gives clear statistical figures on LE that is testimony of world wide efforts on this account. However continuous drop in Sub Sahara Africa and drastic dip in Low HDI countries is a matter of concern (Table-4). Countries 1995-00 Table-4 2000-04 Developing Countri es 64.1 64.9 LDC 51.3 52.0 Arab States 65.9 66.9 East Asia & Pacific 68.8 70.4 Latin America & Caribbe an 69.4 71.7 South Asia (Including India) 61.9 63.2 Sub Sahara Africa 48.8---------? ----> 46.1 H HDI countries 77.0 77.8 M HDI countries 66.5 66.9 L HDI countries 52.2---------? ----> 45.6 High Income countries 77.8 78.6 Medium Income countries 69.2 70.0 Low Income countries 59.0---------? -----> 58.3 World 66.4 67.0 LE gaps are closing but there are exceptions. Over the past three decades developing countries average LE at birth has increased by nine years, compared with Graph-15 seven in high-income countries.

- 121 - The exception again is Sub-Saharan Africa (Graph-15). For the region as whole LE today is lower than it was three decad es ago. (Source: UNDP, HDR 2006) 5.1.7 World Literacy Fig-16 It takes a major effort for a country to educate its populace. A country needs a large pool of the already educated to act as teachers, and an economy that can detach children from the workforce long enough for them to go to school. By comparing the maps with others (Fig-16), it becomes apparent that the countries, which made this commitment early, have dominated the century. By 1900, most of the industrialised countries had instituted free, compulsory education for all children. The rest of the world relied on private tutors and academies for the rich, with mixed results. Progress in education is critical for HD in its own right and because of the links to health, equity and empowerment. Since 1990 adult literacy rates have risen from

- 122-75% to 82%. Women still account for about two-thirds of adult illiteracy, same as in the 1990s (Fig-17). The core challenges to be addressed are the enrolmentcompletion gap, low rates of transition to secondary school & beyond and high levels of post-primary gender inequality. Fig-17 Gender discrimination tracks girls through education in some countries (Source UNDP, HDR 2006) 5.1.8 Happiness/Well Being and HD Link between HD and Happy as well as satisfied life as a whole was analysed (R Irglehat, 1997), using Gross National Product (GNP)/capita as proxy of Graph-16 HD. The resultant graph is

- 123 - interesting, showing clear vertical growth in happiness state for low GNP/capita among many countries (Graph-16). For nearly same GNP / capita many countries reflect widely different happiness state for example Maldives, Ukraine, Georgia, India, Bangladesh and Nigeria. There are similar other vertical axis s reflecting similar observations. From 70 to 80 score on Y-axis we find reverse phenomenon where by for similar level of happiness/ satisfaction with life the GNP/capita varies from 1100 to 15000. Another clear X-axis like this appears between 85 and 95 level of happiness covering some of high HDI countries. The normalised average graph of these plots shows that the main boaster beyond the level of 80 on happiness scale is EG. If HD can be defined to attain a happiness and satisfied state of life with in the concept of providing and developing opportunities and capabilities then the study needs further exploration. Cultural differences can be relatively enduring, but not immutable so as to show cross-national differences in satisfaction with one's life as a whole. (Source: R. Inglehart, Modernization and Post Modernization, Princeton, 1997). Subjective Well-being and Democratic Institutions: An attempt to find correlation between happiness as indicator of subjective well being and sum of freedom house rating as representative of democratic institutions was made. Vertical axis is the sum of the Freedom House ratings for Civil Liberties Graph-17

- 124 - and Political Rights, from 1981 through 1998. Horizontal axis reflects each public's mean factor score on happiness and overall life satisfaction and subjective wellbeing. It again shows many X-axis/Y-axis phenomena, calling for further detailed investigation. However the average graph shows that as freedom/democratic setup improves the subjective well-being improves slowly at initial stage. Between freedom rating of approximate 80 to 140 the curve moves upward prominently before reaching a Plato region of 185 to 200. This is a definitive indicator to support democracy for overall well-being and HD. (Source: R.Inglehart and Klingemann, "Genes, Culture and Happiness" MIT) 5.1.9 Regional Disparities From above discussions it is quite clear that the world is not Graph-18 same everywhere. HDI not only varies, improving from South Asia to High Income OECD countries as shown in Graph-18 but the improvement over period of time is also different. During 20 years of depicted period the best growth was in East & South Asia followed by Arab states & Latin America. The 1990-95 was the retarding factor setback in CIS/Central & Eastern Europe from Graph-19 on its two decade of HDI growth. Adult literacy rate for

- 125 - last quarter of century follows a similar pattern. However change in literacy rate in Sub Sahara Africa and Arab States is significant (Graph-19). It is important to see that in spite of such large improvement across the board including South & East Asia and Low HDI countries, the HDI has not kept pace especially in case of Sub Sahara Africa. Under five mortality rate has decreased all over world from Graph-20 1970 2000, but with varied degree. The Graph-20 shows best result in case of Arab states followed by South Asia and East Asia. Marginal decrease in CIS and OECD countries is because of already quite low IMR and practical impossibility in touching zero. A look at progress of LE at birth raises two observations (Graph- 21). One reversal of it is in Sub Graph-21 Sahara Africa as well as in CIS/Central Eastern Europe. Two Arab states taking a lead as in other areas like literacy and IMR. However much needs to be done to reduce the gap in LEB of 45 in LHDI states and 77 in OECD countries. (Source: HDR 2002) 5.2 HDI IN INDIA

- 126 - India Human Development Statistics: It has been repeatedly claimed that India has been a pioneer in development of national statistical systems among developing countries. However data on HD indicators highlights the persistence of disparities and diversities across regions, gender and social groups. The census does provide a wealth of information very useful with the National Sample Survey Reports. The Sample Registration System complements other sources of information. The preparation of National and State HDRs in India has helped to highlight the need for more disaggregated data. These HDRs database has been formatted in a user friendly way and the reports provide statistical appendixes and in some cases a profile for each district. All such database provides information on HDI across states. Fact sheets provide essential information on demography, income, education, health and environment (Annexure I ). 5.2.1 Indian Formula of HDI The HDI is a summary measure of HD. It measures the average achievements of a State in three basic dimensions of HD. The NHDR uses different indicators in computation of HDI as compared to the UNDP indicators. Dimension Indicators (Weight) Health Life expectancy at age one (0.65) Infant Mortality Rate (0.35) Education Literacy rate for the age group 7 years and above (0.35) Adjusted intensity of formal education (0.65) Command over Inflation and inequality adjusted per capita consumption resources expenditure.

- 127 - Notes: (a) Intensity of formal education has been estimated as the weighted average of the enrolled students from Class I to Class XII (where weights being 1 for class 1, 2 for class 2 and so on) to the total enrolment in Classes I to classes XII), (b) Monthly per capita consumption has been adjusted for inequality using estimated Gini Ratios. This average per capita monthly expenditure for 1993-94 and 1999-2000 has been adjusted for inflation to bring them to 1983 prices, using deflators derived from state specific poverty lines. Table-5 Before the HDI itself is calculated, an index needs to be created for each of these dimensions. To calculate these dim ension indices, minimum and maximum values ( goalposts) are chosen for each underlying indicator. The Goalposts for calculating the HDI are the following:- Indicator Maximum Minimum value value Life expectancy at birth age one (yrs) 80 50 Infant Mortality Rate (per 1000) - 20 Literacy Rate for 7 + years 100 0 Adjusted intensity of formal education (estimated) yrs. 7 0 Consumption Expenditure (per capita per month) Rs. 325 65 Source: Planning Commission, NHDR 2001, GoI, New Delhi Table-6 Performance in each dimension is expressed as a value between 0 and 1 applying the following general formula: Dimension Index = [actual value - m inimum value] / [maximum value - minimum valu e]. The HDI is then calcul ated as a simple average of th e dimensi on indices. 5. 2.2 India s Score (Last 30 Years) Region/Country 1975 1980 1985 1990 1995 2000 2004 1 Afghanistan X X X X X X X 2 Bangladesh 0.347 0.366.0391 0.422 0.454 0.510 0.530 3 Bhutan X X X X X X 0.538 4 India Table-7 0.413 0.439 0.477 0.515 0.548 0.577 0.611 5 Iran 0.567 0.571 0.612 0.651 0.695 0.723 0.746 6 Maldives X X X X X X 0.739 7 Nepal 0.299 0.336 0.378 0.425 0.467 0.500 0.527 8 Pakistan 0.365 0.388 0.420 0.463 0.493 0.511 0.539

- 128-9 Sri Lanka 0.612 0.653 0.684 0.706 0.729 0.747 0.755 Trend in South Asia and India s score in terms of HDI is at Table 7. It is noteworthy that Sri Lanka and Iran both non-democratic states are ahead of India. Countries like Bangladesh and Bhutan are not far behind. Growth of Nepal from 0.30 to 5.2 is definitely impressive. Fig-18

- 129 - NHDR 2001 depicts three measurements of HD that is HDI, HPI and GEI for year 1981 and 1991 (Fig-18). These pictures show that number of states having HDI less than 0.315 reduced from 10 to 1 during above period. As far as poverty is concerned in 1991 Bihar was the only state having HPI more then 50. For GEI once again Bihar is at the bottom of index. 5.2.3 State HDRs In India, due to the social and economic diversity amongst Indian States, and as mandated by the Indian Constitution, the responsibility for implementing social sector programmes rest with the State Governments. India has the distinction of having the first sub national SHDR for the state of Madhya Pradesh in 1995. Since then, the State has published its SHDRs twice in 1998 and 2002. Sixteen other States of Assam, Arunachal Pradesh, Delhi, Tamil Nadu, Himachal Pradesh, Karnataka, Sikkim, Maharashtra, Rajasthan, West Bengal, Punjab, Nagaland, Orissa, Gujarat, Chhattisgarh and Kerala have launched their SHDRs. Reports for 5 other States are at various stages of preparation. These reports, owned by the government and prepared by independent experts, serve as platforms for public accountability and action.

- 130 - The Planning Commission, Government of India in collaboration with HDRC, UNDP, supports the preparation of SHDRs in India. The SHDRs focus on issues related to Poverty, Livelihoods, Health and Education. The SHDRs helps to:- Translate the concept of human development into policy-oriented action. Create awareness among national and local policy makers about tools and techniques to translate HDR analyses into policies and programmes. Facilitate learning and exchange of ideas by strengthening regional and local networks and capacity building. 5.2.4 State HDI Formulas The Planning Commission, Government of India has been estimating the Head Count Ratio of the poor at State level, separately for rural and urban areas for over three decades. It currently uses a minimum consumption expenditure, anchored in an average (food) energy adequacy norm of 2400 and 2100 kilo calories per capita per day to define State specific poverty lines, separately for rural and urban areas. These poverty lines are then applied on the NSSO s household consumer expenditure distributions to estimate the proportion and number of poors at State level. The Census of India currently defines the literacy rate as proportion of literates to total population in age group 7 years and above. The adult literacy rate, in India is defined as the proportion of literate population in age group 15 years and above. Besides the more commonly used life expectancy at birth, in many reports life expectancy has been taken at age one. All Indian states use different formulas modifying both UNDP as well as Planning Commission methodology. Many states use IMR for LEB where as few others

- 131 - depended on mortality rate at 1 year/ 5 years age. Literacy index is also based on different parameter for example Orissa used 6-14 years of age where as many states used above 7 years criteria. Few states even limited it up to class 10 th only. GDP Index showed maximum differences in methodology and parameters. Many states followed Net District Domestic Product (DDP)/Capita as base while many used it in combination with consumption/capita and percentage of population above state poverty line. HP is its 2002 HDR didn t applied log of DDP as per Atkinson s formula. These deviations have been justified by some states but in absence of common datum and method, cross comparison is main difficulty. The district wise HDI and the gender related development index in MP HDR2002 report changed both, the data it uses and the methodology. The districts HDIs in the three MP reports are therefore not strictly comparable. 5.2.5 State HDIs HDI values in various HDRs published by different SHDRs provide interesting but conflicting figures. Table-9 gives the value of HDI as worked out by the SHDRs and NHDR-2001 published by planning commission. Similar picture showing gaps and differences appea r when HPI, Literacy, LEB or Net Dome stic Product/capita is compared for same year from different sources (Table-10). The overall picture is confusing and can be cleared only if one datum and formula comparable with UNDP is applied across all states in India. (Source: Karnataka H DR 1999)

- 132 - Table-8 States SHDR NHDR Delhi - Kerala.773 (2000).638 AP.515 (2001).515 Chhatisgarh.971 (2001) West Bengal.610 (2001).472 Orissa.579 (2001).404 Nagaland.623 (2001) Gujarat.565 (2001).479 Punjab.537 (2001) Assam.407 (2001).386 Tamil Nadu.657 (2001).531 Maharashtra.580 (2000) HP.433 MP -.394 Rajasthan -.424 Sikkim.532 (1998) Karnataka.470 (1999) Table-9 Table-10

- 133-5.2.6 Anomalies - HDI Calculations in India The correct and accurate measurement of HDI is important not only for India but also for its states to see the past present and future. Only right HDI scores can help in identifying the effects of past Table-11 and current policy / programme implementation and need for course correction to attain the object ives and goals in a defined time frame. Study of HDI formula ( Table-11), calculation from state level to international level has shown many serious deviations without any good reasons. Follow ing is the summary of differences between three levels of HDI (Table12). ATTRIBUTES UNDP Life Measured as Expectancy relative achievements in life expectancy. At birth with goal post as min 25yrs & max 85yrs LEI=(Le-25)/(85-25) INDIA (MP) It is weighted sum Life of life expectancy. expectancy At Age 1 and infant at birth & mortality rate. IMR with LEI=0.65Le(1)+0.35 same IMR weights as For Le (1) goal posts National are min 50 yrs and formula. But max 80 yrs. For IMR min is 20 per 1000. goal posts are 85yrs & 25yrs. (RAJ) Same as MP

- 134 - Knowledge Adult (>15yrs Education index is Percentage Percentage age) literary rate literacy rate for the share of all share of all (2/3 weight) and age above 7yrs literate over literate combined (35% weights) & the total over the primary, adjusted intensity of population total secondary & formal education above 6 yrs population tertiary gross (65% weight). Goal of age (2/3 above 6 yrs enrolment ratio posts for former are weights) of age (2/3 (1/3 weight). Goal 0 & 100 and for posts are min 0 & later it is 0 & 7. max 100 and children weights) in age group 6-14yrs enrolled in school ( 1/3 weights). Standard of GDP/capita (PPP Inflation and Average of Per capita living US $). Log values Inequality adjusted various income of GDP/Capita is used with goal consumption expenditure per distinct domestic adjuste d by distribution posts as min 100$ capita per month. products and poverty & max 40000$. Min as Rs 65 & max calculated levels. Table-12 Rs 325. under 16 categories with numerous da ta gaps. HDI 1/3(LEI+EI+GDP) Same Same Same Another unexplained issue is different HDI figures published in s tate HDRs, Planning commission report and NHDR. For example HDI va lues of India based on selected 15 states as per NHDR-2001 are 0.302, 0.381, and 0.472 for 1981, 91 and 2001 respectively. For same year and same 15 states average wor ks out to be 0.328, 0.403, and 0.463 as per Planning commission reports, where as the UNDP reports these to be 0.445, 0.522, and 0. 588.(Table-13, 14 &15)

- 135 - Table-13 Reference 1981 1991 2001 UNDP s (HDI-India) 0.445 0.522 0.588 INDIA s (HDI-India) 0.302 0.381 0.472 Indian States Ave HDI Table-15 0. 328 0.403 0.463 Reference 1981 1991 2001 1 AP 0.298 0.377 0.416 2 Ar. Pradesh 0.328 3 Assam 0.272 0.348 0.386 4 Bihar 0.237 0.308 0.367 5 Gujarat 0.360 0.431 0.479 6 J& Kr 0.402 7 Kerala 0.500 0.591 0.638 8 MP 0.245 0.328 0.394 9 Manipur 0.536 10 Meghalaya 0.365 11 Mizoram 0.548 12 Nagaland 0.486 13 Orissa 0.267 0.345 0.404 14 Rajasthan 0.256 0.347 0.424 15 Sikkim 0.425 16 Tamil Nadu 0.343 0.466 0.531 17 Tripura 0.389 18 Uttar Pradesh 0.255 0.314 0.388 19 West Bengal 0.305 0.404 0.472 20 Haryana 0.360 0.443 0.509 21 Karnataka 0.412 0.412 0.478 22 Maharashtra 0.363 0.452 0.523 23 Punjab 0.411 0.475 0.537 15 States Ave HDI Table-14 0.321 0.403 0.463 0.414 The variation in HDI values am ong three levels (st ates, India, UNDP) from 19 81 to 2 001 is very c lear from Gra ph-22. 0.700 0.600 0.500 0.400 0.300 0.200 0.100 0.000 Graph-22 1975 1980 1981 1985 1990 1991 1995 2000 2001 2005 UNDP HDI India HDI States Ave HDI

- 136 - The NHDR that has been produced under the auspices of the Planning Commission uses data widely differing in their level of reliability without always signposting the huge margins of error and non-comparability among States caused by the differences in the provenance of data and margins of error involved. (Source: Defining HD, Amiya Kumar Bagchi, Frontline, Nov 2002) Error I: India HDI as base E (1981) = Error II:UNDP HDI as base E (1981) = Error III: UNDP HDI as base E (1981) = India HDI-Ave States HDI UNDP HDI - India HDI UNDP HDI - Ave States HDI = 0.302-0.321 = -0.019 (-6.3%) = 0.445-0.302 = 0.143 (32.1%) = 0.445-0.328 = 0.117 (26.3%) E (1991) = E (1991) = E (1991) = India HDI-Ave States HDI UNDP HDI-India HDI UNDP HDI- Ave States HDI = 0.381-0.403 = -0.022 (-5.8%) = 0.522-0.381 = 0.141 (27.0%) = 0.522-0.403 = 0.119 (22.8%) E (2001) = E (2001) = E (2001) = India HDI-Ave States HDI UNDP HDI-India HDI UNDP HDI- Ave States HDI = 0.472-0.463 = 0.009 (1.9%) = 0.588-0.472 = 0.116 (19.7%) = 0.588-0.463 = 0.125 (21.2%) Table-16 These differences give rise to three levels of errors as calculated and shown in Table 16. The maximum deviation for three years 1981, 91 and 2001 appears to be 32.1%, 27.0%, and 21.2%. In other words India s HDI should be this much percent less from UNDP figures. On applying the extrapolated decreasing value of the deviation to 2004 value (HDR-2006), Indian HDI should be [0.611- (0.611*19.25) = 0.439] placing it at 150 th rank instead of 126 th out of 177 countries. 5.2.7 Indian Human Development Goals 2000-2010 10 th Five Year Plan: Officially India s development goals and targets were framework. It officially aimed to adopt a well-knit strategy so that the various crossarticulated in the Tenth Five Year Plan (TFYP) 2002-2007, which is within the HD

- 137 - linkages that exist within the set of social and economic indicators can operate in a synergistic manner in order to attain the ultimate objective of all initiatives namely HD. In the TFYP the Planning Commission had outlined India s HD goals and targets for the next five years. Most of these are related to and are more ambitious than the MDGs. Monitor able targets for the tenth plan and beyond are:- Reduction of poverty ratio by 5 % points by 2007 and by 15 % points by 2012. Providing gainful and high-quality employment to the addition to the Labour force. All children in school by 2003, all children to complete 5 years of schooling by 2007. Reduction in gender gaps in literacy and wage rates by at least 50 % by 2007. Reduction in the decadal rate of population growth between 2001 and 2011 to 16.2 %. Increase in Literacy Rates to 75 % within the Tenth Plan period (2002-3 to 2006-7). Reduction of IMR to 45 per 1000 live births by 2007 and to 28 by 2012. Reduction of MMR to 2 per 1000 live births by 2007 and to 1 by 2012. Increase in forest and tree cover to 25 % by 2007 and 33 % by 2012. All villages to have sustained access to potable drinking water within the Plan period. Cleaning of all major polluted rivers by 2007 and other notified stretches by 2012. HIV/AIDS targets within the Tenth Plan period. Malaria targets are 25% reduction mortality due to malaria by 2007 and 50% by 2010. The Tenth Plan aimed to achieve an 8 % growth rate within the plan period 2003-2007. It is reasonable to expect that unless there are unforeseen circumstances, the overall GDP growth is likely to be higher at around 8.5 per cent with a continued upward bias. (Source: Tenth Five Year Plan, Planning Commission, GoI) 11 th Five Year Plan: The 11th Plan provides an opportunity to restructure policies to achieve a new vision of growth that will be much more broad based and

- 138 - inclusive. The steps must be further strengthened and consolidated into a strategy for the 11th Plan. Rapid growth has to be an essential part of the strategy. The economy can grow between 8% and 9% per year on a sustained basis provided appropriate policies are put in place. With population growing at 1.5% per year, this would ensure that the real income of the average Indian would double in ten years. This must be accompanied by a major effort to provide access to basic facilities such as health, education, clean drinking water etc. The 11th Plan must pay special attention to the needs of primitive tribal groups, adolescent girls, children in the age group 0 to 3, and others who do not have strong lobbies to ensure that their rights are guaranteed. The private sector, including farming, small-scale enterprises and the corporate sector, has a critical role to play in achieving the objective of faster and more inclusive growth. employment for programmes that It will contribute directly by raising income levels and the population in general and it will also help to finance are necessary to ensure that growth is more broad based and inclusive. Converting potential into reality is a formidable task and cannot be achieved if we simply continue on a business as usual basis. We need to move away from a focus on outlays to a hard look at outcomes. (Source: Towards Faster and More Inclusive Growth, Draft Approach to the 11th Five Yr Plan, Plg Commission, GoI, Jun 06) Vision 2020: India s economic and technological transition is slower, less clearly defined and less visible. The main consequences on the functioning of the government 20 years from now and that of transformation are Decentralisation,

- 139 - People s Participation, Efficiency, Transparency and Accountability. Nodal Points of Indian Prosperity as per vision document are:- Peace, Security & National Unity Food & Nutritional Security Good Governance Globalisation Work Values Technology Jobs for All Knowledge Health (Source: Report of the Committee on India Vision 2020, Planning Commission, GoI, Dec 2002) ----------X----------