Article

Long-Term Population Projections for Major States, 1991-2101

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Abstract

The authors decompose the prospective population growth in 16 major states between 1991 and 2101 into three components to estimate the contribution of each of them individually. The decomposition of population growth in different states seeks to estimate the impact of growth momentum built into the age distribution of population and the share of prospective growth attributable to (a) the unmet need for family planning and (b) high wanted fertility.

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... While there is ample literature discussing cross-country experiences of demographic transition and its implications for growth (see, for example, Williamson 1998 andCanning 2004), there is little litera-ture on differences in demographic transition across regions within a country. However, there has been a keen interest in the demographic trends across states in India (for example, Bose 1996Bose , 2006Bhat 2001;Visaria & Visaria 2003;Mitra & Nagarajan 2005;Chandrashekhar et al. 2006;James 2008;Aiyar &Mody 2011 andNavaneetham &Dharmalingam 2012). This is the second strand of literature with which this article is closely connected. ...
... However, they do so only at a very aggregate 'region' level. Visaria and Visaria (2003), using the 1991 census as the base, provide population projections for major states up to 2101. They argue that the difference in fertility and mortality rates will manifest themselves in differences in the pace of demographic transition and that the BIMARU states, Assam, Haryana and Orissa will take 10 to 15 years longer to complete their demographic transition. ...
Article
Age structure and its dynamics are critical in understanding the impact of population growth on a country's growth prospects. Using state-level data from India, we show that the pace of demographic transition varies across states, and that these differences are likely to be exacerbated over the period 2011–26. We show that the so-called BIMARU states (Bihar, Madhya Pradesh, Rajasthan, and Uttar Pradesh) are likely to see a continuing increase in the share of the working-age population in total population. The BIMARU states are expected to contribute 58 per cent of the increase in India's working-age population. The BIMARU states have traditionally been the slow-growing states and have performed poorly on different accounts of social and physical infrastructure. The article argues that whether the demographic window of opportunity will be utilised and turned into a boon or be wasted and result in a bane will rest critically on the ability of the BIMARU states to exploit the bulge in the working-age population.
... Numerous studies have assessed demographic transition in terms of fertility, mortality and health trends and transition on the global scale [6,[8][9][10][11][12][13][14][15][16][17][18][19][20][21]. A growing number of studies in India had also assessed the trends and transition in population health indicators [5,[22][23][24][25][26][27][28][29][30][31][32][33][34][35][36]. However, all these studies have used basic trend line plots, control charts or descriptive tables with annual or decadal changes to determine transition points in population and health indicators. ...
... However, over the past half century, the progress in fertility and mortality decline in India is remarkable [24,26,34,39,61]. Several past studies, which examined the process of demographic transition in India, recognized very few major shifts while concluding that overall demographic trends in India are transitioning from third to the fourth stage of demographic transition [5,27,29,[30][31][32][33][34][35][36]. In view of considerable analytical limitations of such previous studies, in this study we have advanced the 'change-point analyses' as a new methodological tool for assessment of progress and changes in population and health indicators for the larger goal of understanding the true trajectories of the population and health transition. ...
Article
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Lack of a robust analytical tool for trend analysis of population and health indicators is the basic rationale of this study. In an effort to fill this gap, this study advances 'Change-Point analyzer' as a new analytical tool for assessment of the progress and its pattern in population and health indicators. The defining feature of 'change-point analyzer' is that, it detects subtle changes that are often missed in simple trend line plots and also quantified the volume of change that is not possible in simple trend line plots. A long-term assessment of 'change-point analyses' of trends in population and health indicators such as IMR, Population size, TFR, and LEB in India show multiple points of critical changes. Measured change points of demographic and health trends helps in understanding the demographic transitional shifts connecting it to contextual policy shifts. Critical change-points in population and health indicators in India are associated with the evolution of structural changes in population and health policy framework. This study, therefore, adds significantly to the evolutionary interpretation of critical change-points in long-term trajectories of population and health indicators vis-a-vis population and health policy shifts in India. The results have not only helped in reassessing the historical past and the current demographic transition trajectory but also advanced a new method of assessing the population and health trends which are necessary for robust monitoring of the progress in population and health policies.
... Numerous studies have assessed demographic transition in terms of fertility, mortality and health trends and transition at the global scale (Dyson 2010;Van and Knodel, 1980;Bloom and Williamson, 1998;Wilson and Airey, 1999;Wilson, 2001;Wilson, 2011;Bongaarts, 2003;Weeks et al., 2004;Caldwell, 2004;Moser et al., 2005;Doepke, 2005;Dorius, 2008;Dorius and Firebaugh, 2010;Angeles, 2010). A growing number of studies in India had also assessed the trends and transition in population health indicators (Dyson, 2005;Ghosh, 1956;Rele, 1982;Rele, 1987;Dyson, 1989;Bhat, 1989;Bhat, 1997;Bhat et al., 1984;James, 1995, James andNair, 2005;Guilmoto and Rajan, 2001;Visaria and Visaria, 1994;Visaria and Visaria, 2003;Kulkarni and Alagarajan, 2005;Visaria, 2004b;Visaria, 2011). However, all these studies have used basic trend line plots, control charts or descriptive tables with annual or decadal changes to determine transition points in population and health indicators. ...
... However, over the past half century, the progress in fertility and mortality decline in India is remarkable (Rele, 1987;Bhat, 1989;Visaria, 2004b; Office of Registrar General of India, 1971McNay et al., 2003;Visaria, 2011). Several past studies, which examined the process of demographic transition in India recognized very few major shifts and concluded that overall demographic trends in India are transitioning from third to the fourth stage of demographic transition (Visaria and Visaria, 1994;James, 1995;Bhat and Rajan, 1997;Dyson, 2004;Guilmoto and Rajan, 2001;Visaria and Visaria, 2003;Visaria, 2004b;Kulkarni and Alagarajan, 2005;Visaria, 2011). ...
Thesis
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This thesis comes out at a time when the debate on between-state and social group demographic and health inequalities continues to be largely debated based on most recent available information. However, analyses based on the recent demographic and health data have serious limitations in terms of understanding the true trajectories of between-state and social group inequalities. With the changing demographic scenario and most demographic indicators progressing towards the final stages of transition, the major concern in India has been heterogeneity across region and socioeconomic groups. While the demographic heterogeneity in India is well known, how far the differences are converging or diverging has been a matter of great interest. This study attempted to develop a comprehensive framework to study the demographic transition, convergence and its linkage with health inequalities in India. It innovate a mechanism of bridging the gap between demographic convergence and health inequalities by taking the theories and methods found in other social science disciplines. It revisits the old theories such as classic socioeconomic, demographic and health transition theories more clearly identifying the historical linkages between socioeconomic, demographic, health transition and health inequalities. It advances the empirical examination of demographic convergence assessment by assessing convergence not only in the averages, but also in the absolute and relative inequalities in population and health indicators. The core chapters of the thesis deal with the issue of convergence. Chapter 4, 5, 6 and 7 analyse the convergence using various indicators. While chapter four considers convergence in socioeconomic indicators, chapter 5 and 6 looks at the mortality and fertility convergence. Chapter 8 links fertility decline with child health inequalities and chapter 9 identifies the avoidable demographic difference. Chapter 10 presents summary and conclusion. The analyses foster that while economic variables are diverging, fertility variables are converging in recent years. Perhaps, it re-affirms the fact that fertility transition is not critically related to economic factors in India. The mortality convergence has some setbacks in recent years. The child health care utilization has shown converging although at a lesser magnitude. Moreover, fertility decline is associated with increasing in child health inequalities in a context where there are pre-existing socioeconomic inequalities. Inequality is often a consequence of progress. Not everyone gets rich at the same time, and not everyone gets immediate access to the latest life-saving measures. Further, growth, inequality, and catch up are the both sides of the same coin. The dark side is what happens when the process is hijacked, so that catch-up never comes. Powerful and wealthy elites have choked off demographic and health progress before, and they can do so again if they are allowed to undermine the institutions on which broad-based demographic and health progress depends. Now, it is confirmed from this study that a mere reduction in the number of children or fertility convergence in averages are not helping in distributing the fruits of demographic progress equally among the children of different states and socioeconomic groups. How far children and their development (particularly in terms of health) are faring during the progress of demographic transition is an important concern for population policy in India. In principle, inequalities are avoidable as disparities in health stem out from identifiable policy options exercised by governments. Thus, they are amenable to policy interventions. In general, this study promotes the importance of using effective health monitoring tools such as convergence models in countries such as India, which has huge socioeconomic and geographical disparities in the progress of demographic and health inequalities. The policy analyst can use convergence measures as tools for health policy evaluations in India and states. In an effort to continuously track regional progress in population and health indicators, it is important to test the convergence hypothesis for every five years.
... Despite India's strong growth performance, the other growing concern is that the benefits of growth have been concentrated in India's richer states, leaving the poorer states lagging further and further behind (Purfield, 2006). These concerns become more serious when one considers the projections suggesting that 60 per cent of the 620 million increase in India's population, by 2051, will occur in three of its poorest States: Bihar, Madhya Pradesh and Uttar Pradesh (Visaria, 2003). ...
Article
As India grows, driven by its success in information technology and services, there is another revolution waiting to happen in the Retail sector dependent on whether the Government of India can unshackle the various inefficiencies that are keeping this industry constrained. Retail in India is estimated at nearly US$ 400 billion and is growing at a CAGR of 9 percent (AT Kearney GRDI 2010). 96 percent of this sector remains un-organized and constitutes a workforce that have taken to self-employment for daily subsistence due to an overcrowded agriculture sector and lack of employment opportunities for lesser skilled workers in the manufacturing or services sectors. Food and groceries form nearly 60 percent of India's retailing followed by, among others, clothing and footwear at a distant 9 percent of retail. Despite the size of this market, retail and its food supply chain remains unorganized and inefficient. A lack of investment, technology and process control in the agriculture supply chain leads to tremendous waste accounting for nearly 25-30% of fruits and 10% of grains produced. Also, the related and supporting industries for food processing, cold chains and crafts remain nascent. In a grim reflection on the situation, a politician in India recently remarked that Indian consumers buy shoes in air-conditioned stores but food on the streets. Despite this scathing but accurate comment, the debate on whether to organize retail remains unresolved. This debate is further complicated by intellectual and political debate on the impact of Foreign Direct Investment (FDI), by large international retailers like Wal-Mart, on the fate of small retailers. Interestingly, both these questions have been on the table of policy makers in India for more than 15 years and the Government has so far only allowed some FDI in 'single-brand' retailing and 'wholesale trading' of retail goods. While the incumbent Congress party led Government has voiced many reasons to organize retail and allow FDI in multi-brand retailing, public opinion in response to a discussion paper released by the Department of Industrial Policy and Promotion (DIPP) - Ministry of Commerce & Industry - has been negative. In my quest to decipher whether India should organize and allow FDI in multi-brand retail, I have analyzed all the opinions received by the DIPP. I posit that the data is skewed and not sufficient to form the basis of a policy decision. I have also conducted an extensive literature review on the impact of Wal-Mart on small retailers to understand the potential impact it can have on India. Despite the concerns, I conclude that this change can be managed to India's advantage and that opening of the retail sector to FDI is an imperative, not an option.
... For if this process continues, the fast-growing states will not only suck the more mobile skilled labor from the slow moving states leading to a further hollowing out of prospects, but also the divergence in growth rates will increase further. Indeed, there are additional reasons for concern. Visaria and Visaria (2003) suggest that based on current fertility rates in different states, of the expected 620 million addition to the Indian population between now and 2051, 60 percent will be in Bihar, Madhya Pradesh, Rajasthan and Uttar Pradesh, and 32 A recent issue of Business Week notes that: " As India's domestic economy expands, the shortfalls are spre ...
Article
India has followed an idiosyncratic pattern of development, certainly compared with other fast-growing Asian economies. While the importance of services rather than manufacturing is widely noted, within manufacturing India has emphasized skill-intensive rather than laborintensive manufacturing, and industries with higher-than-average scale. Some of these distinctive patterns existed prior to the beginning of economic reforms in the 1980s, and stem from the idiosyncratic policies adopted after India's independence. Using the growth of fastmoving Indian states as a guide, we conclude that India may not revert to the pattern followed by other countries, despite reforms that have removed some policy impediments that contributed to India's distinctive path.
... ge population. We also show the contribution of each of the states to the expected increase in India " s working-age population. This will help identify the states that will account for a lion " s share of the increase in India " s working-age population. We discuss whether these states will be able to exploit the demographic window of opportunity. Visaria and Visaria (2003), using the 1991 census as the base, provide population projections for major states up to 2101. They argue that the difference in fertility and mortality rates will manifest themselves in differences in the pace of demographic transition and that the BIMARU states, Assam, Haryana, and Orissa will take 10 to 15 years longer to complete t ...
Article
Age structure and its dynamics are critical in understanding the impact of population growth on a country’s growth prospects. Using state-level data from India, we show that the pace of demographic transition varies across states, and that these differences are likely to be exacerbated over the period 2011-2026. We show that the so-called BIMARU states (Bihar, Madhya Pradesh, Rajasthan, and Uttar Pradesh) are likely to see a continuing increase in the share of the working-age population in total population. The BIMARU states are expected to contribute 58% of the increase in India’s working-age population. The BIMARU states have traditionally been the slow-growing states and have performed poorly on different accounts of social and physical infrastructure. Whether India can turn demographic dividend into a boon or whether the dividend will become a bane will critically depend on the ability of the BIMARU states to exploit the bulge in the working-age population.
... This can be interpreted as state-level variations in social and political commitments [10][11][12][13]. The persistently high levels of childhood stunting in states like Bihar, Uttar Pradesh, and Madhya Pradesh are a concern not only from a social, political, and public health standpoint but also because these states are projected to contribute the maximum to the future population growth in India [14]. On the other hand, Tamil Nadu is lauded for its superior performance in several public health fronts and often portrayed as the best practices state [15][16][17][18][19]. ...
Article
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Despite rapid macroeconomic growth, one-third of the global burden of childhood stunting is contributed by India. This burden is characterized by widespread geographical variation within the country. This paper explores two research questions: (i) are the drivers of severe and moderate stunting similar? (ii) differential endowments or policy-effect, how do community level nutrition and sanitary practices affect interstate differences? Using data from Indian National Family and Health Survey 4, 2015-16, six states holding different ranks in the stunting continuum are compared to Tamil Nadu, taken as the benchmark state due to its laudable performance in the health care sector. Applying quantile regression approaches, the difference in state-level performance is decomposed into detailed covariate effects (differential endowments) and coefficient effects (differential strength of association between the drivers and outcome). The explanatory variables are not similarly associated with severe and moderate stunting. Decomposition results demonstrate a significant role of community-level sanitation practices compared to child nutrition behaviour in explaining the interstate disparity. Coefficient effects play a dominant role in the lower tail of HAZ distribution for the poor performing states indicating that the worse outcomes of these states are due to weaker policy effects of the control variables on stunting. Multi-sectoral approach, identification and differentiation between severe and moderate stunting cases can be more instrumental in managing and reducing the scourge. This paper also advocates the potential benefits of customizing centrally-launched policies as per the state's performance and introducing the concept coproduction in the existing nutrition and health policy framework. This will instigate a feeling of ownership of the problem of childhood stunting among the policy consumers and strengthen the influence of policies on the outcomes.
... Moreover, as many perceive that globalization and economic liberalization have contributed to this state of affairs, economic divergence could erode support for economic reform and for further opening of the Indian economy. These concerns gain even greater traction when one considers projections that about 60 percent of the forecast 620 million increase in the Indian population between now and 2051 will occur in three of its poorest states, Bihar, Madhya Pradesh and Uttar Pradesh ( Visaria and Visaria, 2003). ...
Article
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This paper examines how growth has varied across India's states. It finds that (i) the income gap between rich and poor states has widened; (ii) rich and faster-growing states have been more effective in reducing poverty; (iii) poor and slower-growing states have had little success in generating private sector jobs; (iv) labor and capital flows do little to close income gaps; and (v) the volatility in economic growth is greatest in poor states. Differences in states' policies affect the cross-state pattern of growth. Greater private sector investment, smaller governments, and better institutions are found to have a positive impact on growth.
... www.elsevier.com/locate/worlddev Madhya Pradesh, and Uttar Pradesh are also where the bulk of the projected population increase in the next decades will come from (Visaria & Visaria, 2003), (iii) A comprehension of the relative roles of covariate and coefficient effects can provide an understanding of the extent to which nutrition convergence can be attained by improving basic endowments that impinge on nutrition, and the extent to which more directly nutrition-related programing and the general quality of institutions and policy-making, as reflected in coefficient effects, are important. A vibrant literature, reviewed below, has emerged that empirically explores the determinants of child anthropometric outcomes in India. ...
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What drives the large disparities in height-forage distributions among Indian states-variation in observed nutrition-related endowments, such as wealth or maternal education, or differential strengths of relationships across states between endowments and height-for-age? We explore this question by comparing a set of states with poor nutrition outcomes with the benchmark of Tamil Nadu, a good performer. Applying counterfactual decomposition methods to National Family Health Survey data, we find that surprisingly modest proportions of HAZ differences are attributable to endowment differences. We discuss our results in light of the superior track record of food and nutrition policies in Tamil Nadu.
... UP state was purposively selected for this study as many studies indicated it is one of the worst affected states in India in terms of nutrition. Visaria and Visaria (2003) reported that Bihar, Madhya Pradesh and UP were the states in the bottom of the nutrition league in India and malnutrition situation in Uttar Pradesh is in general worse than for the country as a whole. The study conducted by IIPS and GoI (2006) indicated that 56 per cent of children in UP as whole are malnourished. ...
Article
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Nutrition status of people is decided by the dietary habits of people of a region and it has substantial implications for the quality of life of its population. In this background, a study had been undertaken with the objective of understanding dietary habits with special reference to dietary diversity and nutritional status among rural population. The study is based on the primary data collected in Baghpat district of Uttar Pradesh during the year 2014-15. The body mass index, one of the indicator of nutrition status reveals about 10 per cent men, 20 per cent women, 30 per cent boys and 35 per cent girls were coming under underweight and remaining fell in overweight category. Nutrition awareness among the female groups was better than male groups and anganwadi workers were the key informants. The actual consumption of all the food groups were about 50 per cent less than the recommended dietary allowance (RDA) across all the categories. Home produced milk consumption was near to RDA and market depended pulses were more deficient in their consumption. The Individual Diet Diversity Score (IDDS) ranged from 7.6 to 8.0; womens' dietary diversity score was slightly less than men, similar was the case with children. Simpson Index of Dietary Diversity (SIDD) ranged from 0.69 to 0.77. As evidenced from this study, household production enhances food accessibility, hence, promotion of diversified cropping pattern could be a right strategy for enhancing nutritional security in rural areas. Further, this study suggests to target men as well women for sensitization and awareness programme about importance of food and nutrition to achieve nutritional security of all in particular women.
... India is expected to reap the demographic dividend through contributions to economic growth by the younger population. States in earlier stages of the demographic transition, like, Bihar, Uttar Pradesh, and Madhya Pradesh have the potential to contribute to more than 30% of the labor supply in India and are projected to be major contributors to the working age population by 2030 [4]. In order to convert the growing working age population into effective labor force, these states need to strengthen their existing health care system and rapidly improve public health outcomes [5,6]. ...
Article
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Background: To draw optimal benefits of the demographic dividend, healthy life years of the young adults is a growing concern in India. Rising prevalence of chronic non-communicable diseases among the younger population is responsible for increasing the life years lived with disability among them and for affecting their productivity in turn. This study measures the disability burden in various Indian sub-populations and assesses the contribution of disability to the change in person years lived with a disability during 2001–11. Methods: Data from the Census of India, 2001 and 2011 was used for estimating the age distribution and disability prevalence among males and females. The Sample Registration System was used for age-specific mortality rate to calculate the life table for 15 states in India. Life years Lived with Disability (LLD) were estimated using the Sullivan method. The extension of Arriaga method was used to decompose change in life years lived with disability into Mortality and Disability Effect (ME and DE, respectively). Positive ME explains improvement in life years due to decline in mortality rate and a negative DE explains a decline in disability incidence in 2001–11. Results: At national level, the disability prevalence has increased from 2001 to 2011. The prevalence of disability and the share of LLD to Life Expectancy (LE) is higher for males. High and medium fertility states scored highest on living with disability to LE ratio and measured DE in the decomposition analysis. At the national level, the DE increased in the age groups of 20–35 years. It was higher among the females. The states that are in the advanced stages of demographic transition show a negative DE. Conclusion: The study highlights expansion of DE in prime productive years of life, especially among females, in medium and high fertility states. Decline in skilled employment and productivity can be two major economic adversities due to increasing DE in working ages. Disability among young and working age population needs to be prioritised as most of the Indian states stand at crucial stages of demographic transitions.
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There is a lack of verifiable evidence on the period and magnitude of the demographic dividends in India, a gap policy makers must address when setting priorities for human resource and capital investment to harvest the economic benefits of the demographic transition currently under way. This study attempts to fill this gap by quantifying the demographic dividends using National Transfer Accounts framework and by indicating their implications for equity. Our analysis projects that income per effective consumer could increase by 24.9% from 2005 to 2035-9.1% from the first demographic dividend and 15.8% from the second demographic dividend-and that the second dividend will be stable up to 2070. However, unless appropriate institutional reforms create an environment conducive to accumulating assets and raising productivity, India will find it difficult to meet the fiscal challenges posed by population aging.
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This paper provides vital insights into the challenges facing youth in terms of employment opportunities in India (Mitra and Verick, 2013). The main objective of this paper is to encourage discussion and further research for the promotion of decent work with respect to youth employment in Asia and the Pacific. According to ILO's Global Trends Report 2012 on Youth, almost 75 million young people are unemployed across the globe, which represents an increase of more than 4 million since 2007 (ILO, 2012). These challenges are noticeable in India, which has the largest youth population in the world with around 66 per cent of the total population under the age of 35 (United Nations, 2003). In this environment, much is often said about a ‗demographic dividend' (Ghosh et al.2010). However, not being able to provide right match of employment opportunities for this lot of young people as they penetrate the labour market risks a ‗demographic disaster' (Verick, 2009). With this regard, governments are precisely concerned about increasing levels of youth unemployment and underemployment because of not only the direct economic costs, but also due to the social impact of joblessness as manifested by increased mental health problems ,violence, drug taking and other social outcomes (Bell and Blanchflower, 2009). Against these conditions, this paper addresses the nature of employment profile of youth in India with focus on the suggestions for challenges with respect to youth unemployment in India. The research methodology used is qualitative with major focus on secondary data.
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The extent to which couples agree with each other on fertility intentions, sex of the next child, and the intention to use family planning in future has a major role not only in determining family size but also in the process of fertility transition. The present paper investigates this question in Uttar Pradesh, India. Quantitative data from the District Level Household Survey conducted in 2002-2004 has been used in the present analysis. Our analysis indicates that more wives than husbands do not desire an additional child. Further, more wives than husbands desire their next child to be a male child. Results show that the husbands have significant influence on the couples’ reproductive goals. It can be concluded that understanding husbands’ views are essential from the policies and programmes’ point of view.
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India seems to have followed an idiosyncratic pattern of development, certainly compared to other fast-growing Asian economies. While the emphasis on services rather than manufacturing has been widely noted, within manufacturing India has emphasized skill-intensive rather than labor-intensive manufacturing, and industries with typically higher average scale. We show that some of these distinctive patterns existed even prior to the beginning of economic reforms in the 1980s, and argue they stem from the idiosyncratic policies adopted soon after India's independence. We then look to the future, using the growth of fast-moving Indian states as a guide. Despite recent reforms that have removed some of the policy impediments that might have sent India down its distinctive path, it appears unlikely that India will revert to the pattern followed by other countries.
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A review of existing approaches to the estimation of wanted fertility concludes that these measures typically contain an upward bias. An alternative methodology is therefore proposed to estimate wanted fertility from survey questions about women's desire to continue childbearing. This new methodology is applied to data from 48 surveys in developing countries. The results from this exercise indicate that in these populations on average 26% of fertility is unwanted, which is substantially more than estimated derived with other methods. The proportion unwanted apparently varies systematically over the course of the fertility transition: it is lowest at the beginning and end and highest among countries in mid-transition. -Author
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Foreword - E M S Namboothiripad Kerala's Demographic Transition - K C Zachariah and S Irudaya Rajan An Overview PART A: DEMOGRAPHIC TRANSITION Demographic Transition Since Independence - P N Mari Bhat and S Irudaya Rajan Demographic Transition - K C Zachariah A Response to Official Policies and Programmes Onset of Mortality and Fertility Transition - S Irudaya Rajan, P N Mari Bhat and Tim Dyson New Evidence from Parish Records Fertility, Mortality and Contraceptive Prevalence - P S Nair Evidence from the National Family Health Survey PART B: DETERMINANTS OF DEMOGRAPHIC CHANGE Can Poverty Determine Fertility? - K S James Agricultural Labourers and Their Fertility Decisions Determinants and Correlates of Age at Marriage - K Krishnakumari and G K Moli Education and Fertility - D Radha Devi Is There Any Link PART C: CONSEQUENCES OF DEMOGRAPHIC CHANGE Life Table Analysis of the Labour Force - S Sulaja and N B Sureshkumar Dynamics of Age at Maternity - U S Mishra and S Irudaya Rajan Low Birth Weight and Need for Nutritional Care for Pregnant Women - R S Kurup Population Ageing - S Irudaya Rajan and U S Mishra Causes and Consequences Inter-Regional Comparison of Demographic Conditions - P Mohanachandran Nair PART D: MIGRATION Peasant Migration from Travancore to Malabar - K V Joseph Economic Consequences of Gulf Migration - T M Thomas Issac Social Consequences of International Migration - Leela Gulati Case Studies of Women Left Behind
Returning a Favour: Changing Relationship between Female Education and Family Size in India
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