Suchergebnisse

Rajshree Chandra (ed.), The Cunning of Rights: Law, Life, Biocultural. New Delhi: Oxford University Press. 2015. 244 pages. ₹850.

SummaryDemographic and socioeconomic data were collected from the Hindu, Mahishya caste community of Chakpota village, Amta Police Station area, Howrah district, West Bengal, to examine the possible effects of economic differences on fertility and mortality, and their potential genetic consequences. The age structure of the low, medium and high economic groups suggests decreasing growth potentials from the former to the latter, with a recent decline of fertility in all the three groups. Analogously, a trend of fertility and mortality decline from the low to high economic groups seems to exist, although with some exceptions. The index of total selection intensity (I) is the highest in the low economic group. Genetic selection seems to be sensitive even to very small differences in economic condition, among related subpopulations of the same population, sharing very similar physical environmental stresses.

Chapter 1: Introduction to Regression Analysis and an overview of the techniques used in the book -- Chapter 2: Regression Decomposition Technique towards Finding Intra-Household Gender Bias of Calorie Consumption -- Chapter 3: Estimation of Poverty Rates by Calorie Decomposition Method -- Chapter 4: Estimating Calorie-Poverty Rates through Regression -- Chapter 5: Contribution of Regressors: A Set Theoretic Approach -- Chapter 6: Estimation of Hidden Markov Chain through Regression -- Chapter 7: Finding Geometric Mean and Aggregate Growth Rate through regression -- Chapter 8: Summary and Discussions

AbstractIndia is the highest contributor to child anaemia among developing countries. To see the latest picture of child anaemia in India, data for 6- to 59-month-old children were taken from the fourth round of the National Family Health Survey conducted in 2015–16 (NFHS-4). The study sample consisted of 1,37,347 children. The dependent variable was the anaemia status of the child. The objectives of the study were to assess (i) the distribution of anaemia prevalence by child age group, (ii) the prevalence of child anaemia by zone and state and (iii) the relation of child anaemia prevalence with social, demographic and economic variables, including maternal nutritional status and low birth weight. The study found that in India in 2015–16, 56% of 6- to 59-month-old children were anaemic – a decrease of only 13.5 percentage points since the NFHS-3 study conducted in 2005–06. It is well known that iron supplementation is necessary for child growth and brain development. This study suggests that, in addition, the socioeconomic conditions of households in India need to be improved to prevent child anaemia. Low birth weight and low maternal nutritional status are also responsible for the high prevalence of anaemia among children in India.

Socio-economic development in a country is very much linked with the improvement of overall status of health of the people in the country. The causality works both ways. However, the degree of relations between the two varies over region and time. This article is an attempt to show how health status is linked with the socio-economic status in different states of India. The health status is seen only for children and women and the data are taken from National Family Health Surveys (NFHS-2 and NFHS-3). For other development parameters National Sample Survey (NSS) data are used. The socio-economic variables taken for this purpose are head count ratio, real mean consumption, sex ratio, literacy level and infant mortality rate whereas the health variables are mainly the morbidity parameters like acute respiratory infection, diarrhoea, anaemia and low nutritional status. The results show that a decrease in the incidence of disease is directly associated with an increase in the socio-economic development, at least in the southern states. In addition to calculating the correlations between pairwise variables, we have found the rank correlation between the average of ranks of socio-economic variables and of health variables. We have also found the canonical correlations between the two sets of variables. The two correlations agreed very well. This was done separately for rural and urban sectors.

SummaryThe aim of this paper is to assess the spatial distribution of nutritional status of children of less than three years through Z-scores of weight-for-age, height-for-age and weight-for-height using data collected by the National Family Health Survey (NFHS-2, 1998–99), India. The nutritional status of pre-school children was regressed on different socio-demographic factors after eliminating the effect of age. The data show that there are gender differences and spatial variations in the nutritional status of children in India. Gender difference is not very pronounced and almost disappears when the effects of age and socio-demographic variables are removed. The spatial difference, especially the rural–urban difference, was found to be very large and decreased substantially when the effects of age and socioeconomic variables were removed. However, the differences were not close to zero. All the variables were found to affect significantly the nutritional status of children. However, the literacy of mothers did not affect height-for-age significantly. The weight-for-age and height-for-age scores showed a dismal picture of the health condition of children in almost all states in India. The worst affected states are Bihar, Madhya Pradesh, Orissa and Uttar Pradesh. Assam and Rajasthans are also lagging behind. Weight-for-height scores do not give a clear picture of state-wise variation. Goa, Kerala and Punjab are the three most developed states in India and also have the lowest percentages of underweight children according to the Z-scores. Along with these three states come the north-eastern states where women are well educated. Thus overall development, enhancement of level of education and low gender inequality are the key factors for improvement in the health status of Indian children.

Intro -- Foreword -- Preface -- Contents -- Editors and Contributors -- Abbreviations -- Introduction -- Inequality, Growth and Development -- 1 Does Economic Growth Increase Inequality?: An Empirical Analysis for ASEAN Countries, China and India -- Abstract -- 1.1 Introduction -- 1.2 Modelling Growth and Inequality: Related Literature -- 1.2.1 Growth, Inequality and Their Interrelationships -- 1.2.2 The 95% Theory of Kuznets' Inverted U Hypothesis: Just a Glorified Speculation? -- 1.2.3 The Exalted Status of the Interrelationships Between Growth and Inequality: The Immortal Triangle of Growth-Inequality-Poverty -- 1.3 Our Modelling Framework -- 1.3.1 Discussion of the Theoretical Findings -- 1.3.2 Empirical Foundation to the Nonlinear Relationship Between Growth and Inequality -- 1.3.3 Inequality and Growth Data: A Small Note -- 1.4 Empirical Results: Panel Analysis of Determinants of Inequality -- 1.4.1 The Panel Estimation Equation -- 1.4.2 GMM Estimation Results -- 1.4.3 Panel Estimation Results and Findings -- 1.5 Sources of Nonlinear Relationship Between Growth and Equity: Methodology and Findings -- 1.5.1 Methodology: Reversal of Roles and Threshold Model in Terms of FDI -- 1.5.2 Findings -- 1.5.3 Discussion of Findings -- 1.5.4 Growth and Inequality: A Simplistic Exposition -- 1.5.5 Growth and Inequality: An Alternative Specification -- 1.5.6 Discussion -- 1.6 Conclusion -- References -- 2 Does Institutional Quality Affect Foreign Direct Investment? A Panel Data Analysis -- Abstract -- 2.1 Introduction -- 2.2 Literature Review -- 2.3 Theory and Hypothesis -- 2.4 Specification and Data -- 2.5 Estimation -- 2.6 Results and Discussion -- 2.7 Conclusion -- References -- 3 An Empirical Verification of Kuznets Hypothesis in India -- Abstract -- 3.1 Introduction -- 3.2 Why Care About Inequality? -- 3.3 Kuznets Hypothesis