The Demographic and Development Divide in India: A District-Level Analyses [1st ed. 2019] 978-981-13-5819-7, 978-981-13-5820-3

Table of contents :
Front Matter ....Pages i-xxxi
Contextualising Demographic and Development Divide in Districts of India (Sanjay K. Mohanty, Udaya S. Mishra, Rajesh K. Chauhan)....Pages 1-15
Population Trends, Distribution and Prospects in the Districts of India (Rajesh K. Chauhan, Sanjay K. Mohanty, Udaya S. Mishra)....Pages 17-144
Fertility Transition in the Districts of India, 1991–2011 (Sanjay K. Mohanty, Sayantani Chatterjee, Emily Das, Suyash Mishra, Rajesh K. Chauhan)....Pages 145-195
Development Disparity and Interstate Out-Migration in the Districts of India (Kalosona Paul)....Pages 197-258
Educational Development and Disparities in India: District-Level Analyses (Sayantani Chatterjee, Udaya S. Mishra)....Pages 259-328
State of Health in the Districts of India (Sanjay K. Mohanty, Nihar R. Mishra, Junaid Khan, Guru Vasishtha, Udaya S. Mishra)....Pages 329-373
Maternal and Child Health in Districts of India: Deprivation and Disparities (Basant Kumar Panda, Udaya S. Mishra, Shubhkant Swain)....Pages 375-416
Primary Healthcare Infrastructure and Reproductive Healthcare in Rural India: A District Level Analysis (Pijush Kanti Khan, Kajori Banerjee, Swarbhanu Nandi)....Pages 417-466
Economic Development in the Districts of India (Sanjay K. Mohanty, Anjali Dash, Radhe Shyam Mishra, Bidyadhar Dehury)....Pages 467-507
Spatial Pattern of Development in Districts of India (Sanjay K. Mohanty, Bidyadhar Dehury, Udaya S. Mishra, Anjali Dash, Rajeev R. Singh)....Pages 509-551
Summarizing Development Divide in Districts of India (Udaya S. Mishra, Sanjay K. Mohanty)....Pages 553-558

Citation preview

Sanjay K. Mohanty · Udaya S. Mishra  Rajesh K. Chauhan Editors

The Demographic and Development Divide in India A District-Level Analyses

The Demographic and Development Divide in India

Sanjay K. Mohanty • Udaya S. Mishra Rajesh K. Chauhan Editors

The Demographic and Development Divide in India A District-Level Analyses

Editors Sanjay K. Mohanty International Institute for Population Sciences Mumbai, Maharashtra, India

Udaya S. Mishra Centre for Development Studies Thiruvananthapuram, Kerala, India

Rajesh K. Chauhan Planning Department Directorate of Economics & Statistics Lucknow, Uttar Pradesh, India

ISBN 978-981-13-5819-7 ISBN 978-981-13-5820-3 https://doi.org/10.1007/978-981-13-5820-3

(eBook)

© Springer Nature Singapore Pte Ltd. 2019 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Dedicated to Our Beloved Parents

Foreword

Recent decades have witnessed the bridging of data gaps in key dimensions of human development. Large-scale population-based surveys, such as the National Family and Health Survey 4, 2015–2016, the District Level Household Surveys, and the Census of India, have facilitated the availability of robust estimates of social, economic, and demographic variables in the districts of India. Though much of this information is obtainable from varying sources, it has not been comprehensively explored and compiled in one place to comment on the regional facets and clustering of outcomes. This book serves as a compilation of a wide range of demographic and developmental indicators at the district level that is useful for researchers and policy-makers to examine the regional perspective on the one hand and developmental clustering on the other. This book is an endeavor of three senior editors and a number of young research scholars. The findings of each chapter are interesting and offer avenues for further exploration. It is resourceful not merely for the disaggregated information base but toward generating new hypothesis concerning the spatial pattern of development in the districts of India. Reading the spatial pattern of demographic, social, and economic inequality can help achieve balanced regional development. This book will be of interest for a range of professionals beyond researchers and academics. It will serve as a ready reference for central and state government officials and district administrators. This is a timely contribution in today’s era of accomplishing sustainable development goals and emphasis on decentralized planning. I consider this as an initiative to read development through a demographic lens as demography is destiny. Honorary Fellow, Centre for Development Studies Thiruvananthapuram, Kerala, India

K. C. Zachariah

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Preface

Demographic transition and its impact on socioeconomic development have drawn considerable research attention worldwide. Demographic transition has yielded demographic dividend, increased income levels, and improved health and educational attainment of the population. However, it has also widened development disparities within and among countries. The spatial inequality in demographic and developmental outcomes is larger within the country than across countries. Thus, a comprehensive understanding of the intertwined association between demographic and developmental indicators at the sub-national level assumes significance in developmental planning. Despite the sound statistical system in India, the key demographic and developmental indicators are not readily available beyond the state level. The state average conceals more than it reveals, given the substantial variations in the districts of India. District is the basic administrative unit in India, and, therefore, planners and policymakers need demographic and developmental indicators at district level for monitoring and evaluation. The number of districts is large (640) and displays enormous variations in demographic and developmental performance. Although constraints in obtaining district-level estimates have been overcome in recent times, exploration of district-level information remains limited. Hence, an examination of the demographic and development divide in the districts of India is a noteworthy attempt. This book presents key demographic and developmental indicators in the districts of India. District is the unit of analyses and the exposition is made on two counts. In the beginning, the demographic divide with respect to population trends, distribution, fertility trends, and migration is presented. This is followed by examining the state of development in the key domains of human development (education, health, and standard of living). The overall state of development is assessed using a District Development Index. Information explored in the book has been taken from the Census of India, National Family and Health Survey 4, National Sample Survey, and other published sources, and many indicators are derived from unit level data. Each of the nine analytical chapters presents a set of indicators to test newer hypothesis. It begins by presenting demographic trends and population ix

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Preface

characteristics with its prospective trends. Association of fertility level with its proximate determinates has been explored. Interstate out-migration has been estimated using data from Census of India, and its association with development has been verified. Educational outcomes in terms of newer indicators with focus on gender are being examined to comment on educational progress. The state of health along with the state of health infrastructure and maternal healthcare utilization is inspected across the districts to inform regarding the imbalance and disparity thereof. In many of the chapters, composite indices are computed, and the districts are ranked at the national level as well as within states. This book has many important findings. It found large variations in child sex ratio, growth rate, median age, and dependency ratio. The declining trend in child sex ratio (number of girls per 1000 boys in 0–6 age group) is not limited to low-fertility districts but is extended to transitional districts. Though fertility reduction is uniform across states, the districts exhibit fertility divergence. The out-migration from districts to other states is high at both extremes of the level of development. The educational outcomes portray large variations when measured using mean years of schooling, school life expectancy, and educational parity index. The state of health, too, varies widely across the districts, and health outcome is associated with healthcare and health infrastructure. The levels of economic development and overall development in the districts are clustered. This book is unique in unfolding a disaggregated story of the evolution of demographic and developmental transition, which can serve as a ready reference for a wide range of readers cutting across various disciplines. It offers an assessment of ranking Indian districts within the state and at the national level. This helps identify the backward districts within the state and in the country. Hence, it serves as a useful reference for the government in designing policies and interventions toward attaining developmental convergence. The spatial analysis carried out in the book identifies the clustering pattern of development in India. The comprehensive exposition of regional disparity in demographic and developmental perspectives will undoubtedly generate curiosity concerning the population and development nexus in India. We thank the authors for contributing the analytical chapters in the book. We thank Prof. K. Srinivasan, Prof. K.C. Zachariah, Prof. K.S. James and Prof. L. Ladusingh for their encouragement and valuable suggestions at various stages of preparing the manuscript. We thank Sudha Raghavendran for the editorial assistance. Above all, we thank the Almighty for giving us strength in completing the work. Mumbai, India Thiruvananthapuram, India Lucknow, India 17th May, 2019

Sanjay K. Mohanty Udaya S. Mishra Rajesh K. Chauhan

Contents

1

2

Contextualising Demographic and Development Divide in Districts of India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sanjay K. Mohanty, Udaya S. Mishra, and Rajesh K. Chauhan

1

Population Trends, Distribution and Prospects in the Districts of India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rajesh K. Chauhan, Sanjay K. Mohanty, and Udaya S. Mishra

17

3

Fertility Transition in the Districts of India, 1991–2011 . . . . . . . . . . 145 Sanjay K. Mohanty, Sayantani Chatterjee, Emily Das, Suyash Mishra, and Rajesh K. Chauhan

4

Development Disparity and Interstate Out-Migration in the Districts of India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 Kalosona Paul

5

Educational Development and Disparities in India: District-Level Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 259 Sayantani Chatterjee and Udaya S. Mishra

6

State of Health in the Districts of India . . . . . . . . . . . . . . . . . . . . . . 329 Sanjay K. Mohanty, Nihar R. Mishra, Junaid Khan, Guru Vasishtha, and Udaya S. Mishra

7

Maternal and Child Health in Districts of India: Deprivation and Disparities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375 Basant Kumar Panda, Udaya S. Mishra, and Shubhkant Swain

8

Primary Healthcare Infrastructure and Reproductive Healthcare in Rural India: A District Level Analysis . . . . . . . . . . . 417 Pijush Kanti Khan, Kajori Banerjee, and Swarbhanu Nandi

xi

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Contents

9

Economic Development in the Districts of India . . . . . . . . . . . . . . . 467 Sanjay K. Mohanty, Anjali Dash, Radhe Shyam Mishra, and Bidyadhar Dehury

10

Spatial Pattern of Development in Districts of India . . . . . . . . . . . . 509 Sanjay K. Mohanty, Bidyadhar Dehury, Udaya S. Mishra, Anjali Dash, and Rajeev R. Singh

11

Summarizing Development Divide in Districts of India . . . . . . . . . . 553 Udaya S. Mishra and Sanjay K. Mohanty

About the Editors and Contributors

Editors Sanjay K. Mohanty is a trained economist and demographer and professor at the International Institute for Population Sciences (IIPS), Mumbai, India. Prof. Mohanty, with more than two decades of teaching and research experience, has guided several doctoral students in their research work. Prof. Mohanty teaches Health Economics and Fertility at IIPS. His research interests include health financing, economics of aging, and multidimensional poverty. Prof. Mohanty has authored more than 100 research papers in international and national peer-reviewed journals. Currently, he is the principal investigator of the study entitled “Multidimensional Poverty in Urban Maharashtra” and coordinator of “Longitudinal Ageing Study in India (LASI)”. Prof. Mohanty was visiting scientist at Harvard T.H. Chan School of Public Health, Boston, USA, during 2014–2015 and CR Parekh Fellow at Asia Research Centre, London School of Economics, U.K. in 2010. He was awarded the K.B. Pathak Award, 2009, by the Indian Association for the Study of Population (IASP) for his research work. Udaya S. Mishra is a statistician/demographer serving as a faculty of the Centre for Development Studies, Trivandrum, Kerala, India. He is engaged in research and teaching on Population and Development issues and has a number of national and international publications to his credit. He has served in various capacities of guiding scientific research in social sciences. During his two and a half decades of teaching and research experience, he has contributed to the areas of aging, health, nutrition, as well as population policy and program evaluation. His current research interest includes measurement issues in health and equity focus in evaluation of outcomes. His scholastic distinctions include Takemi Fellow in the Department of Population and International Health, Harvard School of Public Health, Boston, USA, during 2003–2005; associate member of Southampton Statistical Sciences Research Institute, University of Southampton, UK; and expert group member to review the draft xiii

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About the Editors and Contributors

handbook on Designing of Household Sample Surveys at the United Nations Statistics Division, UN, New York. Rajesh K. Chauhan is a trained demographer and statistician with two decades of research experience. Dr. Chauhan is working as Economics and Statistics Officer at the Directorate of Economics and Statistics, Planning Department, Government of Uttar Pradesh. Prior to this, Dr. Chauhan was working as Joint Director with Population Research Centre (PRC), Department of Economics, University of Lucknow. He has a Ph.D. in Demography from the Australian National University, Canberra, Australia, and Master’s degree in Statistics and Population Studies. His primary interest lies in the area of mortality and public health analysis, large-scale sample surveys, data management and analysis, and money metric welfare and poverty measures with special emphasis on measurement methodology. He has extensive experience of working with main Indian sample survey datasets, National Family Health Survey (NFHS), District Level Household Survey (DLHS), and National Sample Survey (NSS). He has a good understanding of CS-Pro environment for data entry. He undertook his Ph.D. work with the prestigious fellowship of the Australian Agency for International Development (AusAID). He has several publications in reputed international and national journals and contributions in edited books to his credit.

Contributors Kajori Banerjee is senior research fellow pursuing Ph.D. at the International Institute for Population Sciences, Mumbai. Her doctoral research is on childhood stunting among siblings in India. Her research interests are public health, child morbidity, statistical demography, and aging. Sayantani Chatterjee is a doctoral student at the International Institute for Population Sciences, Mumbai. Her doctoral work revolves around fertility and development in India. Her research interests include fertility and family planning and development studies. Emily Das is currently working as Associate Director (Monitoring, Learning and Evaluation) at Population Services International, India. She has more than 15 years of experience in planning and implementation of M&E activities relating to MNCHN programs in India. Trained as a demographer with a Ph.D. degree from IIPS, Mumbai, she is skilled in the design of large-scale sample surveys, processing and managing crosssectional and longitudinal data on population, health, and nutrition. She has a proven track record in promoting timely availability and the use of data and research findings for program decision-making and advocacy efforts. Prior

About the Editors and Contributors

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to coming to PSI, Emily worked as Deputy Director-MLE at Abt Associates (Feb 2014–Jan 2018) and Technical Advisor-MLE at IntraHealth International (Oct 2008–Oct 2013) where she was responsible for the design and implementation of all monitoring and research components of the programmes. She has substantial experience in working with web-based MIS using ICT for routine analysis of programme monitoring data. Anjali Dash is a postdoctoral fellow at the International Institute for Population Sciences, Mumbai. She did her Ph.D. in Economics on “Economic of healthcare in rural Odisha” at MP Institute of Social Science Research, Ujjain, Madhya Pradesh, and, prior to that, she had 4 years of research experience at the Institute of Economic Growth, New Delhi, and Centre for Social Studies, Surat, Gujarat. Her areas of research are public health, health financing, poverty, aging, education, employment, and rural and tribal development. Bidyadhar Dehury has a Master’s and Ph.D. degree in Population Studies from the International Institute for Population Sciences (IIPS), Mumbai. Dr. Dehury also did M.A. in Geography from Utkal University, Bhubaneswar. His research works relate to multidimensional poverty, environmental health, maternal and child health, reproductive health, and nutrition. He has published his research work in reputed peer-reviewed journals. For the last 3 years, he has been associated with the monitoring and evaluation team in India Health Action Trust (IHAT) in Uttar Pradesh Technical Support Unit project, Lucknow. He has experience in program implementation, conducting surveys at community and facility levels, data triangulations and analysis, working with HMIS data, report writing, and working with the government and program teams in data-driven decisions. Junaid Khan is doctoral student (senior research fellow) in Population Studies at the International Institute for Population Sciences, Mumbai. He is working in the domain of public health and nutrition. Pijush Kanti Khan is senior research fellow pursuing Ph.D. at the International Institute for Population Sciences (IIPS), Mumbai, India. He holds an M.Phil. degree from IIPS. His doctoral work focuses on “Geographical variation of health insurance and its effect on health care utilization and health spending in India.” He has a keen interest in health financing, health inequality, epidemiology, and multilevel modelling. Nihar R. Mishra is a trained economist and demographer, presently working with Azim Premji Philanthropic Initiatives as Senior Manager. He holds a Master’s Degree in Economics and M.Phil. in Population Studies from the International Institute for Population Sciences, Mumbai. Mr. Mishra has over 13 years of experience in research, monitoring, evaluation, and impact assessment of a wide range of studies/evaluations covering various areas of health, nutrition, and WASH. His research interests include maternal and child nutrition, aging of population, and

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About the Editors and Contributors

adolescent and youth population. Mr. Mishra has authored six research papers in international and national peer-reviewed journals and also presented papers in various national/internal conferences. Radhe Shyam Mishra is a doctoral fellow at the International Institute for Population Sciences, Mumbai. He is pursuing his doctoral work on “Socioeconomic and health dimension of disable people in India.” His research interest includes disability, aging, and multidimensional poverty. Suyash Mishra is a doctoral student at the International Institute for Population Sciences, Mumbai. His proposed doctoral work deals with “Catastrophic Health Spending and Distress Financing on Health Care in India.” He has a keen interest in epidemiology, health financing, and multilevel modelling. Swarbhanu Nandi is a senior research fellow pursuing Ph.D. at the International Institute for Population Sciences (IIPS), Mumbai, India. His doctoral research focuses on “Demographic dividend and Human capital formation in India: A district level study on age structure, economic activity and educational attainment.” His research interests are econometric application, human capital formation, age-sex transition, and infrastructural change. Basant Kumar Panda is a doctoral research scholar at the International Institute for Population Sciences (IIPS), Mumbai. He has completed his M.Sc. and M.Phil. in Statistics and Master’s in Population Studies. His current research interests include maternal and child health, health inequality, and economics of aging. Kalosona Paul is a doctoral fellow in the “School of Development Studies” of Tata Institute of Social Sciences (TISS), since 2014. His doctoral work is on “Internal Labour Migration from West Bengal to Kerala: A Case Study of Alipurduar district.” His areas of interest are migration, health, and development. He earned a second Master’s and M.Phil. in “Population Studies” from IIPS, Mumbai. He worked on different large-scale international (NFHS-4) and national projects (Maharashtra State Rural Livelihoods Mission). He has written research papers using various sophisticated statistical software packages like STATA, GIS, and GeoDa. Rajeev R. Singh is working as Research Officer at the International Institute for Population Sciences, Mumbai. He holds a Master’s degree in Population Studies and Economics. He has keen interest in gender issues, fertility and health economics. Shubhkant Swain is a program manager of the Tata-Cornell Institute’s (TCI) flagship initiative Technical Assistance and Research for Indian Nutrition and Agriculture (TARINA) and the Gender and Nutrition Specialist at TCI. Dr. Swain is based at Cornell University, Ithaca, New York. He is a demographer by training and has a decade of work experience in gender, nutrition, and public health in India and Africa. Dr. Swain coordinates the grant activities between Cornell University and TCI’s Delhi office. He also focuses on generating evidence to inform policy

About the Editors and Contributors

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around gender, nutrition, food, and agriculture. His research primarily focuses on increasing women’s empowerment and access to agricultural services to improve nutritional outcomes in India. Prior to joining TCI, Dr. Swain was a research coordinator in the Division of Nutritional Sciences (DNS) at Cornell University where, apart from teaching and mentoring students in a study abroad program, he supported a research program designed to avert stunting through a multi-sectoral intervention in Tanzania. He has also managed and led many research projects focused on gender and public health policy in India while working with Population Council and Family Health International (FHI360). Dr. Swain received his Ph.D. in Demography from the International Institute for Population Sciences (IIPS) in Mumbai. Guru Vasishtha is a doctoral research scholar at the International Institute for Population Sciences, Mumbai. He has a Master’s and M.Phil. in Statistics from Dr. B.R. Ambedkar University, Agra, after which he acquired a Master’s and M. Phil. in Population Sciences from the International Institute for Population Sciences, Mumbai. He has worked as project officer in the National Family Health Survey Round 4, for the duration of 2 years. His research interests are multidimensional poverty, malnutrition, maternal health, child mortality, and non-sampling errors.

Abbreviations

ANC ANM BMI CABE CEB CHC CI CID CIH CSSM DDI DLHS DPEP DT EDI EPR EAG FISOMR FI GDP GNI GoI GPI HAQ HDI HMIS IEDSS IMR IMS IOM

Antenatal Care Auxiliary Nurse Midwife Body Mass Index Central Advisory Board of Education Census Enumeration Blocks Community Health Centers Composite Index Composite Index of Development Composite Index of Health Child Survival and Safe Motherhood District Development Index District Level Household and Facility Survey District Primary Education Program Technical Diploma Economic Development Index Educational Progression Ratio Empowered Action Group Female Interstate Out-migration Rate Full Immunization Gross Domestic Product Gross National Income Government of India Gender Parity Index Healthcare Access and Quality Index Human Development Index Health Management Information System Inclusive Education of the Disabled at Secondary Stage Infant Mortality Rate Interstate Migration Survey International Organization for Migration xix

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IoT IPHS ISOMR IT KBK LEB LHV LISA MDGs MISOM MMR MOSPI MPCE MPI MYS MYSI NCERT NDT NEAG NFHS NHM NPEGEL NSS OLS PCNDDP PCA PCI PHC PNA POA PPP PPP PPR PSU RCH RDI RDP RGI RMSA RSM RTE RUSA SBA SC SCERT

Abbreviations

Internet of Things Indian Public Health Standards Interstate Out-migration Rate Information Technology Kalahandi-Bolangir-Koraput Life Expectancy at Birth Lady Health Visitor Local Indicators of Spatial Association Millennium Development Goals Male Interstate Out-migration Rate Maternal Mortality Ratio Ministry of Statistics and Program Implementation Monthly Per Capita Consumption Expenditure Mean Physical Infrastructure Mean Years of Schooling Mean Years of Schooling Index National Council of Educational Research and Training Non-Technical Diploma Non-Empowered Action Group National Family Health Survey National Health Mission National Programme for Education of Girls at Elementary Level National Sample Survey Ordinary Least Squares Per Capita Net District Domestic Product Primary Census Abstract Per Capita Income Primary Health Centre Postnatal Care Programme of Action Public-Private Partnership Purchasing Power Parity Parity Progression Ratio Primary Sampling Units Reproductive and Child Health Program Relative Development Index Relative Development Performance Registrar General of India Rashtriya Madhyamik Shiksha Abhiyan Reverse Survival Method Right to Education Rashtriya Uchchatar Shiksha Abhiyan Skilled Birth Attendance/Skilled Birth Attendants Sub-Centre State Council of Educational Research and Training

Abbreviations

SDG SLE SLEI SMAM SRB SRS SSA SDGs TFR TISOMR UHC UNDP UNESCO UTs U5MR WFPR WHO

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Sustainable Development Goal School Life Expectancy School Life Expectancy Index Singulate Mean Age at Marriage Sex Ratio at Birth Sample Registration System Sarva Shiksha Abhiyan Sustainable Development Goals Total Fertility Rate Total Interstate Out-migration Rate Universal Health Coverage United Nations Development Programme United Nations Educational, Scientific and Cultural Organization Union Territories Under-five Mortality Rate Work Force Participation Rate World Health Organization

List of Appendices

Appendix 1.1 Appendix 2.1 Appendix 2.2

Appendix 2.3

List of New Districts and Their Respective Parent Districts in Varying Census Years, 1991–2011 . . .. .. . .. .. . .. Assumptions on Fertility, Mortality and Sex Ratio at Birth by States of India for Population Projection . . . . . . . . Trends of Population, Population Density, Exponential Population Growth Rate, Proportion Urban Population, Child Sex Ratio and Sex Ratio in States and Districts of India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Trends of Proportion Population in Broad Age Groups, SMAM, Proportion of Population by Caste, Religion and Literacy Rate in States and Districts of India . . . . . . . . . . . . . . . .

8 37

39

91

Appendix 3.1

Trends of TFR (1991–2011) and Percentage of Currently Married Women Using Contraception, Percentage of Girls Marrying Below Age 18 and Unmet Need for Contraception in the Districts of India, 2015–2016 . . . . . . . . . 162

Appendix 4.1

Interstate Out-Migration Rate (ISOMR) and Composite Index of Development in the Districts of India, 2001 . . . . . . . 212 List of Top Fifty and Bottom Fifty Districts in Interstate Out-Migration Rate (ISOMR) and Composite Index of Development in India, 2001 . . .. . . . . . .. . . . . .. . . . . . .. . . . . . .. . 237 Intra-district and Intra-state (Within State Boundary) Out-Migration Rate (per 1000) by Sex (Based on Duration of Residence 0–9 Years) in Districts of India, 2001 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241

Appendix 4.2

Appendix 4.3

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Appendix 5.1

Appendix 5.2

List of Appendices

Mean Years of Schooling, School Life Expectancy, Composite Index of Education, Percentage of Graduates and Gender Parity Indices in Districts of India . . . . . . . . . . . . . . 282 Educational Progression Ratios in Districts of India, 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305

Appendix 6.1

Health Index, All India Rank in Health Index, and Rank of District within the State and All Districts of India, 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344

Appendix 7.1

Percentage Coverage of Antenatal Care, Skilled Birth Attendance, Postnatal Care and Immunization, MCH Index, Deprivation Score in the Districts of India, 2015–2016 . . . .. . . . . . . .. . . . . . . .. . . . . . . .. . . . . . . .. . . . . . . .. . . 389

Appendix 8.1

Status of Health Infrastructure in Primary Health Centers (PHCs) and Selected Reproductive Health Care Utilization Indicators in Districts of Rural India . . . . . . . . . . . . . 435

Appendix 9.1

Pattern and Ranking of Economic Development in Districts of India, 2011 . . .. . . . . .. . . . . . .. . . . . .. . . . . . .. . . . . .. . . . . . .. . . . . .. . . 490

Appendix 10.1

List of Top Fifty Rank and Bottom Fifty Rank Districts in District Development Index (DDI) in India, 2011 . . . . . . . . 531 Disability, District Development Index (DDI), All India Rank in DDI, Relative Development Index (RDI) and Rank of District within the State and All Districts of India, 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 533

Appendix 10.2

List of Figures

Fig. 2.1 Fig. 2.2 Fig. 2.3 Fig. 2.4 Fig. 2.5 Fig. 2.6

Fig. 3.1

Fig. 3.2 Fig. 3.3 Fig. 3.4 Fig. 3.5 Fig. 3.6

Fig. 4.1

Fig. 4.2

Population trends in India, 1951–2031 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Annual exponential growth rates of population (percent) in India, China and the world, 1951–2031 . . . . . . . . . . . . . . . . . . . . . . . . Kernal density plot of sex ratio and child sex ratio in the districts of India, 2001–2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Age sex pyramid of India for 2011, 2021 and 2031 . . . . . . . . . . . . . . Age dependency ratio in districts of India, 2001 and 2011 . . . . . . Population distribution of Scheduled Tribes Population in India, 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . (a) Total fertility rate (TFR) in the districts of India, 1991. (b) Total fertility rate (TFR) in the districts of India, 2001. (c) Total fertility rate (TFR) in the districts of India, 2011 . . . . . . Percentage of currently married women using any modern method of contraception in the districts of India, 2015–2016 . . . Percentage of girls aged 20–24 years marrying before age 18 in the districts of India, 2015–2016 .. . .. .. . .. . .. . .. .. . .. . .. TFR and percentage of women using any modern method of contraception in the districts of India, 2015–2016 .. . . . . . . . .. . . TFR and percentage of girls aged 20–24 years marrying below 18 years in districts of India, 2015–2016 . . . . . . . . . . . . . . . . . . TFR and total unmet need for family planning (%) in the districts of India, 2015–2016 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

23 23 28 29 32 34

151 154 155 156 157 157

Interstate out-migration rate (per 1000) by sex (based on duration of residence 0–9 years) in the districts of India, 2001 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 Scatter plot of interstate out-migration rate and composite index of development by sex in the districts of India . . . . . . . . . . . . 205

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Fig. 5.1 Fig. 5.2 Fig. 5.3 Fig. 5.4

Fig. 6.1 Fig. 6.2 Fig. 6.3 Fig. 6.4 Fig. 6.5 Fig. 7.1 Fig. 7.2 Fig. 7.3 Fig. 7.4 Fig. 7.5

Fig. 7.6 Fig. 7.7 Fig. 8.1 Fig. 8.2 Fig. 8.3 Fig. 8.4

Fig. 8.5

List of Figures

Mean years of schooling (7+ in India) in the districts of India, 2015–2016. (a) Total. (b) Male. (c) Female . . . . . . . . . . . . School life expectancy (6–24 years) in the districts of India, 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Percentage of graduates in the districts of India, 2011. (a) Total. (b) Male. (c) Female . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Educational progression ratio of completion of higher secondary post completion of secondary (EPR4) in the districts of India, 2011: (a) Total, (b) male, (c) female . . . . . . . . . . Scatter plot of percentage of children with diarrhoea and improved sanitation in the districts of India . . . . . . . . . . . . . . . . . . . . . . . Prevalence of diabetes (percentage) among any adult in the districts of India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Diabetes and hypertension (percentage) among adults in the districts of India, 2015–2016 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Percentage of disability among the elderly in the districts of India, 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Index of health in the districts of India, 2015–2016 . . . . . . . . . . . . . . Maternal child health index (MCH) across the states of India, 2015–2016 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Pattern of maternal and child health (MCH) index in the districts of India, 2015–2016 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Scatter plot of total fertility rate (TFR) and maternal and child health (MCH) index in the districts of India . . . . . . . . . . . Deprivation of maternal and child health in India, 2015–2016 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Deprivation of maternal and child health in bottom two districts (Mon and East Kameng) and top two districts (Kapurthala and Jagatsinghapur) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Deprivation score in states of India, 2015–2016 . . . . . . . . . . . . . . . . . . Quintile map for deprivation score in the districts of India . . . . . . Percentage of births by place of delivery in rural India, 2015–2016 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Percentage of rural women who availed three or more ANC visits by type of facilities in India, 2015–2016 . .. .. . .. .. . .. Percentage of PHCs following IPHS norms by states of India, 2012–2013 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Percentage of districts by PHCs following selected IPHS norms in India, non-EAG and EAG states, 2012–2013 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Percentage of districts by PHCs following IPHS norms in India, 2012–2013 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

267 270 272

277

336 337 338 339 340

381 382 384 385

386 387 387

423 425 426

426 427

List of Figures

Fig. 9.1

Fig. 9.2 Fig. 9.3 Fig. 9.4 Fig. 9.5 Fig. 9.6

Fig. 9.7

Fig. 9.8

Fig. 10.1

Fig. 10.2 Fig. 10.3 Fig. 10.4 Fig. 10.5 Fig. 10.6 Fig. 10.7 Fig. 10.8 Fig. 10.9

xxvii

(a) Economic development index (EDI) and per capita net district domestic product (PCNDDP) in the districts of Maharashtra. (b) Economic development index (EDI) and per capita net district domestic product (PCNDDP) in the districts of West Bengal . . . .. . . . . . . .. . . . . . .. . . . . . . .. . . . . . .. . . . . . . .. . . Economic development index (EDI) and poverty head count ratio in districts of India, 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Economic development index in districts of India, 2011 . . . . . . . . Percentage of households owning none of the specified assets in the districts of India, 2011 . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . Scatter plot of economic development index (EDI) and Moran’s I statistics in the districts of India, 2011 . . . . . . . . . . . . . . . . (a) Univariate LISA cluster map of economic development index (EDI) in India, 2011 (b) Univariate LISA significance map of economic development index (EDI) in India, 2011 . . . . . . (a) Bivariate LISA cluster map of economic development index (EDI) and TFR in India, 2011 (b) Bivariate LISA significance map of economic development index (EDI) and TFR in India, 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . (a) Bivariate LISA cluster map of economic development index (EDI) and U5MR in India, 2011 (b) Bivariate LISA significance map of economic development index and U5MR in India, 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . (a) District development index (DDI) and human development index (HDI) in the districts of Uttar Pradesh, 2011. (b) District development index (DDI) and human development index (HDI) in the districts of Maharashtra, 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . District development index (DDI) and level of urbanization in the districts of India, 2011 . . . . . . . . . . . . . . . . . . . . . . . . Distribution of districts by district development index (DDI) in India, 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . District development index (DDI) in India, 2011 . . . . . . . . . . . . . . . . . Total fertility rate (TFR) and district development index (DDI) in the districts of India, 2011 . . . . . . . . . . . . . . . . . . . . . . . . Moran’s I statistics of district development index in India, 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Morans’ I statistics of the district development index (DDI) in states with more than 17 districts, 2011 . . . . .. . . . .. . . . .. . LISA cluster map of district development index (DDI) in India, 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LISA significance map of district development index in India, 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

473 474 477 478 480

482

483

485

516 517 517 518 520 521 523 523 524

xxviii

Fig. 10.10 Fig. 10.11

Fig. 10.12

List of Figures

Bivariate Moran’s I statistics of district development index (DDI) and total fertility rate (TFR) in India, 2011 . . . . . . . . . 525 Bivariate Moran’s I statistics of the district development index (DDI) and total fertility rate (TFR) in states (with more than 17 districts), 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 525 (a) Bivariate LISA cluster map of district development index (DDI) and total fertility rate (TFR) in India, 2011 (b) Bivariate LISA significance map of district development index (DDI) and total fertility rate (TFR) in India, 2011 . . . . . . . . . 527

List of Tables

Table 1.1

Number of districts by states in India, 1991–2011 . . . . . . . . . . . . . . .

Table 2.1

Distribution of districts by size class of population in India 1991–2031 . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . Distribution of districts by exponential growth rate of population in 1991–2001 and 2001–2011 . . . . . . . . . . . . . . . . . . . . . . . . Distribution of districts by sex ratio and child sex ratio in India, 2001–2011 .. .. . .. .. . .. .. . .. .. . .. .. .. . .. .. . .. .. . .. .. . .. .. . .. Distribution of districts by various characteristics in India, 2001–2011 . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . Distribution of districts by literacy level in India, 2001–2011 . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . Distribution of districts by Caste and Religion in India, 2011 . . . .. . . . .. . . .. . . .. . . .. . . .. . . .. . . . .. . . .. . . .. . . .. . . .. . . .. .

Table 2.2 Table 2.3 Table 2.4 Table 2.5 Table 2.6 Table 3.1 Table 3.2 Table 3.3 Table 3.4

Table 3.5

Table 4.1 Table 4.2

Trends in total fertility rate (TFR) in selected states of India, 1991–2016 . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . Distribution of districts by level of TFR and percentage of population in India, 1991–2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fertility convergence across the districts of India, 1991–2011 . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . Mean TFRs by levels of TFR and selected distal and proximate determinants of fertility in the districts of India, 2015–2016 . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . Association of proximate determinants and socio-economic development indicators on fertility in the districts of India, 2015–2016 . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . .

6 25 26 28 31 33 36 150 153 154

158

160

Computation of dimensional indices based on census data, 2001 . .. . . . . .. . . . . . .. . . . . . .. . . . . . .. . . . . . .. . . . . . .. . . . . . .. . . . . . .. . . 202 Interstate out-migration rate (per 1000) by reason based on duration of last residence 0–9 years, 2001 . . . . . . . . . . . . . . . . . . . . . . . . 203 xxix

xxx

Table 4.3 Table 4.4

Table 4.5

List of Tables

Interstate out-migration rate by sex in India (duration of last residence 0–9 years) .. . .. . . .. . .. . .. . .. . .. . .. . . .. . .. . .. . .. . .. . .. . 205 Adjusted effects of selected background characteristics with interstate male/female out-migration in districts of India, 2001 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 Mean of interstate out-migration rate by independent variables and dimensional indices of development in India, 2001 .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . 207

Table 5.1

Summary statistics and distribution of districts by levels of educational indices, India, 2015–2016 . . . . . . . . . . . . . . . . . . 266

Table 6.1

Methodology and descriptive statistics of variables used in composite index of health in the districts of India, 2015–2016 . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . Distribution of districts by selected health indicators in India, 2015–2016 .. .. . .. .. . .. .. . .. .. . .. .. .. . .. .. . .. .. . .. .. . .. .. . .. Composite index of health (mean) by selected variables in the districts of India, 2015–2016 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Number of districts classified in the index of child health and adult health in India, 2016 . . .. . .. . . .. . . .. . .. . . .. . .. . . .. . . .. . .. . Joint probability of index of child health and index of adult health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Number of districts in the index of child and elderly health in India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Table 6.2 Table 6.3 Table 6.4 Table 6.5 Table 6.6 Table 7.1 Table 7.2 Table 7.3 Table 8.1 Table 8.2 Table 9.1 Table 9.2 Table 9.3

333 334 341 341 342 342

Definition, levels and change in selected maternal and child health indicators in India, 2005–16 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379 Correspondence analysis of MCH index with selected indicators . . .. . .. . .. . .. .. . .. . .. . .. . .. . .. .. . .. . .. . .. . .. .. . .. . .. . .. . .. .. . 383 Mean MCH index value by the level of TFR and MCH index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 384 Group of states by infrastructure at primary health centres, 2012–2013 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 428 Effect of health infrastructure in primary healthcare centres on healthcare utilization in the districts of India . . . . . . . . . 431 Methodology used in computing economic development index (EDI) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 471 Distribution of districts in the economic development index by states in India, 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 476 Economic development index (EDI) and 95% confidence interval by selected demographic and developmental variables in India, 2011 . . .. . . . .. . . . . .. . . . . .. . . . .. . . . . .. . . . . .. . . . . .. . 479

List of Tables

xxxi

Table 9.4

Univariate Moran’s I statistics of economic development index (EDI) and bivariate Moran’s I statistics of EDI, TFR and U5MR in states of India, 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . 481

Table 10.1

Methodology in computing district development index (DDI) . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . .. . . . .. . . . .. . . 512 District development index and 95% confidence interval by selected demographic and developmental variables in India, 2011 .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . . .. . 519

Table 10.2

Chapter 1

Contextualising Demographic and Development Divide in Districts of India Sanjay K. Mohanty, Udaya S. Mishra, and Rajesh K. Chauhan

Abstract The Indian districts are perfect laboratory to understand the demographic diversity, pattern of development and test the newer hypotheses. Besides, districts are the basic administrative unit and the periodic assessment on spatial pattern of development is an essential input in national and regional planning. While data limitation is often cited for limited district-specific analyses, the data gap in many key variables is bridging over time. This chapter describes the theoretical rationale of understanding the demographic and development divide in districts of India.

Global Pattern of Demography and Development Demographic transition and socioeconomic development are concomitant among and within countries. Though demographic transition has become universal the demographic divide with respect to population size, population growth age and sex structure and geographical distribution have dispersed over time. The world population was 2.54 billion in 1950, 5.33 billion in 1990 and 7.55 billion in 2017 and projected to reach 9.77 billion in 2050. The share of Europe in world population has declined from 21.67% in 1950 to 9.83% in 2017 while that of Africa has increased from 9.02% to 16.64% during this period (www.esa.un.org). Though countries are converging with regard to longevity and child survival, they seem to display limited convergence in fertility trends (Wilson 2001; Dorius 2008). On the other hand, the disparity in the level, growth and pattern of development has widened over time. The largest divide is often observed in per capita income. For example, in 1950, the ratio of gross domestic product (GDP) per capita at 1990 purchasing power parity (PPP) S. K. Mohanty (*) Department of Fertility Studies, International Institute for Population Sciences, Mumbai, Maharashtra, India U. S. Mishra Centre for Development Studies, Thiruvananthapuram, Kerala, India R. K. Chauhan Directorate of Economics & Statistics, Planning Department, Government of Uttar Pradesh, Lucknow, Uttar Pradesh, India © Springer Nature Singapore Pte Ltd. 2019 S. K. Mohanty et al. (eds.), The Demographic and Development Divide in India, https://doi.org/10.1007/978-981-13-5820-3_1

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S. K. Mohanty et al.

of Western Europe and sub-Saharan Africa was 5.35, which increased to 14.07 in 2010 (Bolt et al. 2014). Global inequality, measured by Gini index remained high – nearly 0.722 in 1988, 0.715 in 1998 and 0.705 in 2008 (Lakner and Milanovic 2015). Countries are also diverging in consumption, wealth and technological knowhow. The disparity in education and health remains high with a systematic response to demographic change. Realising the trend, reduction of inequality within and among the countries, it has been placed in the global development agenda (SDGs 10) (UN 2015). A large body of literature has established the short- and long-run benefits of demographic change on developmnetal outcome within and among countries. Specifically, effect of fertility and mortality reduction on economic growth, educational attainment, work participation, poverty reduction and improvement in the health of the population has been extensively documented (Aiyar and Mody 2012; Bloom et al. 2000, 2001, 2002; Dreze and Murthi 2001; Merrick 2002) Studies also suggest that economic inequality within countries is increasing and contributes to large variations in overall inequality (Lakner and Milanovic 2015; Ravallion 2014; Fosu 2009). The pace of demographic change, levels and patterns of economic growth, educational progress and the health outcome remain distinct for each country and are context specific. Goal 10 of Sustainable Development Goal (SDG) aimed to reduce ineqaulity within and among the countries (UN 2015).

Demographic and Development Dichotomy in India India, the second largest country with a population of 1.3 billion in 2016, is undergoing demographic, epidemiological and economic transition. During the last two decades, the country has made significant progress in the key dimensions of human development – health, education and standard of living. On the demographic front, the total fertility rate (TFR) has declined from 5.2 in 1971 to 2.3 in 2017, and life expectancy at birth (a measure of health) has increased from 58.7 years in 1990 to 68.7 years in 2014 (ORGI 2018). The infant mortality rate (IMR) has come down from 129 per 1000 live births in 1971 to 34 per 1000 live births in 2016 (ORGI 2009; 2017). The maternal mortality ratio (MMR) too has come down from a level of 398 in 1997–1998 to 130 per 100,000 live births in 2014–2016 (ORGI 2006; 2018). The literacy level has recorded a notable improvement from 52% in 1991 to 74% in 2011 (Census of India 2011). The expected years of schooling have increased from 7.7 years in 1990 to 11.7 years in 2012, and the mean years of schooling have increased over 2 years. The gross national income (GNI) per capita (at 2011 PPP$) has increased from 1754 to 4909 US$, making India a fast-growing economy (www. data.worldbank.org). In the composite index of human development, the country has moved up from 0.43 in 1990 to 0.60 by 2012 (UNDP 2015). The percentage of

1 Contextualising Demographic and Development Divide in Districts of India

3

population living below poverty line (as per Tendulkar Committee) has declined from 37.2% in 2004–2005 to 21.9% in 2011–2012 (Planning Commission 2014). Despite these improvements in various dimensions, undernutrition among children remains high along with the emergence of non-communicable diseases that are the leading cause of mortality, hospitalisation and disability. The gini index, measured from consumption expenditure, has increased from 0.30 in 1992–93 to 0.36 by 2011–12. Regional inequality in developmental variables manifests a wider divide over time (Sen and Himanshu 2004; Kurian 2000; Kalra and Thakur 2015; Mukherjee et al. 2014). We have used the term “dichotomy” to describe the inter-district variation in demographic and developmental parameters within and among states of India. Though a large number of Indian states are realising the demographic targets and reaching the replacement level of fertility, the inter-district variations remained large. The inter-district variations in developmental parameters are even larger than the demographic variables. Also, the pace of demographic transition is affecting the growth and pattern of development at state and district level.

Why the Demography and Development Divide in the Districts of India? The emergence of a whole host of indicators in recent times is least exploited by policy-makers. Indicators should be utilized beyond indication. More of the disaggregated information should result in making aggregates robust in terms of representation by accounting for the differences and disparities in them. Gauging development without demography can sometimes be naïve. Development read with demographics lenses not only unfolds its complexity but also informs accurately regarding its future trajectory. Hence, this attempt at reading both demography and development side by side should serve towards making demographic assessment the mainstay of evaluating development. The reason and rationale behind district level analyses of demographic and developmental variables have been amply justified in literature (Drèze and Murthi 2001; Mohanty et al. 2016a, b). In recent years, there is an increasing efforts towards obtaining demographic estimates in the districts of India (Kumar and Sathyanarayana 2012; Guilmoto and Rajan 2013; Singh et al. 2017). However, similar attempts at examining differences in socioeconomic development at the district level disaggregation remain limited (Chaudhuri and Gupta 2009; Ohlan 2013; Mohanty et al. 2016a, b). While earlier, this was primarily due to data limitations, such limitations can be overcome with information on key variables being generated at the district level disaggregation. This book serves towards presenting empirical evidence on demographic and developmental variables in the districts of India.

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S. K. Mohanty et al.

The motivation behind reading the demographic and developmental divide in the districts of India is prompted by the following: 1. Demographic variables are integral component of manpower planning, educational planning and health planning and determine the size of domestic and international markets. Though district level information is increasingly available in various forms at different places, comprehensive estimates are not available. While some indicators are readily available, newer indicators need to be estimated from the unit record data. 2. The district is the basic administrative unit of India with an average population of over two million. According to the last Census in 2011, there were 640 districts that were spread over 29 states and 7 union territories in the country. The state average in key demographic and development indicators conceals large variation across districts in India. The state and central governments often sought demographic and developmental variables at the district level and a number of committees and commissions have been set up to designate backward regions in the country with special focus on districts. The demographic and developmental indicators at micro regions are thus essential input for evidence-based planning, allocation of resources and special assistance programmes. Hence, periodic assessment on spatial pattern of development is an essential input in national and regional planning. Besides, understanding spatial pattern of development is a regular exercise among academia and researchers. 3. The number of districts in India is large, and they exhibit enormous variations in demographic, social and economic development. Thus, Indian districts are a perfect laboratory to understand the pattern of development and diversity to offer fresh hypothesis for exploration. For example, in 2011, the female literacy rate ranged between 30.29% in Alirajpur district of Madhya Pradesh and 97.67%, the highest in Aizawl district of Mizoram. About seven districts had cent percent urbanization, while ten districts had no urban area. On the demographic front, the total fertility rate (TFR) varied from 1.1 in Kolkata district of West Bengal to 5 in Khagaria district of Bihar. Similar variations are found in other key indicators of development as well. 4. The extent of inequality in key dimensions of development remains large with respect to region, gender and income. While there is considerable amount of literature at state and household level, there are a limited number of studies that examine the spatial pattern of development and demography in the districts. 5. District level analyses could capture the diffusion effect of fertility and other social variables (Drèze and Murthi 2001). Given the size, diversity and growth of Indian districts, the district-specific analyses are of immense use to multiple stakeholders. Hence sub-national analyses on the linkage between demography and development are rewarding and would be useful for multiple stakeholders.

1 Contextualising Demographic and Development Divide in Districts of India

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Core Argument The visible progress in demographic and developmental indicators in the states conceals large differences across districts both within the state and among all the districts in the country. Also, the observed pattern of development in the districts remains clustered. Reduction in regional disparity requires comprehensive strategies in improving health, education and increasing standard of living. The central and state governments may make use of empirical evidences in devising strategies towards developing poorer regions for balanced regional development.

Approach The approach of this book is to examine the subnational variations in key demographic and development indicators in India. The district is the unit of analysis in all the nine analytical chapters. These chapters cover a broad range of topics concerning the key domains of human development – education, health and income. The data used are from the Census of India, National Family and Health Survey (NFHS) 4, District Level Household and Facility Survey (DLHS). The unique feature of the Census of India is its complete coverage. We have used data from the Census of India to estimate some indicators relating to age structure, migration and education. Data from three reseach papers; on child mortality by Ram et al. (2013) and district estimates on total fertility rate and estimates of poverty and inequality by Mohanty et al. (2016a, b) has been used. Descriptive analyses, composite indices and regression analyses are used. Maps are presented in each of the analytical chapters. Table 1.1 presents the number of districts during three Census years – 1991, 2001 and 2011. The number of districts has increased from 466 in 1991 to 593 in 2001 and 640 in 2011 and 706 in 2018. Since the Census of India and NFHS 4 form the main database, we have considered 640 districts according to Census 2011 in all the chapters, except in Chap. 4. Appendix 1.1 provides the list of districts that were created between 1991 and 2001 and 2001 and 2011. The state of Telangana was created in 2014 by taking ten districts from the erstwhile state of Andhra Pradesh.

Structure of the Book The book is structured in two sections – section one deals with demographic divides in the districts of India and section two deals with the development divide in the districts of India. The first section comprises four chapters including the introductory chapter, and the second section comprises six analytical chapters. The nine analytical chapters deal with a wide range of population and developmental issues in the

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S. K. Mohanty et al.

Table 1.1 Number of districts by states in India, 1991–2011 States of India Andaman and Nicobar Islands Andhra Pradesh (erstwhile) Arunachal Pradesh Assam Bihar Chandigarh Chhattisgarh Dadra and Nagar Haveli Daman and Diu Goa Gujarat Haryana Himachal Pradesh Jammu and Kashmir Jharkhand Karnataka Kerala Lakshadweep Madhya Pradesh Maharashtra Manipur Meghalaya Mizoram Nagaland Delhi Odisha Puducherry Punjab Rajasthan Sikkim Tamil Nadu Tripura

Number of districts in 1991 2

Number of districts created between 1991 and 2001

Number of districts created between 2001 and 2011 1

23

11 23 29 1 7 1

23

2

3

16

8

4 1

9

2

27 38 1 18 1

2 2 19 16 12

Total number of districts in 2011 3

2

6 3

14

1 2

2 26 21 12

8

22 24 30 14 1 50

13 20 14 1 38

5 7

6 3

7

5

30 8 5 3 7 1 13 4 12 27 4 21 3

5 1 2 5 1 8 17

3

5 5

3 1

9 1

2

35 9 7 8 11 9 30 4 20 33 4 32 4 (continued)

1 Contextualising Demographic and Development Divide in Districts of India

7

Table 1.1 (continued) States of India Uttar Pradesh Uttarakhand West Bengal All India

Number of districts in 1991 54 9 17 466

Number of districts created between 1991 and 2001 16 4 1 127

Number of districts created between 2001 and 2011 1 1 47

Total number of districts in 2011 71 13 19 640

districts of India. These include population trends and future population prospects, fertility trends and proximate determinants, interstate out-migration from the district, educational progress, state of health, economic development and overall level of development in 640 districts of India. A brief description of each of the chapters is given below. Chapter 2 presents population size, growth, distribution and projected population for the districts of India. Dependency ratio, median age and singulate mean age at marriage are computed for the districts. Given the change in the number of districts, the revised population of each district has been presented. We have also provided the projected population for each of the 640 districts for 2021 and 2031. Fertility transition in the districts is explored in Chap. 3. It provides district level estimates of the total fertility rate during the last two decades and the proximate determinants based on the recently conducted National Family Health Survey (NFHS) 4. Chapter 4 presents interstate out-migration and its association with the level of development in the districts. Since, recent migration data of Census 2011 at the district level is yet to be released, the same exercise was carried out using 2001 Census of India. Chapter 5 elaborates on the progress of education in the districts. The main contribution of this chapter relates to the estimation of educational progression ratio, school life expectancy and the mean years of schooling by sex, which were earlier not available. Chapter 6 deals with the state of health in the districts. It combines the state of child health, adult health and elderly health and depicts the overall health with the help of a composite index. In Chap. 7, a composite index of maternal health and the shortfall in maternal health is estimated for each of the districts. Chapter 8 depicts the state of public health infrastructure by taking the primary health centre as the case. The state of economic development and the overall level of development in the districts have been discussed in Chaps. 9 and 10 respectively. Spatial analysis is used in both these chapters to understand the clustering of development. Besides, bivariate and multivariate analyses have been performed to understand associations between varied attributes. Spatial analyses is complemented with LISA cluster maps. Moran’s I statistics are computed to understand the extent of spatial clustering in the level of development. Districts are ranked based on the composite index of development within the state, and Relative Development Index (RDI) has also been computed.

8

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Backward districts within and across the states of India have been identified. Chapter 11 sums up the highlights of the various chapters and concludes. We believe that the book will serve as a ready reference to multiple stakeholders – central and state governments, district administrators, academia and researchers. With comprehensive information on demographic and development attributes in one place, potential hypothesis linking various dimensions could be verified using this data. On the whole, the book could be a model for exploring disaggregated information in districts of India and may serve as a reference for policy-makers, programme managers, researchers and students.

Contribution The book makes two major contributions. It is a maiden attempt at presenting comprehensive information on demographic and developmental indicators at the district level for the nation as a whole. To our knowledge, there is no other book that contains such disaggregated information in one place. Apart from the rich information set, it presents nine analytical chapters elaborating on the state of demographic and development divides in the districts of India. Each chapter provides estimates for a fresh set of indicators and its association with demographic/developmental variables. Each chapter is supported by an appendix containing key indicators for all 640 districts of India. Districts are ranked according to key developmental indicators across all districts in the country and among the districts within the state. This book is a ready reference for users interested in examining the regional pattern of differences and disparities in India.

Appendix 1.1 List of New Districts and Their Respective Parent Districts in Varying Census Years, 1991–2011

States/Union Territories Andaman and Nicobar Islands Arunachal Pradesh

Districts created between 1991–2001

Parent districts from which new districts were created between 1991–2001

Districts created between 2001–11 South Andaman

Papum Pare

Lower Subansiri

Upper Siang

East Siang

Kurung Kumey Anjaw Lower Dibang Valley

Parent districts from which new districts were created between 2001–11 North and Middle Andaman Lower Subansiri Lohit Dibang Valley (continued)

1 Contextualising Demographic and Development Divide in Districts of India

States/Union Territories Assam

Districts created between 1991–2001

Parent districts from which new districts were created between 1991–2001

Districts created between 2001–11 Udalguri Chirang

Kamrup Metropolitan Baksa

Bihar

Chhattisgarh

Gujarat

Banka Buxar Supaul Kaimur (Bhabhua) Sheohar Jamui Lakhisarai Sheikhpura Korea Kabirdham Janjgir-Champa Mahasamund Kanker (Uttar Bastar) Korba Jashpur Dantewada (Dakshin Bastar) Dhamtari Anand Dohad Navsari Patan Porbandar Narmada

Bhagalpur Bhojpur Saharsa Rohtas Sitamarhi Munger Munger Munger and Nalanda Surguja Rajnandgaon and Bilaspur Bilaspur Raipur Bastar

Arwal

9

Parent districts from which new districts were created between 2001–11 Darrang and Sonitpur Kokrajhar and Bongaigaon and Barpeta Kamrup Barpeta and Kamrup and Nalbari Jehanabad

Narayanpur Bijapur

Bastar Dantewada (Dakshin Bastar)

Tapi (Vyara)

Surat

Bilaspur Raigarh Bastar

Raipur Bhavnagar and Amreli and Kheda Panchamahal Valsad Mehsana and Banaskantha Junagarh Bharuch and Vadodara

(continued)

10

States/Union Territories Haryana

S. K. Mohanty et al.

Districts created between 1991–2001 Panchkula Jhajjar Fatehabad

Parent districts from which new districts were created between 1991–2001 Ambala Rohtak and Rewari Hisar

Ramban

Jammu and Kashmir

Jharkhand

Karnataka

Madhya Pradesh

Districts created between 2001–11 Palwal Mewat

Chatra Pakur Bokaro

Ganderbal Bandipore Reasi Kulgam Kishtwar Samba Shopian Khunti Latehar Ramgarh

Kodarma

Hazaribagh Sahibganj Dhanbad and Giridih Hazaribagh

Garhwa

Palamu

Chamarajanagar

Mysuru

Gadag Haveri Bagalkot Udupi Koppal Davanagere

Dharwad Dharwad Vijayapura Dakshina Kannada Raichur Chitradurga and Shivamogga and Ballari Mandsaur Hoshangabad

Ramanagara Chikaballapura

Jabalpur Mandla Khargone (West Nimar) Morena Shahdol

Singrauli Alirajpur Anuppur

Neemuch Harda Katni Dindori Barwani Sheopur Umaria

Seraikella Kharsawan Simdega Jamtara Yadgir

Ashoknagar Burhanpur

Parent districts from which new districts were created between 2001–11 Faridabad Gurgaon Doda and Udhampur Srinagar Baramulla Udhampur Anantnag Doda Jammu and Kathua Pulwama Ranchi Palamu Hazaribagh West Singhbhum Gumla Dumka Kalaburagi (Gulbarga) Bengaluru Rural Kolar

Guna Khandwa (East Nimar) Sidhi Jhabua Shahdol

(continued)

1 Contextualising Demographic and Development Divide in Districts of India

States/Union Territories Maharashtra

Manipur Meghalaya

Mizoram

Nagaland

Delhi

Odisha

Districts created between 1991–2001 Washim Nandurbar Gondia Mumbai Suburban Hingoli Imphal East South Garo Hills Ri Bhoi Champhai Mamit Lawngtlai Kolasib Serchhip Dimapur

North Delhi West Delhi South Delhi New Delhi North East Delhi East Delhi North West Delhi Central Delhi Bhadrak Malkangiri Gajapati Nayagarh Sonepur Rayagada Angul Jajpur Bargarh Kandhamal Jharsuguda

Parent districts from which new districts were created between 1991–2001 Akola Dhule Bhandara Greater Bombay

11

Districts created between 2001–11

Parent districts from which new districts were created between 2001–11

Kiphire Peren Longleng

Tuensang Kohima Tuensang

Parbhani Imphal West Garo Hills East Khasi Hills Aizawl Aizawl Chimpuitui Aizawl Aizawl Kohima

Delhi Delhi Delhi Delhi Delhi Delhi Delhi Delhi Balasore Koraput Ganjam Puri Balangir Koraput Cuttack Cuttack Sambalpur Phulabani Sambalpur (continued)

12

S. K. Mohanty et al. Parent districts from which new districts were created between 2001–11

Districts created between 1991–2001 Jagatsinghapur

Parent districts from which new districts were created between 1991–2001 Cuttack

Punjab

Deogarh Kendrapara Khordha Nabarangapur Nuapada Muktsar

Sambalpur Cuttack Puri Koraput Kalahandi Faridkot

Patiala Faridkot Bathinda Jalandhar

Rajasthan

Fatehgarh Sahib Moga Mansa Shahid Bhagat Singh Nagar Rajsamand

Udaipur

Pratapgarh

Chittorgarh and Udaipur and Banswara

Baran Karauli Dausa Hanumangarh Ariyalur Thiruvarur

Kota Sawai Madhopur Jaipur Sri Ganganagar Trichirapalli Thanjavur

Krishnagiri Tiruppur

Dharmapuri Erode and Coimbatore

Theni Cuddalore Perambalur Namakkal Karur Kancheepuram Nagapattinam Dhalai

Madurai South Arcot Tiruchirapalli Salem Trichirapalli Chengalpattu Thanjavur North Tripura and South Tripura Bahraich

Kanshiram Nagar

Etah

States/Union Territories

Tamil Nadu

Tripura Uttar Pradesh

Shravasti Kaushambi Sant Kabir Nagar Amroha (Jyotiba Phule Nagar) Auraiya

Districts created between 2001–11

Sahibzada Ajit Singh Nagar (Mohali) Tarn Taran Barnala

Rupnagar and Patiala Amritsar Sangrur

Allahabad Basti and Siddharth Nagar Moradabad

Etawah (continued)

1 Contextualising Demographic and Development Divide in Districts of India

States/Union Territories

Districts created between 1991–2001 Hathras Kushinagar Kannauj Balrampur Gautam Buddha Nagar Baghpat

Uttarakhand

Chandauli Bhadohi Mahoba Ambedkar Nagar Chitrakoot Bageshwar Champawat Udham Singh Nagar Rudraprayag

West Bengal

Dakshin Dinajpur

Parent districts from which new districts were created between 1991–2001 Mathura and Aligarh

Districts created between 2001–11

Parent districts from which new districts were created between 2001–11

Purba Medinipur

Paschim Medinipur

13

Deoria Farukkhabad Gonda Ghaziabad and Bulandshahar Meerut and Ghaziabad Varanasi Varanasi Hamirpur Faizabad (Ayodhya) Banda Almora Pithoragarh and Udham Singh Nagar Nainital Chamoli and Tehri Garwal and Pauri Garhwal West Dinajpur

Name of Phulbani has been changed to Kandhamal Source: ORGI (2011), Administrative Atlas of India

References Aiyar, S., & Mody, A. (2012). The demographic dividends: Evidences from the Indian states (IMF Working paper, 11/38). http://www.imf.org/external/pubs/ft/wp/2011/wp1138.pdf Bloom, D. E., Canning, D., & Malaney, P. L. (2000). Demographic change and economic growth in Asia. Population and Development Review, 26(Suppl), 257–290. Bloom, D. E., Canning, D., & Sevilla, J. (2001). Economic growth and demographic transition (Working paper 8685). http://www.nber.org/papers/w8685 Bloom, D. E., Canning, D., & Seveilla, J. (2002). The demographic dividend: A new perspective on the economic consequence of population change (Population Matters Monograph MR-1274). RAND, Santa Monica. Bolt, J., Timmer, M., & van Zanden, J. L. (2014). GDP percapita since 1820. In J. L. van Zanden et al. (Eds.), How was life?: Global well-being since 1820. Paris: OECD Publishing. https://doi. org/10.1787/9789264214262-7-en.

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Chaudhuri, S., & Gupta, N. (2009). Levels of living and poverty patterns: A district-wise analysis for India. Economic and Political Weekly, 44, 94–110. Census. (2011). Administrative Atlas of India, Registrar General of India, Ministry of Home Affairs, Government of India. Available at: http://censusindia.gov.in/2011census/maps/admin istrative_maps/Final%20Atlas%20India%202011.pdf. Drèze, J., & Murthi, M. (2001). Fertility, education, and development: evidence from India. Population and development Review, 27(1), 33-63. Dorius, S. F. (2008). Global demographic convergence? A reconsideration of changing intercountry inequality in fertility. Population and Development Review, 34(3), 519–537. Drèze, J., & Murthi, M. (2001). Fertility, education, and development: Evidence from India. Population and Development Review, 27(1), 33–63. Fosu, A. K. (2009). Inequality and the impact of growth on poverty: Comparative evidence for sub-Saharan Africa. The Journal of Development Studies, 45(5), 726–745. Guilmoto, C. Z., & Rajan, S. I. (2013). Fertility at the district level in India. Economic and Political Weekly, 48(23), 59–70. Kalra, R., & Thakur, S. (2015). Development patterns in India: Spatial convergence or divergence? GeoJournal, 80(1), 15–31. Kumar, S., & Sathyanarayana, K. M. (2012). District-level estimates of fertility and implied sex ratio at birth in India. Economic and Political Weekly, 47(33), 66–72. Kurian, N. J. (2000). Widening regional disparities in India: Some indicators. Economic and Political Weekly, 35, 538–550. Lakner, C., & Milanovic, B. (2015). Global income distribution from the fall of the Berlin Wall to the Great Recession. Revista de Economía Institucional, 17(32), 71–128. Available at: http:// www.scielo.org.co/scielo.php?script¼sci_arttext&pid¼S0124-59962015000100004 Merrick, T. W. (2002). Population and poverty: New views on an old controversy. International Family Planning Perspectives, 28(1), 41. Mohanty, S. K., Fink, G., Chauhan, R., & Canning, D. (2016a). Distal determinants of fertility decline: Evidence from 640 Indian districts. Demographic Research, 34, 373–406. Mohanty, S. K., Govil, D., Chauhan, R. K., Kim, R., & Subramanian, S. V. (2016b). Estimates of poverty and inequality in the districts of India, 2011–2012. Journal of Development Policy and Practice, 1(2), 142–202. Mukherjee, S., Chakraborty, D., & Sikdar, S. (2014). Three decades of human development across Indian states: Inclusive growth or perpetual disparity? National Institute of Public Finance and Policy, New Delhi “Proposed Sustainable Development Report of Indian States” (2013), Housing & Urban Affairs Division, Planning Commission. Office of the Registrar General of India (ORGI). (2006). Maternal mortality in India: 1997–2003 trends, causes and risk factors. New Delhi: Office of the Registrar General. Office of the Registrar General of India (ORGI). (2009). Compendium of India’s ferility and mortality indicators 1971–2007. New Delhi: Office of the Registrar General. Office of the Registrar General of India (ORGI). (2017). Sample registration system bulletin. Office of the Registrar General of India (ORGI). (2018). SRS based abridged life tables, 2012–2016 (Registrar General of India SRS Analytical Report). New Delhi: Registrar General of India, Government of India. Ohlan, R. (2013). Pattern of regional disparities in socio-economic development in India: District level analysis. Social Indicators Research, 114(3), 841–873. Planning Commission. (2014). Report of the expert group to review the methodology for measurement of poverty. New Delhi: Government of India. Ram, U., Jha, P., Ram, F., Kumar, K., Awasthi, S., Shet, A., & Kumar, R. (2013). Neonatal, 1–59 months, and under-5 mortality in 597 Indian districts, 2001 to 2012: Estimates from national demographic and mortality surveys. The Lancet Global Health, 1(4), e219–e226. Ravallion, M. (2014). Income inequality in the developing world. Science, 344(6186), 851–855. Sen, A., & Himanshu. (2004). Poverty and inequality in India: I. Economic and Political Weekly, 39, 4247–4263.

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Singh, A., Kumar, K., Pathak, P. K., Chauhan, R. K., & Banerjee, A. (2017). Spatial patterns and determinants of fertility in India. Population, 72(3), 505–526. UN. (2015). Final list of proposed sustainable development goal indicators. Retrieved from https://sustainabledevelopment.un.org/content/documents/11803Official-List-of-ProposedSDG-Indicators.pdf UNDP. (2015). Human development report. New York: Palgrave Macmillan. Wilson, C. (2001). On the scale of global demographic convergence 1950–2000. Population and Development Review, 27(1), 155–171. https://data.worldbank.org/indicator/NY.GDP.PCAP. PP.KD?end¼2017&locations¼IN&name_desc¼false&start¼2017&view¼bar. Accessed on 28 July 2018. https://esa.un.org/unpd/wpp/DataQuery/. Accessed on 28th July 2018.

Chapter 2

Population Trends, Distribution and Prospects in the Districts of India Rajesh K. Chauhan, Sanjay K. Mohanty, and Udaya S. Mishra

Abstract Poised to become the most populous country of the world, India exhibits vast geographic variations in the size, composition and distribution of the population. The national and state average conceals large disparities in demographic variables across the districts of India. This chapter examines the population size, distribution, composition and selected characteristics in 640 districts of India. Recasted data for the Census of India 1991, 2001 and 2011 have been used. Districts of 2011 have been taken as the basis for comparison of various characteristics across the years 1991 and 2001. Results suggest that the projected population of India are likely to be 1.35 billion by 2021 and 1.47 billion by 2031. India’s share of global population is likely to rise from 14.8% in 1951 to 17.7% in 2031. The average population size per district is likely to increase from 1.3 million in 1991 to 2.3 million in 2031. This increase in population is inevitable despite the fact that the annual exponential growth rate of population of 1.95% in 1991–2001 is expected to decline by half and is estimated to become 0.87% during 2021–2031.There is a clear north-south divide in demographic characteristics among the states and districts in India. With variations across districts, the child sex ratio presents a discouraging picture between 2001 and 2011. Median age and singulate mean age at marriage (SMAM) of the population are increasing, and dependency ratio is decreasing over time. The literacy level and the gender gap in the literacy level have declined over time. The demographic divide in the districts of India has been large and is likely to increase in the coming years.

R. K. Chauhan (*) Directorate of Economics & Statistics, Planning Department, Government of Uttar Pradesh, Lucknow, Uttar Pradesh, India S. K. Mohanty Department of Fertility Studies, International Institute for Population Sciences, Mumbai, Maharashtra, India U. S. Mishra Centre for Development Studies, Thiruvananthapuram, Kerala, India © Springer Nature Singapore Pte Ltd. 2019 S. K. Mohanty et al. (eds.), The Demographic and Development Divide in India, https://doi.org/10.1007/978-981-13-5820-3_2

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Keywords India · District · Population growth · Age structure · Age dependency ratio · Median age · Singulate mean age at marriage · Urbanization

Introduction Global progress on population stabilization, attaining the Sustainable Development Goals (SDGs) and improving the overall level of human development is contingent on India’s progress in realizing its demographic targets. The population of India has increased from 361 million in 1951 to 1211 million in 2011 and projected to be 1474 million by 2031. Though the population growth rate in India has slowed down from 2.31% in 1971–1981 to 1.52% in 2001–2011, it is likely to be the most populous country in near future (UN 2018). The population trends are determined by past trends and current levels of fertility, mortality and migration. Fertility, mortality and migration are governed by a set of social, economic, cultural and political factors. The demographic variables such as age and sex structure, geographical distribution and social composition are essential ingredients of educational and health planning, economic growth, manpower supply, employment, poverty reduction, saving and investment and reproductive potential. Population composition by social composition is relevant for targeting public schemes and augmenting the benefits for the socioeconomically deprived. The disaggregated information on demographic estimates and future projections are of immense use for planning, policy formulation, administration and research. The sex ratio, defined as number of females per 1000 male population, has been unfavourable to females in India. Griffiths et al. (2000) infer that persisting small differences in mortality at young ages along with skewed sex ratio at birth result in a highly masculine population sex ratio in India. Sachar and Soni (1995) observes that difference in sex ratio can also be attributed to a higher number of males being born probably as a result of selective abortion of female fetuses. India’s demographic scenario presents some opportunities to realise demographic dividend and interstate migration in some areas can arrest labor shortage, but there are serious challenges addressing the issue of skewed sex ratio and enhancing human capital (James 2011). The Northern hindi-speaking belt has lacked demographically, and the sex ratio at birth remained high. The preference for sons is reduced when the ideal family size becomes small, even though it does not completely disappear (Bhat and Zavier 2003). The national average in demographic trends conceals large variations across the states and districts of India. The north-south dichotomy in population growth among India’s states has raised debate and discussion. The recent controversy in financial allocation to the states of India based on population size reiterates the need for

2 Population Trends, Distribution and Prospects in the Districts of India

19

understanding the robust demographic variables in decision-making (The Hindu, March 29, 2018; April 14, 2018). The population growth rate during 2001–2011 varies from 0.48% in the state of Kerala to 4.44% in the state of Dadra and Nagar Haveli (Census 2011). A total of 24 states and union territories (out of 36) have reached the replacement level of fertility (IIPS and ICF 2017). The demographic variations are even larger among districts within the state and in the country. Specifically, the population growth, distribution, composition and its future potential are distinct for many districts of India. As of 2011, India has 640 districts across 29 states and 7 union territories (the state of Telangana was created after census of India 2011). In 2011, the average population size of an Indian district was 2.3 million, and Indian districts vary enormously in many demographic parameters. The demographic variables are customarily analysed at the state level and less at the district level. Population distribution along with its composition and characteristics across varying levels of administrative segregation in the districts assumes significance from numerous standpoints. Population size, growth and distribution of population convey population concentration in one region compared to others. Such concentration indicated in terms of density becomes important given its implication in efficient provisioning of infrastructure and services. Similarly, the composition and characteristics of the population become relevant towards assessment of differential needs and priorities of the regions with regard to provisioning of services. Given the significance of population dynamics at the disaggregated level, this chapter presents the population size, growth, distribution, sex ratio, child sex ratio (number of females per 1000 males in 0–6 age group) and population composition (caste and religion) in 640 districts of India. The specific objectives of this chapter are to examine the population growth, distribution and composition and project population in districts of India. In addition, the median age, singulate mean age at marriage (SMAM) and dependency ratio for each district have been estimated.

Data and Methods Data Data from the Census of India 2001 and 2011 have been used for estimation of various demographic parameters. Primary Census Abstract (PCA) data have been used for estimating the number of persons, sex ratio, child sex ratio, person literate and proportion of urban population. For estimating age distribution, dependency ratio, potential support ratio, median age, proportion of population by religion and singulate mean age at marriage, data from C-series were used. Recasted population

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of 1991 and 2001 for 640 districts has been taken from Census Table A-2 (ORGI 2018) and number of males and females facilitate computation of overall sex ratio. For estimating other indicators like child sex ratio, proportion urban, proportion of population in broad age groups and SMAM for 2001 for bifurcated districts two situations arise – one where districts are vertically divided into two or more districts, in that case values for bifurcated districts were repeated based on original district; two, where districts were carved out by combining constituents from two or more districts, in those cases averages of the indicators from parent districts were used. In cases where separation in data was not possible, adjustments in estimates were made by taking the average of estimates of the constituent districts. Data for the newly created state of Telangana was created for 1991, 2001 and 2011 by transferring the data of ten districts of the erstwhile state of Andhra Pradesh. Data for global comparisons have been compiled from World Population Prospects (UN 2018). Data from the Sample Registration System (SRS) and National Family Survey (NFHSs) have been used in population projection. For estimation of life expectancy at birth, SRS life tables have been used. Life tables for 2000–2002 and 2010–2012 have been used to estimate linear gains in decadal life tables. For smaller states/UTs, for which SRS does not publish life tables, they have been borrowed from the neighbouring larger states – for Chandigarh, from the life table of Punjab; Daman and Diu and Dadra and Nagar Haveli from Gujarat; Goa from Maharashtra; Lakshadweep from Kerala; Puducherry and Andaman and Nicobar Islands from Tamil Nadu; and for Telangana, it has been assumed to be equivalent to that of the erstwhile parent state, Andhra Pradesh. For sex ratio at birth, the number of births as reported in the Health Management Information System (HMIS) for 2011 has been used. Demographic estimates of each district have been presented within each state. A subnational population projection has been carried out and district level estimates obtained for 2021 and 2031.

Methods The demographic variables used are density, exponential growth rate, sex ratio, child sex ratio (sex ratio of 0–6 population), median age, young dependency ratio, old dependency ratio, potential support ratio, singulate mean age at marriage (SMAM) and population projection. These variables are commonly used in demographic analyses, and a brief description is given below. Population density is defined as the number of persons per square kilometre of area, and sex ratio is computed as number of females per 1000 males. The young dependency and the old dependency ratio are defined as follows: Young dependency ratio ¼ P014 =P1564 ∗ 1000

ð2:1Þ

2 Population Trends, Distribution and Prospects in the Districts of India

Old dependency ratio ¼ P65þ =P1564 ∗ 1000

21

ð2:2Þ

The singulate age at marriage is computed as: Singulate Mean Age at Marriage:
15 þ SMAM ¼

4549 P a¼1519

 Sa ∗ 5  50∗ 12ðS4549 þ S5054 Þ

1  12ðS4549 þ S5054 Þ

ð2:3Þ

where Sa is the proportion of singles in age group a, 15 is the age below which nobody married, S45–49 is proportion of singles at age 45–49 and S50–54 is proportion of singles at age 50–54.

Population Projection The projected population for the districts of India was carried out in two steps. In the first step, a projection exercise was undertaken for each state using the component method of projection. In the second step, the ratio method was used to obtain district level estimates. Projection parameters were derived by making realistic assumptions of futility, mortality, sex ratio at birth and life expectancy at birth and migration. The assumption on each of the parameters is given below.

Assumptions on Fertility The trend analysis of TFR was carried out using Gompertz model for projecting the future levels of TFR for each of the state of India. The assumption on lowest threshold for TFR was fixed for each state. The mathematical form of Gompertz model is: Ln ððLn ðTFR  LÞ=ðU  LÞÞÞ ¼ Ln ðLn∗ aÞ þ t∗ Ln∗ b

ð2:4Þ

where U and L are the upper and lower limits of TFR, respectively, and a and b are constants. The observed values of TFRs from 1991 to 2015 were used for projecting the future levels of TFR as reliable estimates from SRS are available for the period. For those states where TFR attained a low level, it has been assumed to remain the same as a further decline in TFR is not envisaged. The assumption of TFR and the values of 2011, 2021 and 2031 for each state are shown in Appendix 2.1. The lower limit of total fertility rate used for 11 states was assumed at 1.7, for 5 states between 1.7 and 1.8 and for 7 states between 1.8 and 2.0. For three states/union territories (UTs), the levels of TFR have been assumed to be 1.5 for 2031, for three more states

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1.55 and 1.6 for five states. Among the remaining states, Madhya Pradesh is expected to achieve a TFR of 2.1 in 2031, and only one state, Bihar with a TFR of 2.58, will not reach below replacement fertility by 2031. Most of the states in India will attain the replacement level of fertility by 2031.

Assumptions on Mortality Life expectancy at birth (LEB) for base years 2001 and 2011 was taken from SRS abridged life tables. Life expectancy at birth for 2021 is assumed to increase by two-thirds of the average annual increase in LEB from 2000–2003 to 2010–2012. For 2031, the annual increase was taken as half of the average annual increase in LEB from 2000–2003 to 2010–2012. The upper bound for LEB for 2031 was fixed at the current observed value of LEB in Kerala. The estimated LEB by sex for 2021 and 2031 is shown in Appendix 2.1.

Assumptions on Migration The population projection was assumed to be closed to migration.

Assumption on Sex Ratio at Birth (SRB) Sex ratio at birth (SRB) for each state was derived using Health Management Information System (HMIS) data for births reported in 2011. This is used as a base year estimate of SRB, and it is assumed to remain constant during the future. Spectrum software was used to project the population of 36 states and union territories including the newly created state of Telangana.

Results Population Trends in India Figure 2.1 presents the trends in India’s population from 1901 to 2031. The population of India was 238 million in 1901, 319 million in 1941 and 361 million in 1951. By 2011, the population of India was 1211 million, which was more than a threefold increase since 1951, and was projected to rise to 1474 million by 2031. In 1951, India accounted for 14.5% of the world’s population, and its share increased to 17.7% in 2011. The population of India is projected to be 1.47 billion by 2031.

2 Population Trends, Distribution and Prospects in the Districts of India

23

1600

1,474 1,352

1400 Population (million)

1,211

1200 1,029

1000

846

800

683 548

600 400

238

252

251

279

1901

1911

1921

1931

361

319

439

200 0

1941

1951

1961

1971

1981

1991

2001

2011

2021

2031

Years

Annual exponential growth rates (percent)

Fig. 2.1 Population trends in India, 1951–2031. (Source: Registrar General of India, for years 1901 to 2011 and authors’ projection for 2021 and 2031) 2.5 2.0 1.5 1.0 0.5 0.0 1951-1961

1961-1971

1971-1981

1981-1991

World

1991-2001 India

2001-2011

2011-2021

2021-2031

China

Fig. 2.2 Annual exponential growth rates of population (percent) in India, China and the world, 1951–2031. (Source: World population prospects 2018, Medium Variant)

The population growth rates in India have been hovering around 2% during the latter half of the nineteenth century. During 2001–2011, the growth rate of India’s population declined to 1.63% and is expected to decrease to 1.10% in 2011–2021 (Fig. 2.2) and further to 0.87% by 2021–2031, largely due to fertility decline. In the pre-independence period, the population growth rate was slow due to high birth and death rate. In the post-independence period, death rate declined faster followed by decline in birth rate. During the last two decades, fertility reduction has been faster, and the country is nearing the replacement level of fertility. India lagged behind in reducing population growth by almost three decades when compared to China. The annual population growth rate of China during 1991–2001 was less than 1%, and India is projected to have a similar growth rate in 2021–2031. India and China have certain similarities as both countries favor sons and have an imbalance in the sex ratio; the dissimilarities are that the population in China is relatively homogeneous,

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while India’s population is quite varied, and there is higher contraceptive usage in China than in India (Adlakha and Banister 1995). There are large regional differences in population growth, and the Indian substate scenario presents a picture of nations within nation. Particular trends exhibited by northern and southern states present a typical demographic divide. Many noteworthy distinct patterns like these are available at various substate levels. Among all states and union territories, Uttar Pradesh is the most populous state with a population of 198.8 million in 2011. Uttar Pradesh alone accounts for one-sixth of India’s population and about 3% of world population. The states of Maharashtra and Bihar account for 9.28% and 8.6% of India’s population, respectively. Thus, about a quarter of the population lives in Uttar Pradesh and Bihar. Looking at the population share across the regions of India, the Central region has a population of 24.6% followed by the Eastern region (22.3%), Southern region (20.9%), Western region (14.4%), Northern region (14%) and North-eastern region (3.8%). This conveys the imbalance in the regional distribution of the population. With regard to the annual exponential growth rates, the Central region is growing at a rate of 1.86% followed by Northern (1.78%), Eastern (1.75%), North-eastern (1.61%), Western (1.58%) and Southern (1.18%). The variations in growth rate of population across regions suggest divergence in population distribution across regions.

Population Trends in the Districts of India Appendix 2.2 presents the population trends of 1991, 2001 and 2011 along with the projected population for 2021 and 2031 for the districts of India. Table 2.1 provides the distribution of population among the 640 districts of India at five points of time. The population size has been adjusted for 1991–2011. The average population of a district in India was 1.3 million in 1991, which increased to 1.89 million in 2011 and is expected to rise to 2.3 million by 2031. Twenty Four Parganas district of West Bengal is the most populous district and Dibang Valley of Arunachal Pradesh is the least populous district for all the time periods under observation. The change in the number of districts for a higher size class of population is indicative of the rising population size. Districts with less than 0.1 million population were 45 in 1991, which reduced to 26 by 2011.The number of districts with a population size of 1 million or more has increased from 353 in 1991 to 445 by 2011 and is likely to be 479 in 2031. This distribution of districts according to population size essentially indicates the share of districts with lower population counts being on a decline and those with larger size on a rise. This entails an inference that populous districts are expected to become densely populated as against the share of districts with sparse inhabitation. Another apparent observation relates to population concentration that will become more imbalanced over time. The variation in the annual exponential growth rate of population was enormous across the districts. There were 22 districts with an exponential growth rate of 4% or

Number of districts 1991 45(7.0) 242 (37.8) 213 (33.3) 96 (15.0) 30 (4.7) 8 (1.3) 6 (0.9) 640 (100) 7393 7,281,881 1,322,533

Figures in parentheses indicate percentage Source: Authors

Size class