World Population Prospects 2019: Highlights


Book Description

The United Nations population estimates and projections form a comprehensive set of demographic data to assess population trends at the global, regional and national levels. They are used in the calculation of many of the key development indicators commonly used by the United Nations system, including for more than one third of the indicators used to monitor progress towards the achievement of the Sustainable Development Goals. The 2019 revision of the World Population Prospects is the twenty-sixth edition of the official United Nations population estimates and projections, which have been prepared since 1951 by the Population Division of the Department of Economic and Social Affairs. The 2019 revision presents population estimates from 1950 until the present for 235 countries or areas, which have been developed through country-specific analyses of historical demographic trends. It builds on previous revisions by incorporating additional results from the 2010 and 2020 rounds of national population censuses as well as information from vital registration and recent nationally representative household sample surveys. The 2019 revision also presents population projections to the year 2100 that reflect a range of plausible outcomes at the global, regional and country levels. These Highlights summarise key population trends described by the estimates and projections presented in World Population Prospects 2019.




Oregon Blue Book


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Statistical Abstract of the United States, 2012


Book Description

The Statistical Abstract of the United States, published since 1878, is the standard summary of statistics on the social, political, and economic organization of the United States. It is designed to serve as a convenient volume for statistical reference and as a guide to other statistical publications and sources. The latter function is served by the introductory text to each section, the source note appearing below each table, and Appendix I, which comprises the Guide to Sources of Statistics, the Guide to State Statistical Abstracts, and the Guide to Foreign Statistical Abstracts.




The Global Findex Database 2017


Book Description

In 2011 the World Bank—with funding from the Bill and Melinda Gates Foundation—launched the Global Findex database, the world's most comprehensive data set on how adults save, borrow, make payments, and manage risk. Drawing on survey data collected in collaboration with Gallup, Inc., the Global Findex database covers more than 140 economies around the world. The initial survey round was followed by a second one in 2014 and by a third in 2017. Compiled using nationally representative surveys of more than 150,000 adults age 15 and above in over 140 economies, The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution includes updated indicators on access to and use of formal and informal financial services. It has additional data on the use of financial technology (or fintech), including the use of mobile phones and the Internet to conduct financial transactions. The data reveal opportunities to expand access to financial services among people who do not have an account—the unbanked—as well as to promote greater use of digital financial services among those who do have an account. The Global Findex database has become a mainstay of global efforts to promote financial inclusion. In addition to being widely cited by scholars and development practitioners, Global Findex data are used to track progress toward the World Bank goal of Universal Financial Access by 2020 and the United Nations Sustainable Development Goals. The database, the full text of the report, and the underlying country-level data for all figures—along with the questionnaire, the survey methodology, and other relevant materials—are available at www.worldbank.org/globalfindex.




Subnational Population Estimates


Book Description

Providing a unified and comprehensive treatment of the theory and techniques of sub-national population estimation, this much-needed publication does more than collate disparate source material. It examines hitherto unexplored methodological links between differing types of estimation from both the demographic and sample-survey traditions and is a self-contained primer that combines academic rigor with a wealth of real-world examples that are useful models for demographers. Between censuses, which are expensive, administratively complex, and thus infrequent, demographers and government officials must estimate population using either demographic modeling techniques or statistical surveys that sample a fraction of residents. These estimates play a central role in vital decisions that range from funding allocations and rate-setting to education, health and housing provision. They also provide important data to companies undertaking market research. However, mastering small-area and sub-national population estimation is complicated by scattered, incomplete and outdated academic sources—an issue this volume tackles head-on. Rapidly increasing population mobility is making inter-census estimation ever more important to strategic planners. This book will make the theory and techniques involved more accessible to anyone with an interest in developing or using population estimates.




Kids Count Data Book


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Bayesian Analysis for Population Ecology


Book Description

Emphasizing model choice and model averaging, this book presents up-to-date Bayesian methods for analyzing complex ecological data. It provides a basic introduction to Bayesian methods that assumes no prior knowledge. The book includes detailed descriptions of methods that deal with covariate data and covers techniques at the forefront of research, such as model discrimination and model averaging. Leaders in the statistical ecology field, the authors apply the theory to a wide range of actual case studies and illustrate the methods using WinBUGS and R. The computer programs and full details of the data sets are available on the book's website.




Population Statistics


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