Bryant, John; Zhang, Junni L. Bayesian demographic estimation and forecasting. (English) Zbl 1435.62002 Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences Series. Boca Raton, FL: CRC Press (ISBN 978-1-4987-6262-5/hbk; 978-0-429-45298-7/ebook). xii, 280 p. (2019). From the cover of the book: “Bayesian Demographic Estimation and Forecasting presents three statistical frameworks for modern demographic estimation and forecasting. The frameworks draw on recent advances in statistical methodology to provide new tools for tackling challenges such as disaggregation, measurement error, missing data, and combining multiple data sources. The methods apply to single demographic series, or to entire demographic systems. The methods unify estimation and forecasting, and yield detailed measures of uncertainty. The book assumes minimal knowledge of statistics, and no previous knowledge of demography. The authors have developed a set of R packages implementing the methods. Data and code for all applications in the book are available on http://www.bdef-book.com.” From the Preface of the book: “This book presents new methods for answering questions such as – How long can be a newborn baby expect to live, given the ethnicity and income of the baby’s parents? – What proportion of future increases in health spending will be due to population aging? – How should alternative estimates of population size be reconciled when these estimates do not agree? The methods combine ideas from demography with ideas from statistics – especially a subfield known as Bayesian statistics.” The book is very large structured in a preface, 20 chapters (divided in 123 subchapters), bibliography, index: Chapter 1. Introduction Part I. “Demographic Foundations” with the Chapter 2. Demographic Foundations – Chapter 3. Demographic Individuals – Chapter 4. Demographic Arrays – Chapter 5. Demographic Accounts – Chapter 6. Demographic Data Part II. “Bayesian Foundations” with the Chapter 7. Bayesian Foundations – Chapter 8. Bayesian Model Specification – Chapter 9. Bayesian Inference and Model Checking Part III. “Inferring Arrays from Reliable Data” with the Chapter 10. Inferring Demographic Arrays from Reliable Data – Chapter 11. Infant Mortality in Sweden – Chapter 12. Life Expectancy in Portugal – Chapter 13. Health Expenditure in the Netherlands Part IV. “Inferring Arrays from Unreliable Data” with the Chapter 14. Inferring Demographic Arrays from Unreliable Data – Chapter 15. Internal Migration in Iceland – Chapter 16. Fertility in Cambodia Part V. “Inferring Accounts” with the Chapter 17. Inferring Demographic Accounts – Chapter 18. Population in New Zealand – Chapter 19. Population in China – Chapter 20. Conclusion All chapters finish with references and further reading. The bibliography contains 94 references and the index more than 140 items. The book can be recommend all readers, who are interested in this field. Reviewer: Ludwig Paditz (Dresden) MSC: 62-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics 62P25 Applications of statistics to social sciences 62H12 Estimation in multivariate analysis 91D20 Mathematical geography and demography 92D25 Population dynamics (general) 62F15 Bayesian inference 62M20 Inference from stochastic processes and prediction Keywords:demographic foundations; demographic data; Bayesian demographic estimation; measurement error; demographic individuals; life expectancy; infant mortality; fertility rate; region effect; age effect; sex effect; migration; emigration; data structure Software:R PDFBibTeX XMLCite \textit{J. Bryant} and \textit{J. L. Zhang}, Bayesian demographic estimation and forecasting. Boca Raton, FL: CRC Press (2019; Zbl 1435.62002) Full Text: DOI