Demographic Forecasting

Demographic Forecasting introduces new statistical tools that can greatly improve forecasts of population death rates. Mortality forecasting is used in a wide variety of academic fields, and for policymaking in global health, social security and retirement planning, and other areas. Federico Girosi and Gary King provide an innovative framework for forecasting age-sex-country-cause-specific variables that makes it possible to incorporate more information than standard approaches. These new methods more generally make it possible to include different explanatory variables in a time-series regression for each cross section while still borrowing strength from one regression to improve the estimation of all. The authors show that many existing Bayesian models with explanatory variables use prior densities that incorrectly formalize prior knowledge, and they show how to avoid these problems. They also explain how to incorporate a great deal of demographic knowledge into models with many fewer adjustable parameters than classic Bayesian approaches, and develop models with Bayesian priors in the presence of partial prior ignorance. By showing how to include more information in statistical models, Demographic Forecasting carries broad statistical implications for social scientists, statisticians, demographers, public-health experts, policymakers, and industry analysts. Introduces methods to improve forecasts of mortality rates and similar variables Provides innovative tools for more effective statistical modeling Makes available free open-source software and replication data Includes full-color graphics, a complete glossary of symbols, a self-contained math refresher, and more

This open access book presents new developments in the field of demographic forecasting, covering both mortality, fertility and migration. For each component emerging methods to forecast them are presented. Moreover, instruments for forecasting evaluation are provided. Bayesian models, nonparametric models, cohort approaches, elicitation of expert opinion, evaluation of probabilistic forecasts are some of the topics covered in the book. In addition, the book is accompanied by complementary material on the web allowing readers to practice with some of the ideas exposed in the book. Readers are encouraged to use this material to apply the new methods to their own data. The book is an important read for demographers, applied statisticians, as well as other social scientists interested or active in the field of population forecasting. Professional population forecasters in statistical agencies will find useful new ideas in various chapters.

Demographic Forecasting introduces new statistical tools that can greatly improve forecasts of population death rates. Mortality forecasting is used in a wide variety of academic fields, and for policymaking in global health, social security and retirement planning, and other areas. Federico Girosi and Gary King provide an innovative framework for forecasting age-sex-country-cause-specific variables that makes it possible to incorporate more information than standard approaches. These new methods more generally make it possible to include different explanatory variables in a time-series regression for each cross section while still borrowing strength from one regression to improve the estimation of all. The authors show that many existing Bayesian models with explanatory variables use prior densities that incorrectly formalize prior knowledge, and they show how to avoid these problems. They also explain how to incorporate a great deal of demographic knowledge into models with many fewer adjustable parameters than classic Bayesian approaches, and develop models with Bayesian priors in the presence of partial prior ignorance. By showing how to include more information in statistical models, Demographic Forecasting carries broad statistical implications for social scientists, statisticians, demographers, public-health experts, policymakers, and industry analysts. Introduces methods to improve forecasts of mortality rates and similar variables Provides innovative tools for more effective statistical modeling Makes available free open-source software and replication data Includes full-color graphics, a complete glossary of symbols, a self-contained math refresher, and more

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 www.bdef-book.com. "This book will be welcome for the scientific community of forecasters...as it presents a new approach which has already given important results and which, in my opinion, will increase its importance in the future." ~Daniel Courgeau, Institut national d'études démographiques

"The book will be of interest to scientists, researchers and students in demography and applied demography, statistics, economy, social geography and urban and regional planning and science studies."--BOOK JACKET.

Provides a unique introduction to demographic problems in a familiar language. Presents a unified statistical outlook on both classical methods of demography and recent developments. Exercises are included to facilitate its classroom use. Both authors have contributed extensively to statistical demography and served in advisory roles and as statistical consultants in the field.

Andrei Rogers, one of the world's leading authorities on population trends, offers a powerful technique for carrying out regional population projections. He gives a clear step-by-step analysis and demonstrations of actual projections of future populations at the regional level. The examples show how to calculate regional population growth rates, age compositions, and spatial distributions using data from several developed and less developed countries.

Is rapid world population growth actually coming to an end? As population growth and its consequences have become front-page issues, projections of slowing growth from such institutions as the United Nations and the World Bank have been called into question. Beyond Six Billion asks what such projections really say, why they say it, whether they can be trusted, and whether they can be improved. The book includes analysis of how well past U.N. and World Bank projections have panned out, what errors have occurred, and why they have happened. Focusing on fertility as one key to accurate projections, the committee examines the transition from high, constant fertility to low fertility levels and discusses whether developing countries will eventually attain the very low levels of births now observed in the industrialized world. Other keys to accurate projections, predictions of lengthening life span and of the impact of international migration on specific countries, are also explored in detail. How good are our methods of population forecasting? How can we cope with the inevitable uncertainty? What population trends can we anticipate? Beyond Six Billion illuminates not only the forces that shape population growth but also the accuracy of the methods we use to quantify these forces and the uncertainty surrounding projections. The Committee on Population was established by the National Academy of Sciences (NAS) in 1983 to bring the knowledge and methods of the population sciences to bear on major issues of science and public policy. The committee's work includes both basic studies of fertility, health and mortality, and migration; and applied studies aimed at improving programs for the public health and welfare in the United States and in developing countries. The committee also fosters communication among researchers in different disciplines and countries and policy makers in government, international agencies, and private organizations. The work of the committee is made possible by funding from several government agencies and private foundations.

Information on future mortality trends is essential for population forecasts, public health policy, actuarial studies, and many other purposes. Realising the importance of such needs, this volume contains contributions to the theory and practice of forecasting mortality in the relatively favourable circumstances in developed countries of Western Europe. In this context techniques from mathematical statistics and econometrics can provide useful descriptions of past mortality. The naive forecast obtained by extrapolating a fitted model may give as good a forecast as any but forecasting by extrapolation requires careful justification since it assumes the prolongation of historical conditions. On the other hand, whilst it is generally accepted that scientific and other advances will continue to impact on mortality, perhaps dramatically so, it is impossible to quantify more than the outline of future consequences with a strong degree of confidence. The decision to modify an extrapolation of a model fitted to historical data (or conversely choosing not to modify it) in order to obtain a forecast is therefore strongly influenced by subjective and judgmental elements, with the quality of the latter dependent on demographic, epidemiological and indeed perhaps more general considerations. The thread running through the book reflects therefore the necessity of integrating demographic, epidemiological, and statistical factors to obtain an improvement in the prediction of mortality.

Authors, scholars and scientists whose mother tongue is not one of the major languages of international communication are seriously disadvantaged. Some individuals, such as Joseph Conrad or Vladimir Nabokov, have overcome that handicap brilliantly. Others learn to live with it: they can express themselves sufficiently lucidly in a second language to make their voice heard internation ally. At least when they have something original or striking to say they will be certain to reach their peers. Most scientists and scholars fall into that category. Others, again, have to wait until their work has been translated before its value is recognised. This may apply even to those whose mother tongue is widely read. The writings of Frenchmen Lyotard, Derrida, Baudrillard or Foucault on post-modernism, on language, discourse and power, for example, had tremendous world-wide impact only after English translations appeared on the market. De Gans' study of the development of population forecasting in The Nether lands is another striking illustration of the effects a language barrier may have. He demonstrates convincingly that although a -possibly some what awkward Dutchman named Wiebols, was a pioneer of modern cohort component demo graphic forecasting, he never received international recognition for this. In his thesis of 1925 Wiebols employed the newest instruments of demographic analysis in improving forecasting methodology.