Statistical Demography And Forecasting

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.

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.

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

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.

The initial plans for this book sprang from a late-afternoon conversation in a hotel bar. All three authors were attending the 1996 meeting of the Population As- ciation of America in New Orleans. While nursing drinks and expounding on a variety of topics, we began talking about our current research projects. It so happened that all three of us had been entertaining the notion of writing a book on state and local population projections. Recognizing the enormity of the project for a single author, we quickly decided to collaborate. Had we not decided to work together, it is unlikely that this book ever would have been written. The last comprehensive treatment of state and local population projections was Don Pittenger’s excellent work Projecting State and Local Populations (1976). Many changes affecting the production of population projections have occurred since that time. Technological changes have led to vast increases in computing power, new data sources, the development of GIS, and the creation of the Internet. The procedures for applying a number of projection methods have changed considerably, and several completely new methods have been developed.

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

This book focuses on the methodology and analysis of state and local population projections. It describes the most commonly used data sources and application techniques for four types of projection methods: cohort-component, trend extrapolation, structural models, and microsimulation. It covers the components of population growth, sources of data, the formation of assumptions, the development of evaluation criteria, and the determinants of forecast accuracy. It considers the strengths and weaknesses of various projection methods and pays special attention to the unique problems that characterize small-area projections. The authors provide practical guidance to demographers, planners, market analysts, and others called on to construct state and local population projections. They use many examples and illustrations and present suggestions for dealing with special populations, unique circumstances, and inadequate or unreliable data. They describe techniques for controlling one set of projections to another, for interpolating between time points, for sub-dividing age groups, and for constructing projections of population-related variables (e.g., school enrollment, households). They discuss the role of judgment and the importance of the political context in which projections are made. They emphasize the “utility” of projections, or their usefulness for decision making in a world of competing demands and limited resources. This comprehensive book will provide readers with an understanding not only of the mechanics of the most commonly used population projection methods, but also of the many complex issues affecting their construction, interpretation, evaluation, and use.​

This textbook focuses on the cohort change ratio (CCR) method. It presents powerful, yet relatively simple ways to generate accurate demographic estimates and forecasts that are cost efficient and require fewer resources than other techniques. The concepts, analytical frameworks, and methodological tools presented do not require extensive knowledge of demographics, mathematics, or statistics. The demographic focus is on the characteristics of populations, especially age and sex composition, but these methods are applicable estimating and forecasting other characteristics and total population. The book contains more traditional applications such as the Hamilton-Perry method, but also includes new applications of the CCR method such as stable population theory. Real world empirical examples are provided for every application; along with excel files containing data and program code, which are accessible online. Topics covered include basic demographic measures, sources of demographic information, forecasting and estimating (both current and historical) populations, modifications to current methods, forecasting school enrollment and other characteristics, estimating life expectancy, stable population theory, decomposition of the CCR into its migration and mortality components, and the utility of the CCR. This textbook is designed to provide material for an advanced undergraduate or graduate course on demographic methods. It can also be used as a supplement for other courses including applied demography, business and economic forecasting and market research.