The Springer Series on Demographic Methods and Population Analysis

The book is well organized and clearly written so that it is accessible to those with only a minimal knowledge of calculus. It begins with a review of fixed rate population models, from the basic life table to multistate stable populations. The process of convergence to stability is described, and the regularities underlying change in the size and composition of any population are explored. Techniques for estimating rates from multistate population distributions are presented, and new multi-age, multistate dynamic models are developed. Building on the logical closure of demographic models and the close relationship between population stocks and flows, the book sets forth the latest approaches for capturing population change in a world experiencing profound demographic transformations.

In population studies, most research is based on non-experimental designs (observational or survey designs) and rarely on quasi experiments or natural experiments. Using non-experimental designs to infer causal relationships—i.e. relationships that can ultimately inform policies or interventions—is a complex undertaking. Specifically, treatment effects can be inferred from non-experimental data with a counterfactual approach. In this counterfactual perspective, causal effects are defined as the difference between the potential outcome irrespective of whether or not an individual had received a certain treatment (or experienced a certain cause). The counterfactual approach to estimate effects of causes from quasi-experimental data or from observational studies was first proposed by Rubin in 1974 and further developed by James Heckman and others.

This book presents both theoretical contributions and empirical applications of the counterfactual approach to causal inference.

This book provides a comprehensive, thoughtful and critical discussion of all aspects involved in the relationship between socioeconomic status, health and mortality. In a well-written language, it synthesizes the sociological theory of social inequality and an empirical study of mortality differences that has been performed at the Max Planck Institute for Demographic Research (Rostock, Germany).

The best available datasets from Denmark and the USA, as two very different countries, are used to analyze the age pattern of social mortality differences, the Danish register data covering the whole Danish population between 1980 and 2002.

This study is the most comprehensive analysis of socioeconomic mortality differences in the literature, in terms of data quantity, quality, and the statistical method of event-history modeling. It makes important new theoretical and empirical contributions. With a new method it also addresses the question whether the measurement of social mortality differences in old age so far has been biased by mortality selection due to unobserved heterogeneity.

"This book signifies an important step forward in theory, empirical data analysis and methodology and an advancement for many disciplines involved in the subject of socioeconomic differences in old age mortality". Prof. Dr. Gabriele Doblhammer, Max Planck Institute for Demographic Research, Rostock, Germany

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.

The results presented in this book allow researchers, governments and policy makers to evaluate to what extent various migration and labour market policies may be instrumental in achieving the desired population and labour size and structures.

The secondary purpose of this volume is to reveal the methodology and argumentation lying behind a complex population forecasting and simulation exercise, which is not done frequently, but is critical for the assessment of the forecasts and also valuable from a purely didactic point of view.

The book further addresses such current imperatives as understanding the social meanings of emergency contraception, measuring gender-based violence, improving reproductive health governance, strengthening health systems and services, and redressing institutional barriers.

The book also assesses how reproductive health programs can be reconfigured to new challenges such as those posed by climate change, vulnerable youth in fragile states, and risks from new infertility treatments.

Using a rich and varied set of cases, a broad public health and social science perspective, and novel methodological approaches, this book questions common assumptions, illustrates effective solutions and sets out research, policy, and programmatic agendas for the present and future.

This is a comprehensive volume which provides a valuable resource to researchers, educators, practitioners, policymakers and students, as well as anyone studying or advocating for reproductive health.

In the past, the estimation of levels, trends and differentials in demographic and health outcomes in developing countries was heavily reliant on indirect methods that were devised to suit limited or deficient data. In recent decades, world-wide surveys like the World Fertility Survey and its successor, the Demographic and Health Survey have played an important role in filling the gap in survey data from developing countries. Such modern demographic and health surveys enable investigators to make in-depth analyses that guide policy intervention strategies, and such analyses require the modern and advanced statistical techniques covered in this book.

The text is ideally suited for academics, professionals, and decision makers in the social and health sciences, as well as others with an interest in statistical modelling, demographic and health surveys. Scientists and students in applied statistics, epidemiology, medicine, social and behavioural sciences will find it of value.