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Demography of Population Health, Aging and Health Expenditures

  • Book
  • © 2020

Overview

  • Provides a theoretical methodology for estimating population health expenditure allocation
  • Includes qualitative analysis and quantitative estimates on health related issues
  • Describes and applies quantitative methods in demography

Part of the book series: The Springer Series on Demographic Methods and Population Analysis (PSDE, volume 50)

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Table of contents (31 chapters)

  1. Mortality Modeling and Applications

  2. Birth-Death Process, Self-Perceived Age and Gender Differences

Keywords

About this book

This book provides theoretical and applied material for estimating vital parts of demography and health issues including the healthy aging process along with calculating the healthy life years lost to disability. It further includes the appropriate methodology for the optimum health expenditure allocation. Through providing data analysis, statistical and stochastic methodology, probability approach and important applications, the book explores topics such as aging and mortality, birth-death processes, self-perceived age, life-time and survival as well as pension and labor-force. By providing a methodological approach to health problems in demography and society including and quantifying important parameters, this book is a valuable guide for researchers, theoreticians and practitioners from various disciplines.

Editors and Affiliations

  • ISAST, Athens, Greece

    Christos H. Skiadas

  • Mathematics & Computer Science, Hanover College, Hanover, USA

    Charilaos Skiadas

About the editors

Christos H. Skiadas, PhD, was the founder and director of the Data Analysis and Forecasting Laboratory at the Technical University of Crete. He is chair of the Demographics Workshop series, the Applied Stochastic Models and Data Analysis Conference series and the Chaotic Modeling and Simulation Conference series. He has published more than 80 papers, three monographs, and 18 books, including probability, statistics, data analysis and forecasting. His research interests include innovation diffusion modeling and forecasting, life table data modeling, healthy life expectancy estimates, and deterministic, stochastic, and chaotic modeling.

Charilaos Skiadas, PhD, is an associate professor in mathematics and computer science at Hanover College. His research interests encompass a wide array of mathematical and computing topics, ranging from algebraic geometry to statistics and programming languages to data science and health state modeling.

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