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.
Part I: Healthy Aging, Healthy Life Years Lost and Health Expenditure
Allocation.
Chapter
1. Relation of the Weibull Shape Parameter with the
Healthy Life Years Lost Estimates: Analytic Derivation and Estimation from an
Extended Life Table.
Chapter
2. Direct Healthy Life Expectancy Estimates
from Life Tables with a Sullivan Extension. Bridging the Gap Between HALE and
Eurostat Estimates.
Chapter
3. Modeling the Health Expenditure in Japan,
2011. A Healthy Life Years Lost Methodology.
Chapter
4. Healthy Ageing in
Czechia.
Chapter
5. Evolution of Systems with Power-Law Memory: Do We Have
to Die?.- Part II: Mortality Modeling and Applications.
Chapter
6.
Structural Equation Modeling: Infant Mortality Rate in Egypt Application.-
Chapter
7. Modeling of mortality in elderly by lung cancer in the Northeast
of Brazil.
Chapter
8. Demographics of the Russian pension reform.
Chapter
9. Using the Developing Countries Mortality Database (DCMD) to
Probabilistically Evaluate the Completeness of Death Registration at Old
Ages.
Chapter
10. Mortality developments in Greece from the cohort
perspective.
Chapter
11. On demographic approach of the BGGM distribution
parameters on Italy and Sweden.
Chapter
12. Alcohol consumption in selected
European countries.- Part III: Birth-Death Process, Self-perceived Age and
Gender Differences.
Chapter
13. Modelling monthly birth and deaths using
Seasonal Forecasting Methods as an input for population estimates.
Chapter
14. Births by order and childlessness in the post-socialist countries.-
Chapter
15. On the evaluation of Self-perceived Age for Europeans and
Americans.- Part IV: Theoretical Issues and Applications.
Chapter
16.
Spatio-temporal aspects of community well-being in Multivariate Functional
Data approach.
Chapter
17. Properties and Dynamics of the Beta Gompertz
Generalized Makeham Distribution.
Chapter
18. Increasing efficiency in the
EBT algorithm.
Chapter
19. Psychometric validation of constructs defined by
ordinal-valued items.
Chapter
20. Robust Minimal Markov Model for Dengue
Virus Type 3.
Chapter
21. Determining influential factors in spatio-temporal
models.
Chapter
22. Describing labour market dynamics through Non
Homogeneous Markov System theory.- Part V: Life-time, Survival, Pension,
Labor Force and Further Estimates.
Chapter
23. The wide variety of
regression models for lifetime data.
Chapter
24. Analysing the risk of
bankruptcy of firms: survival analysis, competing risks and multistate
models.
Chapter
25. A bayesian modeling approach to private preparedness
behavior against flood hazards.
Chapter
26. Assessing labour market mobility
in Europe.
Chapter
27. The implications of applying
alternative-supplementary measures of the unemployment rate to regions:
Evidence from the European Union Labour Force Survey for Southern Europe,
2008-2015.
Chapter
28. Reverse Mortgages: Risks and Opportunities.
Chapter
29. Estimating the Health State at Retirement: A Stochastic Modeling Approach.
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.
