Demographics2019 Workshop

2027

Demographics 2027 Workshop

8 - 11 June 2027 Heraklion, Crete, Greece

Christos H. Skiadas has made significant contributions to actuarial science and demography by developing a dynamic modeling framework based on the First Exit Time (or Hitting Time) stochastic theory. Rather than relying strictly on traditional static mortality laws, his approach models the underlying health state of an individual or population as a stochastic process. In this framework, death or system failure occurs when this unobserved "vitality" variable crosses a critical boundary or reaches zero for the first time. [1, 2, 3, 4]

Core Methodologies & Actuarial Applications

Vitality and Health State Modeling: He treats an individual's health state as a continuous stochastic variable that deteriorates over time. This allows insurers and demographers to calculate a population's mean health state trajectory based on known death probability densities. [1, 2]
First Exit Time Probabilities: By solving technical foundations like the Fokker-Planck equation for boundary conditions, his models derive probability density functions to calculate when a system or life will hit a zero-level barrier. This has direct applications in life insurance pricing, pension fund forecasting, and life table estimations. [1, 2, 3]
Life Table Overhauls: In papers like Properties of a Stochastic Model for Life Table Data, Skiadas demonstrates that his stochastic approach fits historical data more accurately than classical curves like the Gompertz law. His models successfully capture both infant mortality spikes and the mortality plateaus observed in extreme old age. [1, 2]
Life Expectancy Forecasting: Using software implementations like the IM-First Exit Time nonlinear regression program, his research provides methodologies to accurately forecast Life Expectancy at Birth (LEB) using databases like the Human Mortality Database (HMD). [1]
- Books: He authored the textbook Exploring the Health State of a Population by Dynamic Modeling Methods (Springer Series on Demographic Methods and Population Analysis), which serves as a guide for using demographic models in actuarial practice and finance. [1, 2]
- Conferences: As the founder of the Data Analysis and Forecasting Laboratory at the Technical University of Crete, Skiadas has heavily driven the International Conference on Applied Stochastic Models and Data Analysis (ASMDA). He has edited highly cited volumes such as Stochastic Modeling, Data Analysis and Statistical Applications. [1, 2, 3]

Key Literature and Institutional Impact

Skiadas has extensively published his findings, bridging the gap between theoretical probability and real-world insurance risks.

Download the Healthy Life Expectancy calculation file inExcel

HLE-Template-1950-2019-Final-.zip

Figure from a 4-parameter mortality model. The best estimates achieved from a 4-parameter model

Healthy Life Years Lost Estimates

Related Excel Programs (Enable the Solver option)

4_Parameter_Mortality_Model

4_Parameter_Mortality_Model-ZIP

2. The Fokker-Planck Equation and the First Exit Time Problem. A Fractional Second Order Approximation

3. Remarks on “Limits to Human Lifespan”

Distribution of Health Expenditure in AUSTRIA

From a recent study to be presented in the Conference

Related work for 20 Countries is in progress

There are 2 options for downloading the Excel program for estimating the above picture with all the estimation details. One is based on the Solver facilities in Excel and the second without the Solver. Both programs estimate the Population Health State and the Deterioration stage in different age years thus providing a strong methodology for deciding the retirement ages.

1Health_State_Model-Solver

2Health_State_Model_Final

2Health_State_Model_Final -ZIP

Stochastic_Simulations-ZIP

Healthy Life Years Lost Estimates

The health state curve for USA females in 2010 is illustrated by the heavy magenta line. The corresponding survival curve for the related case is presented by the cyan curve (σ=0.068814). The blue curve expresses the death distribution. The light curves with various colors are the stochastic paths from the related simulation. The dashed curves express the confidence intervals. (source, C. H. Skiadas, 2016)

The rapid improvements last 60 years in science and especially in medicine, biology and the related fields gave rise to better conditions of life leading to a higher life span. Improvement also came in the way we cope with the nature and the natural phenomena. Demography and demographic analysis and research grow rapidly along with the other scientific fields and especially the quantitative branches of mathematics, statistics and more recently the computing methods and techniques. The new methods and techniques along with the classical qualitative aspects of demography tend to straighten the theoretical approaches and lead to various applications in the same or in other scientific fields including social and economic sciences, insurance and finance thus improving the social welfare of the countries. The research now is more interdisciplinary and the aim of the Workshop on Demographics 2021 is to attract people from the academia and practice thus closing the gap between theory and applications. Presentations expressing the state-of-the art will be organized.

The Workshop is organized under the umbrella of the Applied Stochastic Models and Data Analysis International Society - ASMDA International, and it is aimed to invite people in improving demography and the related fields of analysis and research including life and physical sciences as well as medical and technical information. We strongly support interdisciplinary studies and the improvement of the analytic tools and research methods. Both theoretical and practical submissions are accepted.

Abstract and Paper submissions are welcomed by using this website tools.

Papers in final form due, July 20, 2025 (one month after presentation)

More information at secretariat@asmda.com or from the workshop chair:

Christos H Skiadas (skiadas@cmsim.net )

Web: http://www.cmsim.net

Population Health State and Mortality Theory and Applications

Main Topics

1. Human population and mortality data and databases
2. Models and modeling of human mortality, longevity and life expectancy
3. Gompertz, Gompertz-Makeham, Weibull, Brass, Heligman and Pollard, Lee and Carter
4. Stochastic models, First exit time models of Human mortality
5. Methods and tools for fitting models
6. Nonlinear regression, Nonlinear regression packquages, Nonlinear regression with Excel
7. Life expectancy limits
8. Life expectancy forecasts
9. Human organism deterioration and application in life expectancy
10. Health state of a population: definition, modeling and estimates
11. The health state function
12. Healthy life expectancy estimates
13. Healthy life expectancy estimates from death and population data
14. Applications and comparisons of healthy life expectancy estimates
15. Longevity, theory and estimates

16. Human Development Stages Estimates

17. Miscellaneous

18. Other demographic analysis and research topics