79034 - Demographic Models for Insurance and Enterprises

Learning outcomes

The student knows the main models of life expectancy and applications. More specifically, the student will be able to forecast population and subgroups of population and to apply these modelling technique to insurance issues.

Course contents

Recall of some basic concepts of demographic analysis: crude and specific rates, standardization methods, Lexis diagram, period and cohort analysis, life tables; stationary population. Recal of survival analysis: survivorship functions of Kaplan Meier, Hazard function, parametric and semiparametric models. Analysis of mortality at specific ages. Application of smoothing techniques to mortality data. Forecasting mortality risks. Lee-Carter model. Mortality models with frailty (some notes).
Insurance applications.
Elements of business demography. Bankruptcy risk analysis for private enterprises.

Readings/Bibliography

Notes of the lectures will be given during the course. It is possible to download them from the web site https://virtuale.unibo.it/

Suggested readings:

- S. Preston, P. Heuveline, M. Guillot.

"Demography: Measuring and Modeling Population Processes" (chapters 1, 2 e 3)

- E. Pitacco, M. Denuit, S. Haberman, Olivieri.

"Modelling Longevity Dynamics for Pensions and Annuity Business" (chapters 2, 3 e 4)

- Susanna Levantesi, Massimiliano Menzietti

"Allungamento della vita media e rischio assicurativo"

 

- D. G. Kleinbaum, M. Klein

"Survival Analysis" (chapters 1, 2, 3)

Teaching methods

All topics are illustrated with demographic data using some demographic software packages.

Assessment methods

The final exam aims at evaluating the achievement of the following educational targets:

- knowledge of the demographic methods and models shown during the frontal lectures;

- ability to employ these techniques to analyze and forecast mortality trends;

- knowledge of the main demographic models for business and insurances

- knowledge of the demographic software packages.

Exam:

1) PRACTICAL PART: the student will carry out a project using real demographic data and the statistical software R;

2) THEORETICAL PART: an oral test on all the theoretical topics.

The final vote is an average of the marks obtained in the two parts.

Teaching tools

Overhead projector, computer lab.

Office hours

See the website of Francesco Scalone