Skip Navigation


Biometrika Advance Access originally published online on September 15, 2008
Biometrika 2008 95(4):979-986; doi:10.1093/biomet/asn026
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Kuang, D.
Right arrow Articles by Nielsen, J. P.
Right arrow Search for Related Content
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© 2008 Biometrika Trust

Miscellanea

Identification of the age-period-cohort model and the extended chain-ladder model

D. Kuang

Department of Statistics, University of Oxford, Oxford OX1 3TG, U.K., di.kuang{at}some.ox.ac.uk

B. Nielsen

Nuffield College, Oxford OX1 1NF, U.K., bent.nielsen{at}nuffield.ox.ac.uk

J. P. Nielsen

Cass Business School, City University London, 106 Bunhill Row, London EC1Y 8TZ, U.K., Jens.Nielsen.1{at}city.ac.uk

Received for publication 1 June 2007. Revision received 1 January 2008.

We consider the identification problem that arises in the age-period-cohort models as well as in the extended chain-ladder model. We propose a canonical parameterization based on the accelerations of the trends in the three factors. This parameterization is exactly identified and eases interpretation, estimation and forecasting. The canonical parameterization is applied to a class of index sets which have trapezoidal shapes, including various Lexis diagrams and the insurance-reserving triangles.

Key Words: Age-period-cohort model • Chain-ladder model • Identification



References

    Barnett G., Zehnwirth B. Best estimates for reserves. Proc. Casualty Actuar. Soc (2000) 87:245–321.

    Carstensen B. Age-period-cohort models for the Lexis diagram. Statist. Med (2007) 26:3018–45.[CrossRef]

    Clayton D., Schifflers E. Models for temporal variation in cancer rates. II: Age-period-cohort models. Statist. Med (1987) 6:469–81.[CrossRef]

    Cox D. R., Hinkley D. V. Theoretical Statistics (1974) London: Chapman and Hall.

    England P. D., Verrall R. J. Stochastic claims reserving in general insurance. Br. Actuar. J (2002) 8:519–44.

    Holford T. R. The estimation of age, period and cohort effects for vital rates. Biometrics (1983) 39:311–24.[CrossRef][Web of Science][Medline]

    Keiding N. Statistical inference in the Lexis diagram. Phil. Trans. R. Soc. A (1990) 332:487–509.

    R Development Core Team. R: A Language and Environment for Statistical Computing (2006) Vienna: R Foundation for Statistical Computing.

    Zehnwirth B. Probabilistic development factor models with applications to loss reserve variability, prediction intervals, and risk based capital. Casualty Actuar. Soc. Forum: 1994 Spring Forum (1994) 447–605.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?



This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Kuang, D.
Right arrow Articles by Nielsen, J. P.
Right arrow Search for Related Content
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?