Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/25295 
Erscheinungsjahr: 
2008
Schriftenreihe/Nr.: 
SFB 649 Discussion Paper No. 2008,052a
Verlag: 
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk, Berlin
Zusammenfassung: 
We present a new way to model age-specific demographic variables, using the example of age-specific mortality in the United States, building on the LeeCarter approach and extending it in several dimensions. We incorporate covariates and model their dynamics jointly with the latent variables underlying mortality of all age classes. In contrast to previous models, a similar development of adjacent age groups is assured, allowing for consistent forecasts. We develop an appropriate Markov chain Monte Carlo algorithm to estimate the parameters and the latent variables in an efficient one-step procedure. Via the Bayesian approach we are able to assess uncertainty intuitively by constructing error bands for the forecasts. We observe that in particular parameter uncertainty is important for long-run forecasts. This implies that existing forecasting methods, which ignore certain sources of uncertainty, may yield misleadingly sure predictions. To test the forecast ability of our model we perform in-sample and out-of-sample forecasts up to 2050, revealing that covariates can help improve the forecasts for particular age classes. A structural analysis of the relationship between age-specific mortality and covariates is conducted in a companion paper.
Schlagwörter: 
Demography
age-specific mortality
LeeCarter
stochastic
Bayesian state space models
forecasts
JEL: 
C11
C32
C53
I10
J11
Dokumentart: 
Working Paper

Datei(en):
Datei
Größe
876.59 kB





Publikationen in EconStor sind urheberrechtlich geschützt.