Bayesian Demographic Modeling and Forecasting: An Application to U.S. Mortality Export

@misc{reichmuth_and_sarferaz_2008, abstract = {We present a new way to model age-specific demographic variables with the example of age-specific mortality in the U.S., building on the Lee-Carter 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 asses 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 hitherto 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 to 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.}, address = {Germany}, author = {Reichmuth, Wolfgang and Sarferaz, Samad}, booktitle = {SFB 649 Discussion Paper 2008-052}, citeulike-article-id = {3405065}, comment = {An interesting paper proposing a Bayesian modelling approach to forecasting national mortality trends. The Bayesian approach allows us to directly calculate error bands, which are vital for probabilistic forecasting. Incorporates the Brass relational system and model life tables. Interesting from a demographic standpoint --- might not turn out to be relevant but maybe some of the ideas on incorporating different age-specific mortality models may be useful.}, institution = {Humboldt-Universit\"{a}t zu Berlin}, keywords = {bayesian, forecasting, life-expectancy, mortality, usa}, posted-at = {2008-10-14 17:41:16}, priority = {0}, title = {Bayesian Demographic Modeling and Forecasting: An Application to U.S. Mortality}, year = {2008} }

TY - GEN ID - reichmuth_and_sarferaz_2008 L3 - citeulike-article-id:3405065 N2 - We present a new way to model age-specific demographic variables with the example of age-specific mortality in the U.S., building on the Lee-Carter 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 asses 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 hitherto 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 to 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. AD - Germany TI - Bayesian Demographic Modeling and Forecasting: An Application to U.S. Mortality T2 - SFB 649 Discussion Paper 2008-052 KW - bayesian KW - forecasting KW - life-expectancy KW - mortality KW - usa N1 - An interesting paper proposing a Bayesian modelling approach to forecasting national mortality trends. The Bayesian approach allows us to directly calculate error bands, which are vital for probabilistic forecasting. Incorporates the Brass relational system and model life tables. Interesting from a demographic standpoint --- might not turn out to be relevant but maybe some of the ideas on incorporating different age-specific mortality models may be useful. AU - Reichmuth, Wolfgang AU - Sarferaz, Samad PY - 2008/// ER -