TY - JOUR
T1 - Backtesting stochastic mortality models
T2 - An expost evaluation of multiperiod-ahead density forecasts
AU - Dowd, Kevin
AU - Cairns, A. J G
AU - Blake, David
AU - Coughlan, Guy D.
AU - Epstein, David
AU - Khalaf-Allah, Marwa
PY - 2010
Y1 - 2010
N2 - This study sets out a backtesting framework applicable to the multiperiod-ahead forecasts from stochastic mortality models and uses it to evaluate the forecasting performance of six different stochastic mortality models applied to English & Welsh male mortality data. The models considered are the following: Lee-Carter's 1992 one-factor model; a version of Renshaw-Haberman's 2006 extension of the Lee-Carter model to allow for a cohort effect; the age-period-cohort model, which is a simplified version of Renshaw-Haberman; Cairns, Blake, and Dowd's 2006 two-factor model; and two generalized versions of the last named with an added cohort effect. For the data set used herein, the results from applying this methodology suggest that the models perform adequately by most backtests and that prediction intervals that incorporate parameter uncertainty are wider than those that do not. We also find little difference between the performances of five of the models, but the remaining model shows considerable forecast instability.
AB - This study sets out a backtesting framework applicable to the multiperiod-ahead forecasts from stochastic mortality models and uses it to evaluate the forecasting performance of six different stochastic mortality models applied to English & Welsh male mortality data. The models considered are the following: Lee-Carter's 1992 one-factor model; a version of Renshaw-Haberman's 2006 extension of the Lee-Carter model to allow for a cohort effect; the age-period-cohort model, which is a simplified version of Renshaw-Haberman; Cairns, Blake, and Dowd's 2006 two-factor model; and two generalized versions of the last named with an added cohort effect. For the data set used herein, the results from applying this methodology suggest that the models perform adequately by most backtests and that prediction intervals that incorporate parameter uncertainty are wider than those that do not. We also find little difference between the performances of five of the models, but the remaining model shows considerable forecast instability.
UR - http://www.scopus.com/inward/record.url?scp=79952015928&partnerID=8YFLogxK
U2 - 10.1080/10920277.2010.10597592
DO - 10.1080/10920277.2010.10597592
M3 - Article
SN - 1092-0277
VL - 14
SP - 281
EP - 298
JO - North American Actuarial Journal
JF - North American Actuarial Journal
IS - 3
ER -