Abstract
Age and period are the most widely used parameters for forecasting mortality rates. Empirical mortality rate differences in multiple populations often show strong geometric patterns on the two-dimensional age–period plane. The idea of this paper is to take these geometric patterns as the starting point for the development of forecasts. A parametric approach is presented and discussed which uses simple techniques from spatial statistics. The proposed model is statistically parsimonious and yields forecasts that are consistent with the historical data and coherent for multiple populations.
Original language | English |
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Pages (from-to) | 477-502 |
Number of pages | 26 |
Journal | ASTIN Bulletin: The Journal of the IAA |
Volume | 45 |
Issue number | 3 |
Early online date | 3 Jul 2015 |
DOIs | |
Publication status | Published - Sept 2015 |
Keywords
- Box–Cox transform
- conditional simulation
- Gaussian random fields
- geostatistics
- Kriging
- modeling multiple populations
- Mortality forecasting
ASJC Scopus subject areas
- Finance
- Accounting
- Economics and Econometrics