Model Averaging Approach to Forecasting the General Level of Mortality

Marcin Bartkowiak , Katarzyna Kaczmarek-Majer , Aleksandra Rutkowska

Abstract

Already a 1% improvement to the overall forecast accuracy of mortality rates, may lead to the significant decrease of insurers costs. In practice, Lee-Carter model is widely used for forecasting the mortality rates. Within this study, we combine the traditional Lee-Carter model with the recent advances in the weighted model averaging. For this purpose, first, the training database of template predictive models is constructed for the mortality data and processed with similarity measures, and secondly, competitive predictive models are averaged to produce forecasts. The main innovation of the proposed approach is reflecting the uncertainty related to the shortness (e.g., 14 observations) of available data by the incorporation of multiple predictive models. The performance of the proposed approach is illustrated with experiments for the Human Mortality Database. We analyzed time series datasets for women and men aged 0–100 years from 10 countries in the Central and Eastern Europe. The presented numerical results seem very promising and show that the proposed approach is highly competitive with the state-of-the-art models. It outperforms benchmarks especially when forecasting long periods (6–10 years ahead).
Author Marcin Bartkowiak (WIiGE / KMS)
Marcin Bartkowiak,,
- Department of Applied Mathematics
, Katarzyna Kaczmarek-Majer - Systems Research Institute of the Polish Academy of Sciences
Katarzyna Kaczmarek-Majer,,
-
, Aleksandra Rutkowska (WIiGE / KMS)
Aleksandra Rutkowska,,
- Department of Applied Mathematics
Pages453-464
Publication size in sheets0.55
Book Medina Jesús, Ojeda-Aciego Manuel , Verdegay José Luis, Pelta David A., Cabrera Inma P. , Bouchon-Meunier Bernadette , Yager Ronald R. (eds.): Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations. 17th International Conference, IPMU 2018, Cádiz, Spain, June 11-15, 2018, Proceedings, Part I, Communications in Computer and Information Science, no. 853, 2018, Springer, ISBN 978-3-319-91472-5, [978-3-319-91473-2], 835 p.
Keywords in EnglishInformation Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations
ASJC Classification2600 General Mathematics; 1700 General Computer Science
DOIDOI:10.1007/978-3-319-91473-2_39
Languageen angielski
Score (nominal)20
Score sourceconferenceList
ScoreMinisterial score = 20.0, 12-03-2020, ChapterFromConference
Publication indicators Scopus Citations = 0; WoS Citations = 0; Scopus SNIP (Source Normalised Impact per Paper): 2018 = 0.385
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