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題名 Using Graduation to Modify the Estimation of Lee-Carter Model for Small Populations
作者 余清祥
Yue, Jack C.
Wang, Hsin-Chung
Wang, Tzu-Yu
貢獻者 統計系
日期 2019-11
上傳時間 25-Jun-2021 10:16:41 (UTC+8)
摘要 Many mortality models, such as the Lee–Carter model, have unsatisfactory estimation in the case of small populations. Increasing population size is a natural choice to stabilize the estimation, if we can find a larger reference population that has a mortality profile similar to that of the small population. Aggregating historical data of the small populations is a fine candidate for the reference population. However, it is often not feasible in practice and we need to rely on other reference populations. In this study, we explore whether graduation methods can be used if the mortality profile of a small population differs from that of the reference population. To explore the appropriate occasion to use graduation methods, we create several mortality scenarios and similarity types between small and reference populations. We propose combining the graduation methods and mortality models, either graduating mortality rates first or applying the mortality model first, and determine whether they can improve the model fit. We use computer simulation to determine whether the proposed approach has better mortality estimation than the Lee–Carter model and the the Li–Lee model. We found that the Li–Lee model always has smaller estimation errors than the Lee–Carter model, and the proposed approach has smaller estimation errors than the Li–Lee model in most cases.
關聯 North American Actuarial Journal, Vol.25, pp.S410-S420
資料類型 article
DOI https://doi.org/10.1080/10920277.2019.1650288
dc.contributor 統計系
dc.creator (作者) 余清祥
dc.creator (作者) Yue, Jack C.
dc.creator (作者) Wang, Hsin-Chung
dc.creator (作者) Wang, Tzu-Yu
dc.date (日期) 2019-11
dc.date.accessioned 25-Jun-2021 10:16:41 (UTC+8)-
dc.date.available 25-Jun-2021 10:16:41 (UTC+8)-
dc.date.issued (上傳時間) 25-Jun-2021 10:16:41 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/135887-
dc.description.abstract (摘要) Many mortality models, such as the Lee–Carter model, have unsatisfactory estimation in the case of small populations. Increasing population size is a natural choice to stabilize the estimation, if we can find a larger reference population that has a mortality profile similar to that of the small population. Aggregating historical data of the small populations is a fine candidate for the reference population. However, it is often not feasible in practice and we need to rely on other reference populations. In this study, we explore whether graduation methods can be used if the mortality profile of a small population differs from that of the reference population. To explore the appropriate occasion to use graduation methods, we create several mortality scenarios and similarity types between small and reference populations. We propose combining the graduation methods and mortality models, either graduating mortality rates first or applying the mortality model first, and determine whether they can improve the model fit. We use computer simulation to determine whether the proposed approach has better mortality estimation than the Lee–Carter model and the the Li–Lee model. We found that the Li–Lee model always has smaller estimation errors than the Lee–Carter model, and the proposed approach has smaller estimation errors than the Li–Lee model in most cases.
dc.format.extent 490288 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) North American Actuarial Journal, Vol.25, pp.S410-S420
dc.title (題名) Using Graduation to Modify the Estimation of Lee-Carter Model for Small Populations
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1080/10920277.2019.1650288
dc.doi.uri (DOI) https://doi.org/10.1080/10920277.2019.1650288