Long Memory Analysis in Human Mortality
Date Issued
2009
Date
2009
Author(s)
Yang, Hsi-Ling
Abstract
In recent years, long-memory property has gained considerable attention in economic and financial fields. However, although many economic and financial time series have been studied, human mortality, which plays an important role in insurance has not been considered. In this thesis we will analyze the human mortality of 25-year-old to 85-year-old females and males in the U.S. to find out whether it is a long-memory process. After building the ARFIMA model and considering the Whittle likelihood function along with the Robinson test statistic, we found out that both females’ and males’ annual mortality growth rates are indeed long-memory processes. Additionally, if the ARFIMA model is to be replaced by the ARIMA model it would result in misunderstandings in product pricing and risk control. In our thesis, we also found out that females’ mean of annual mortality growth rates increases by generation while males’ remains stable. Nevertheless, this result doesn’t contradict the fact that females’ average residual life becomes longer because females’ 25-year-old mortality rate decreases by generation.
Subjects
Long-memory
ARFIMA model
Human mortality
Whittle likelihood function
Robinson test statistic
SDGs
Type
thesis
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