Hybrid of the Lee-Carter Model with Maximum Overlap Discrete Wavelet Transform Filters in Forecasting Mortality Rates

Nurul Aityqah Yaacob, Jamil Jaber, Dharini Pathmanathan, Sadam Alwadi and Ibrahim Mohamed
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Nurul Aityqah Yaacob: Faculty of Science, Institute of Mathematical Sciences, University Malaya, Kuala Lumpur 50603, Malaysia
Dharini Pathmanathan: Faculty of Science, Institute of Mathematical Sciences, University Malaya, Kuala Lumpur 50603, Malaysia
Sadam Alwadi: Department of Finance, Faculty of Business, The University of Jordan/Aqaba branch, Aqaba 77110, Jordan
Ibrahim Mohamed: Faculty of Science, Institute of Mathematical Sciences, University Malaya, Kuala Lumpur 50603, Malaysia

Mathematics, 2021, vol. 9, issue 18, 1-11

Abstract: This study implements various, maximum overlap, discrete wavelet transform filters to model and forecast the time-dependent mortality index of the Lee-Carter model. The choice of appropriate wavelet filters is essential in effectively capturing the dynamics in a period. This cannot be accomplished by using the ARIMA model alone. In this paper, the ARIMA model is enhanced with the integration of various maximal overlap discrete wavelet transform filters such as the least asymmetric, best-localized, and Coiflet filters. These models are then applied to the mortality data of Australia, England, France, Japan, and USA. The accuracy of the projecting log of death rates of the MODWT-ARIMA model with the aforementioned wavelet filters are assessed using mean absolute error, mean absolute percentage error, and mean absolute scaled error. The MODWT-ARIMA (5,1,0) model with the BL14 filter gives the best fit to the log of death rates data for males, females, and total population, for all five countries studied. Implementing the MODWT leads towards improvement in the performance of the standard framework of the LC model in forecasting mortality rates.

Keywords: MODWT; DWT; BL14; Coiflet; least asymmetric; wavelet (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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