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Multivariate Control Chart and Lee–Carter Models to Study Mortality Changes

Author

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  • Gisou Díaz-Rojo

    (Departamento de Matemáticas y Estadística, Facultad de Ciencias, Universidad del Tolima, Barrio Santa Helena Parte Alta, 730006 Ibagué, Tolima, Colombia)

  • Ana Debón

    (Centro de Gestión de la Calidad y del Cambio, Universitat Politècnica de València, Camino de Vera, s/n, 46022 Valencia, Spain)

  • Jaime Mosquera

    (School of Statistic, Universidad del Valle, Calle 13 No. 100-00, 760001 Cali, Colombia)

Abstract

The mortality structure of a population usually reflects the economic and social development of the country. The purpose of this study was to identify moments in time and age intervals at which the observed probability of death is substantially different from the pattern of mortality for a studied period. Therefore, a mortality model was fitted to decompose the historical pattern of mortality. The model residuals were monitored by the T 2 multivariate control chart to detect substantial changes in mortality that were not identified by the model. The abridged life tables for Colombia in the period 1973–2005 were used as a case study. The Lee–Carter model collects information regarding violence in Colombia. Therefore, the years identified as out-of-control in the charts are associated with very early or quite advanced ages of death and are inversely related to the violence that did not claim as many victims at those ages. The mortality changes identified in the control charts pertain to changes in the population’s health conditions or new causes of death such as COVID-19 in the coming years. The proposed methodology is generalizable to other countries, especially developing countries.

Suggested Citation

  • Gisou Díaz-Rojo & Ana Debón & Jaime Mosquera, 2020. "Multivariate Control Chart and Lee–Carter Models to Study Mortality Changes," Mathematics, MDPI, vol. 8(11), pages 1-17, November.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:11:p:2093-:d:449474
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    References listed on IDEAS

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