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Space, mortality, and economic growth

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  • Kyran Cupido
  • Petar Jevtić
  • Tim J. Boonen

Abstract

Currently, most academic research involving the mortality modeling of multiple populations mainly focuses on factor‐based approaches. Increasingly, these models are enriched with socio‐economic determinants. Yet these emerging mortality models come with little attention to interpretable spatial model features. Such features could be highly valuable to demographers and old‐age benefit providers in need of a comprehensive understanding of the impact of economic growth on mortality across space. To address this, we propose and investigate a family of models that extend the seminal Li‐Lee factor‐based stochastic mortality modeling framework to include both economic growth, as measured by the real gross domestic product (GDP), and spatial patterns of the contiguous United States mortality. Model selection performed on the introduced new class of spatial models shows that based on the AIC criteria, the introduced spatial lag of GDP with GDP (SLGG) model had the best fit. The out‐of‐sample forecast performance of SLGG model is shown to be more accurate than the well‐known Li–Lee model. When it comes to model implications, a comparison of annuity pricing across space revealed that the SLGG model admits more regional pricing differences compared to the Li‐Lee model.

Suggested Citation

  • Kyran Cupido & Petar Jevtić & Tim J. Boonen, 2024. "Space, mortality, and economic growth," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1321-1337, August.
    • Handle: RePEc:wly:jforec:v:43:y:2024:i:5:p:1321-1337
    DOI: 10.1002/for.3086
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    References listed on IDEAS

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    1. Han Li & Colin O’Hare, 2019. "Mortality Forecasting: How Far Back Should We Look in Time?," Risks, MDPI, vol. 7(1), pages 1-15, February.
    2. Ludkovski, Mike & Risk, Jimmy & Zail, Howard, 2018. "Gaussian Process Models For Mortality Rates And Improvement Factors," ASTIN Bulletin, Cambridge University Press, vol. 48(3), pages 1307-1347, September.
    3. Malgorzata Seklecka & Norazliani Md. Lazam & Athanasios A. Pantelous & Colin O'Hare, 2019. "Mortality effects of economic fluctuations in selected eurozone countries," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(1), pages 39-62, January.
    4. Franks, P. & Jerant, A.F. & Leigh, J.P. & Lee, D. & Chiem, A. & Lewis, I. & Lee, S., 2007. "Cigarette prices, smoking, and the poor: Implications of recent trends," American Journal of Public Health, American Public Health Association, vol. 97(10), pages 1873-1877.
    5. Geng Niu & Bertrand Melenberg, 2014. "Trends in Mortality Decrease and Economic Growth," Demography, Springer;Population Association of America (PAA), vol. 51(5), pages 1755-1773, October.
    6. Li, Hong & Lu, Yang, 2017. "Coherent Forecasting Of Mortality Rates: A Sparse Vector-Autoregression Approach," ASTIN Bulletin, Cambridge University Press, vol. 47(2), pages 563-600, May.
    7. Yuhong Yang, 2005. "Can the strengths of AIC and BIC be shared? A conflict between model indentification and regression estimation," Biometrika, Biometrika Trust, vol. 92(4), pages 937-950, December.
    8. O’Hare, Colin & Li, Youwei, 2012. "Explaining young mortality," Insurance: Mathematics and Economics, Elsevier, vol. 50(1), pages 12-25.
    9. Malgorzata Seklecka & Athanasios A. Pantelous & Colin O'Hare, 2017. "Mortality effects of temperature changes in the United Kingdom," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(7), pages 824-841, November.
    10. Samir Soneji & Gary King, 2012. "Statistical Security for Social Security," Demography, Springer;Population Association of America (PAA), vol. 49(3), pages 1037-1060, August.
    11. Nan Li & Ronald Lee, 2005. "Coherent mortality forecasts for a group of populations: An extension of the lee-carter method," Demography, Springer;Population Association of America (PAA), vol. 42(3), pages 575-594, August.
    12. David Blake & Richard MacMinn, 2020. "Longevity Risk and Capital Markets: The 2016–2017 Update," North American Actuarial Journal, Taylor & Francis Journals, vol. 25(S1), pages 1-6, December.
    13. Su, Shu & Sherris, Michael, 2012. "Heterogeneity of Australian population mortality and implications for a viable life annuity market," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 322-332.
    14. Tim J. Boonen & Hong Li, 2017. "Modeling and Forecasting Mortality With Economic Growth: A Multipopulation Approach," Demography, Springer;Population Association of America (PAA), vol. 54(5), pages 1921-1946, October.
    15. Doukhan, P. & Pommeret, D. & Rynkiewicz, J. & Salhi, Y., 2017. "A class of random field memory models for mortality forecasting," Insurance: Mathematics and Economics, Elsevier, vol. 77(C), pages 97-110.
    16. David Blake & Richard MacMinn & Jason Chenghsien Tsai & Jennifer Wang, 2020. "Longevity Risk and Capital Markets: The 2017–2018 Update," North American Actuarial Journal, Taylor & Francis Journals, vol. 25(S1), pages 280-308, December.
    17. Ludkovski, Mike & Risk, Jimmy & Zail, Howard, 2018. "Gaussian Process Models For Mortality Rates And Improvement Factors – Corrigendum," ASTIN Bulletin, Cambridge University Press, vol. 48(3), pages 1349-1349, September.
    18. Joshua C. Hall & Donald J. Lacombe & Timothy M. Shaughnessy, 2019. "Economic Freedom And Income Levels Across U.S. States: A Spatial Panel Data Analysis," Contemporary Economic Policy, Western Economic Association International, vol. 37(1), pages 40-49, January.
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