IDEAS home Printed from https://ideas.repec.org/a/dem/demres/v28y2013i9.html

Gamma-Gompertz life expectancy at birth

Author

Listed:
  • Trifon Missov

    (Syddansk Universitet)

Abstract

Background: The gamma-Gompertz multiplicative frailty model is the most common parametric model applied to human mortality data at adult and old ages. The resulting life expectancy has been calculated so far only numerically. Objective: Properties of the gamma-Gompertz distribution have not been thoroughly studied. The focus of the paper is to shed light onto its first moment or, demographically speaking, characterize life expectancy resulting from a gamma-Gompertz force of mortality. The paper provides an exact formula for gamma-Gompertz life expectancy at birth and a simpler high-accuracy approximation that can be used in practice for computational convenience. In addition, the article compares actual (life-table) to model-based (gamma-Gompertz) life expectancy to assess on aggregate how many years of life expectancy are not captured (or overestimated) by the gamma-Gompertz mortality mechanism. Comments: A closed-form expression for gamma-Gomeprtz life expectancy at birth contains a special (the hypergeometric) function. It aids assessing the impact of gamma-Gompertz parameters on life expectancy values. The paper shows that a high-accuracy approximation can be constructed by assuming an integer value for the shape parameter of the gamma distribution. A historical comparison between model-based and actual life expectancy for Swedish females reveals a gap that is decreasing to around 2 years from 1950 onwards. Looking at remaining life expectancies at ages 30 and 50, we see this gap almost disappearing.

Suggested Citation

  • Trifon Missov, 2013. "Gamma-Gompertz life expectancy at birth," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 28(9), pages 259-270.
  • Handle: RePEc:dem:demres:v:28:y:2013:i:9
    DOI: 10.4054/DemRes.2013.28.9
    as

    Download full text from publisher

    File URL: https://www.demographic-research.org/volumes/vol28/9/28-9.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.4054/DemRes.2013.28.9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. James Vaupel & Kenneth Manton & Eric Stallard, 1979. "The impact of heterogeneity in individual frailty on the dynamics of mortality," Demography, Springer;Population Association of America (PAA), vol. 16(3), pages 439-454, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lucia Zanotto & Vladimir Canudas-Romo & Stefano Mazzuco, 2021. "A Mixture-Function Mortality Model: Illustration of the Evolution of Premature Mortality," European Journal of Population, Springer;European Association for Population Studies, vol. 37(1), pages 1-27, March.
    2. Hal Caswell, 2014. "A matrix approach to the statistics of longevity in heterogeneous frailty models," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 31(19), pages 553-592.
    3. Castellares, Fredy & Patrício, Silvio C. & Lemonte, Artur J., 2020. "On gamma-Gompertz life expectancy," Statistics & Probability Letters, Elsevier, vol. 165(C).
    4. Missov, Trifon I. & Lenart, Adam, 2013. "Gompertz–Makeham life expectancies: Expressions and applications," Theoretical Population Biology, Elsevier, vol. 90(C), pages 29-35.
    5. Hartemink, Nienke & Missov, Trifon I. & Caswell, Hal, 2017. "Stochasticity, heterogeneity, and variance in longevity in human populations," Theoretical Population Biology, Elsevier, vol. 114(C), pages 107-116.
    6. Jonas Šiaulys & Rokas Puišys, 2022. "Survival with Random Effect," Mathematics, MDPI, vol. 10(7), pages 1-17, March.
    7. María-Dolores Huete-Morales & Esteban Navarrete-Álvarez & María-Jesús Rosales-Moreno & María-José Del-Moral-Ávila & José-Manuel Quesada-Rubio, 2020. "Modelling the survival function of the Spanish population by the Wong–Tsui model with the incorporation of frailty and covariates," Letters in Spatial and Resource Sciences, Springer, vol. 13(2), pages 151-163, August.
    8. Castellares, Fredy & Patrício, Silvio C. & Lemonte, Artur J. & Queiroz, Bernardo L., 2020. "On closed-form expressions to Gompertz–Makeham life expectancy," Theoretical Population Biology, Elsevier, vol. 134(C), pages 53-60.
    9. James W. Vaupel & Trifon Missov, 2014. "Unobserved population heterogeneity," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 31(22), pages 659-686.
    10. Bijwaard, G.E.; & Jones, A.M.;, 2019. "Education and life-expectancy and how the relationship is mediated through changes in behaviour: a principal stratification approach for hazard rates," Health, Econometrics and Data Group (HEDG) Working Papers 19/05, HEDG, c/o Department of Economics, University of York.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wolfgang Drobetz & Lars Hornuf & Paul P. Momtaz & Niclas Schermann, 2025. "Token-Based Crowdfunding: Investor Choice and the Optimal Timing of Initial Coin Offerings," Entrepreneurship Theory and Practice, , vol. 49(1), pages 232-282, January.
    2. Bagdonavicius, Vilijandas & Nikulin, Mikhail, 2000. "On goodness-of-fit for the linear transformation and frailty models," Statistics & Probability Letters, Elsevier, vol. 47(2), pages 177-188, April.
    3. Yahia Salhi & Pierre-Emmanuel Thérond, 2016. "Age-Specific Adjustment of Graduated Mortality," Working Papers hal-01391285, HAL.
    4. Michael Murphy, 2010. "Reexamining the Dominance of Birth Cohort Effects on Mortality," Population and Development Review, The Population Council, Inc., vol. 36(2), pages 365-390, June.
    5. Feehan, Dennis & Wrigley-Field, Elizabeth, 2020. "How do populations aggregate?," SocArXiv 2fkw3, Center for Open Science.
    6. M. K. Lintu & Asha Kamath, 2022. "Performance of recurrent event models on defect proneness data," Annals of Operations Research, Springer, vol. 315(2), pages 2209-2218, August.
    7. Il Do Ha & Maengseok Noh & Youngjo Lee, 2010. "Bias Reduction of Likelihood Estimators in Semiparametric Frailty Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(2), pages 307-320, June.
    8. Yashin, Anatoli I. & Arbeev, Konstantin G. & Akushevich, Igor & Kulminski, Alexander & Akushevich, Lucy & Ukraintseva, Svetlana V., 2008. "Model of hidden heterogeneity in longitudinal data," Theoretical Population Biology, Elsevier, vol. 73(1), pages 1-10.
    9. Andreas Wienke & Anne M. Herskind & Kaare Christensen & Axel Skytthe & Anatoli I. Yashin, 2002. "The influence of smoking and BMI on heritability in susceptibility to coronary heart disease," MPIDR Working Papers WP-2002-003, Max Planck Institute for Demographic Research, Rostock, Germany.
    10. Stephen Gyimah & Alex Ezeh & J. Fotso, 2012. "Frailty models with applications to the study of infant deaths on birth timing in Ghana and Kenya," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(5), pages 1505-1521, August.
    11. Rasmus Hoffmann, 2005. "Does the socioeconomic mortality gradient interact with age? Evidence from US survey data and Danish register data," MPIDR Working Papers WP-2005-020, Max Planck Institute for Demographic Research, Rostock, Germany.
    12. Filipe Costa Souza & Wilton Bernardino & Silvio C. Patricio, 2024. "How life-table right-censoring affected the Brazilian social security factor: an application of the gamma-Gompertz-Makeham model," Journal of Population Research, Springer, vol. 41(3), pages 1-38, September.
    13. Maxim S. Finkelstein & Veronica Esaulova, 2005. "On mixture failure rate ordering," MPIDR Working Papers WP-2005-019, Max Planck Institute for Demographic Research, Rostock, Germany.
    14. Svetlana V. Ukraintseva & Anatoli I. Yashin, 2005. "Economic progress as cancer risk factor. I: Puzzling facts of cancer epidemiology," MPIDR Working Papers WP-2005-021, Max Planck Institute for Demographic Research, Rostock, Germany.
    15. Castellares, Fredy & Patrício, Silvio C. & Lemonte, Artur J., 2020. "On gamma-Gompertz life expectancy," Statistics & Probability Letters, Elsevier, vol. 165(C).
    16. Silke van Daalen & Hal Caswell, 2015. "Lifetime reproduction and the second demographic transition: Stochasticity and individual variation," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 33(20), pages 561-588.
    17. Shikhar Tyagi & Arvind Pandey & Christophe Chesneau, 2022. "Weighted Lindley Shared Regression Model for Bivariate Left Censored Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 655-682, November.
    18. Bessonova, Evguenia, 2023. "Firms’ efficiency, exits and government procurement contracts," European Journal of Political Economy, Elsevier, vol. 76(C).
    19. David McCarthy, 2021. "80 will be the new 70: Old‐age mortality postponement in the United States and its likely effect on the finances of the OASI program," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(2), pages 381-412, June.
    20. Hess , Wolfgang & Schwarzkopf , Larissa & Hunger , Matthias & Holle , Rolf, 2013. "Competing-Risks Duration Models with Correlated Random Effects: An Application to Dementia Patients’ Transition Histories," Working Papers 2013:28, Lund University, Department of Economics.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:dem:demres:v:28:y:2013:i:9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Editorial Office (email available below). General contact details of provider: https://www.demogr.mpg.de/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.