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The formal demography of kinship IV: Two-sex models and their approximations

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  • Hal Caswell

    (Woods Hole Oceanographic Institute)

Abstract

Background: Previous kinship models analyze female kin through female lines of descent, neglecting male kin and male lines of descent. Because males and females differ in mortality and fertility, including both sexes in kinship models is an important unsolved problem. Objective: The objectives are to develop a kinship model including female and male kin through all lines of descent, to explore approximations when full sex-specific rates are unavailable, and to apply the model to several populations as an example. Methods: The kin of a focal individual form an age×sex-classified population and are projected as Focal ages using matrix methods, providing expected age-sex structures for every type of kin at every age of Focal. Initial conditions are based on the distribution of ages at maternity and paternity. Results: The equations for two-sex kinship dynamics are presented. As an example, the model is applied to populations with large (Senegal), medium (Haiti), and small (France) differences between female and male fertility. Results include numbers and sex ratios of kin as Focal ages. An approximation treating female and male rates as identical provides some insight into kin numbers, even when male and female rates are very different. Contribution: Many demographic and sociological parameters (e.g., aspects of health, bereavement, labor force participation) differ markedly between the sexes. This model permits analysis of such parameters in the context of kinship networks. The matrix formulation makes it possible to extend the two-sex analysis to include kin loss, multistate kin demography, and time varying rates.

Suggested Citation

  • Hal Caswell, 2022. "The formal demography of kinship IV: Two-sex models and their approximations," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 47(13), pages 359-396.
  • Handle: RePEc:dem:demres:v:47:y:2022:i:13
    DOI: 10.4054/DemRes.2022.47.13
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    References listed on IDEAS

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    1. Hal Caswell & Xi Song, 2021. "The formal demography of kinship III: Kinship dynamics with time-varying demographic rates," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 45(16), pages 517-546.
    2. Adrian E. Raftery & Nevena Lalic & Patrick Gerland, 2014. "Joint probabilistic projection of female and male life expectancy," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 30(27), pages 795-822.
    3. Hal Caswell, 2020. "The formal demography of kinship II: Multistate models, parity, and sibship," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 42(38), pages 1097-1146.
    4. Bruno Schoumaker, 2019. "Male Fertility Around the World and Over Time: How Different is it from Female Fertility?," Population and Development Review, The Population Council, Inc., vol. 45(3), pages 459-487, September.
    5. Hal Caswell, 2019. "The formal demography of kinship: A matrix formulation," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 41(24), pages 679-712.
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    Cited by:

    1. Sha Jiang & Diego Alburez-Gutierrez & Pil H. Chung & Monica J. Alexander, 2025. "Measuring kinship dependency: a cross-national comparison across care regimes," MPIDR Working Papers WP-2025-024, Max Planck Institute for Demographic Research, Rostock, Germany.
    2. Butterick, Joe W.B. & Smith, Peter W.F. & Bijak, Jakub & Hilton, Jason, 2025. "A mathematical framework for time-variant multi-state kinship modelling," Theoretical Population Biology, Elsevier, vol. 163(C), pages 1-12.
    3. Sha Jiang & Haili Liang & Diego Alburez-Gutierrez & Emilio Zagheni, 2025. "Human capital investment helps mitigate family caregiving challenges in aging China," MPIDR Working Papers WP-2025-021, Max Planck Institute for Demographic Research, Rostock, Germany.
    4. Sha Jiang & Wenyun Zuo & Hal Caswell & Zhen Guo & Shripad Tuljapurkar, 2023. "How does the demographic transition affect kinship networks?," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 48(32), pages 899-930.
    5. Leonie Diffené & Thomas Leopold & Zafer Buyukkececi & Marcel Raab, 2026. "Click, collect, compare: Evaluating a nonprobability web survey for family demography," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 54(42), pages 1375-1412.
    6. Hal Caswell, 2024. "The formal demography of kinship VI: Demographic stochasticity and variance in the kinship network," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 51(39), pages 1201-1256.
    7. Hal Caswell & Rachel Margolis & Ashton Verdery, 2023. "The formal demography of kinship V: Kin loss, bereavement, and causes of death," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 49(41), pages 1163-1200.
    8. Liliana P. Calderón-Bernal & Diego Alburez-Gutierrez & Martin Kolk & Emilio Zagheni, 2025. "Assessing the agreement between microsimulated and register-based kin counts in Sweden," MPIDR Working Papers WP-2025-020, Max Planck Institute for Demographic Research, Rostock, Germany.
    9. Moretti, Margherita & Balbo, Nicoletta & Tosi, Marco & Alburez-Gutierrez, Diego, 2026. "Disability in the kinship network: population-level exposure to kin with disability across ages in Europe," SocArXiv udmkh_v1, Center for Open Science.
    10. Joe Butterick & Jason Hilton & Peter W F Smith & Jakub Bijak & Erengul Dodd, 2026. "Probabilistic projections of distributions of kin over the life course," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 54(9), pages 263-308.

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    JEL classification:

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

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