IDEAS home Printed from https://ideas.repec.org/a/dem/demres/v47y2022i13.html
   My bibliography  Save this article

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

Author

Listed:
  • Hal Caswell

    (Universiteit van Amsterdam)

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
    as

    Download full text from publisher

    File URL: https://www.demographic-research.org/volumes/vol47/13/47-13.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.4054/DemRes.2022.47.13?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. 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 & Patrick Gerland & Nevena Lalic, 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.
    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. 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.
    2. Sha Jiang & Shripad Tuljapurkar & Hal Caswell & Zhen Guo & Wenyun Zuo, 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.
    3. 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.

    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. 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.
    2. Sha Jiang & Shripad Tuljapurkar & Hal Caswell & Zhen Guo & Wenyun Zuo, 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.
    3. 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.
    4. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    5. 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.
    6. Diego Alburez-Gutierrez & Ugofilippo Basellini & Emilio Zagheni, 2022. "When do parents bury a child? Quantifying uncertainty in the parental age at offspring loss," MPIDR Working Papers WP-2022-016, Max Planck Institute for Demographic Research, Rostock, Germany.
    7. Dominik Paprotny, 2021. "Convergence Between Developed and Developing Countries: A Centennial Perspective," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(1), pages 193-225, January.
    8. Dudel, Christian & Klüsener, Sebastian, 2019. "New opportunities for comparative male fertility research: Insights from a new data resource based on high-quality birth registers," SocArXiv 8kqws_v1, Center for Open Science.
    9. Muhammad Asif Wazir & Anne Goujon, 2019. "Assessing the 2017 Census of Pakistan Using Demographic Analysis: A Sub-National Perspective," VID Working Papers 1906, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna.
    10. Beatrice D. Simo-Kengne & Lumengo Bonga-Bonga, 2020. "House prices and fertility in South Africa: A spatial econometric analysis," Economics Bulletin, AccessEcon, vol. 40(4), pages 3193-3210.
    11. Linus Andersson, 2023. "The Role of Gender Differences in Partnering and Re-partnering for Gender Differences in Completed Fertility," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 42(2), pages 1-28, April.
    12. Blake, David & Cairns, Andrew J.G., 2021. "Longevity risk and capital markets: The 2019-20 update," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 395-439.
    13. Diego Alburez-Gutierrez, 2021. "The demographic drivers of grief and memory after genocide in Guatemala," MPIDR Working Papers WP-2021-003, Max Planck Institute for Demographic Research, Rostock, Germany.
    14. Bijak Jakub & Bryant Johan & Gołata Elżbieta & Smallwood Steve, 2021. "Preface," Journal of Official Statistics, Sciendo, vol. 37(3), pages 533-541, September.
    15. Christian Dudel & Sebastian Klüsener, 2019. "New opportunities for comparative male fertility research: insights from a new data resource based on high-quality birth registers," MPIDR Working Papers WP-2019-023, Max Planck Institute for Demographic Research, Rostock, Germany.
    16. José Henrique Costa Monteiro da Silva & Everton Emanuel Campos de Lima & Maria Coleta Ferreira Albino de Oliveira, 2022. "Educational pairings and fertility decline in Brazil: An analysis using cohort fertility," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 46(6), pages 147-178.
    17. Dudel, Christian & Klüsener, Sebastian, 2019. "New opportunities for comparative male fertility research: Insights from a new data resource based on high-quality birth registers," SocArXiv 8kqws, Center for Open Science.
    18. de Jong, Piet & Tickle, Leonie & Xu, Jianhui, 2016. "Coherent modeling of male and female mortality using Lee–Carter in a complex number framework," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 130-137.
    19. Shang, Han Lin & Smith, Peter W.F. & Bijak, Jakub & Wiśniowski, Arkadiusz, 2016. "A multilevel functional data method for forecasting population, with an application to the United Kingdom," International Journal of Forecasting, Elsevier, vol. 32(3), pages 629-649.
    20. 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.

    More about this item

    Keywords

    kinship; matrix models; two-sex models; male fertility; female fertility; sex ratio;
    All these 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:47:y:2022:i:13. 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.