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Analysing biases in genealogies using demographic microsimulation

Author

Listed:
  • Liliana P. Calderón-Bernal

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Diego Alburez-Gutierrez

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Emilio Zagheni

    (Max Planck Institute for Demographic Research, Rostock, Germany)

Abstract

An incomplete understanding of biases affecting the representativeness of genealogies has hindered their full exploitation. We report on a series of experiments on synthetic populations designed to assess how different biases in ascendant genealogies can affect the accuracy of demographic estimates. Using the SOCSIM microsimulation programme and Swedish fertility and mortality data (1751-2022), we analyse three sources of bias: selection in direct lineages, incomplete reconstruction of family trees, and missing information on subpopulations. Comparing demographic measures derived from ‘fully-recorded’ and ‘bias-infused’ synthetic populations, we find that including only direct ancestors leads to underestimating total fertility rate (TFR) (c.a. −39%) before the fertility decline and overestimating life expectancy at birth (e0) (c.a. +42.2%) in the first two centuries. However, after including collateral kin, TFR underestimation was reduced to −2.4% and e0 overestimation limited to +1.5%. Our study shows that the completeness of family trees is essential for obtaining accurate demographic estimates.

Suggested Citation

  • Liliana P. Calderón-Bernal & Diego Alburez-Gutierrez & Emilio Zagheni, 2023. "Analysing biases in genealogies using demographic microsimulation," MPIDR Working Papers WP-2023-034, Max Planck Institute for Demographic Research, Rostock, Germany.
  • Handle: RePEc:dem:wpaper:wp-2023-034
    DOI: 10.4054/MPIDR-WP-2023-034
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    References listed on IDEAS

    as
    1. Mike Murphy, 2004. "Tracing very long-term kinship networks using SOCSIM," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 10(7), pages 171-196.
    2. Chen-Hao Hsu & Oliver Posegga & Kai Fischbach & Henriette Engelhardt, 2021. "Examining the trade-offs between human fertility and longevity over three centuries using crowdsourced genealogy data," PLOS ONE, Public Library of Science, vol. 16(8), pages 1-20, August.
    3. Ridhi Kashyap, 2021. "Has demography witnessed a data revolution? Promises and pitfalls of a changing data ecosystem," Population Studies, Taylor & Francis Journals, vol. 75(S1), pages 47-75, December.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    genealogy; historical demography; kinship; microsimulation;
    All these keywords.

    JEL classification:

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

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