Year: 2023
Type: report
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 assessing how structural biases in ascendant genealogies affect the accuracy of demographic estimates.Using the SOCSIM microsimulation programme and Swedish fertility and mortality data (1751-2022), we analyse three biases: lineage survival, limited coverage of collateral kin, and selective omission.Comparing demographic measures from 'fully recorded' and 'bias-infused' synthetic populations, we find that across the period, including only direct ancestors can underestimate total fertility rate (TFR) (≈ -42%) and overestimate life expectancy at birth (e 0 ) (≈ +33%), mainly due to missing infant, child, and some young adult deaths.Including direct ancestors' offspring shifts TFR to overestimation (≈ +21%) while improving mortality estimation across all ages, with e 0 overestimation reduced to ≈ +1.8%.Our study shows that completeness of family trees is essential for obtaining accurate demographic estimates from genealogies.
Language: English
Subfield: Demography
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
OpenAlex ID: W4385841205