Arbeitsbereich

Bevölkerungsdynamik und Nachhaltiges Wohlbefinden

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Projekt

From Ancestors to Descendants: Modeling Kinship Networks Across Centuries, 1751–2100 (Dissertation)

Liliana P. Calderón-Bernal, Martin Kolk (Stockholm University, Schweden), Emilio Zagheni; in Zusammenarbeit mit Diego Alburez-Gutierrez, Sha Jiang (beide: MPIDR)

Ausführliche Beschreibung

Kinship networks are an essential aspect of human life, surrounding individuals from birth until death. These networks extend family ties beyond the nuclear family, as they include relatives connected by biological, legal, or social bonds. Despite their significance as sources of support and intergenerational exchange throughout the life course, our understanding of kinship networks remains limited, primarily due to the scarcity of data providing information on kinship ties beyond the household.

There are two common approaches for estimating kinship networks within a population. One approach derives these networks empirically from data sources such as administrative registers, surveys, censuses, and, increasingly, online genealogical data. The other approach uses modeling techniques, including formal demographic methods and demographic microsimulation. As only a few countries worldwide have the high-quality demographic data necessary for the first approach, it is essential to consider methods for studying kinship in temporal and spatial contexts where detailed empirical data are unavailable or biased.

This project advances demographic microsimulation to analyze the structure and transformation of kinship networks over time, to compare microsimulation estimates with estimates derived from population registers and formal demographic kinship models, and to assess biases in genealogical and register data. In all studies, SOCSIM microsimulations are run using the MPIDR-developed “rsocsim” R-package.

The first study uses the SOCSIM microsimulation model to examine how three structural biases in ascendant genealogies – lineage survival, limited coverage of collateral kin, and selective omission of individuals – affect the accuracy of demographic estimates. We run SOCSIM microsimulations using Swedish data (1751–2022) to obtain “fully recorded” synthetic populations, which are used as benchmark to assess biases. We replicate the genealogical reconstruction process by introducing different types of biases that are common in genealogical data. We then compare fertility and mortality measures from “fully recorded” and “bias-infused” synthetic populations. The results show that the completeness of family trees is essential for obtaining accurate demographic estimates from genealogies. The second study examines the agreement of kin counts from SOCSIM microsimulation outputs and Swedish population registers. It traces the numbers of children, parents, grandchildren, grandparents, siblings, aunts and uncles, nieces and nephews, and cousins of synthetic individuals born between 1915 and 2017, and compares them with empirical counts. The results show that microsimulation closely approximates mean kin numbers and reasonably reflects parity distributions. It could also provide a more accurate representation of kin networks for older cohorts with incomplete register data. The third study examines the similarities and differences between the two main types of kinship models, demographic microsimulation and matrix kinship models, in stable and dynamic demographic settings between 1950 and 2100. It compares the models’ characteristics, assumptions, data requirements, and outputs, focusing on the means and distributions of the numbers and ages of different types of kin. The final study uses SOCSIM to examine the prevalence of having living parents, grandparents, and great-grandparents throughout the life course. It focuses on the mean numbers and years of life shared with ancestors for Swedish synthetic cohorts born between 1751 and 2000.

Schlagworte:

Demografischer Wandel, Historische Demografie, intergenerationelle Beziehungen

Schlagworte (Region):

China, Kolumbien, Schweden