The Role of Kinship in Racial Differences in Exposure to Unemployment

Song, Xi; Caswell, Hal

doi:10.1215/00703370-10057831

Cited by 5 publications

(9 citation statements)

References 77 publications

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“…Although we have not explored it here, the results in Section 2.3.2 make it possible to assign weights that treat recent deaths and past deaths differently, effectively making it possible to account for Focal 'forgetting' the past. Because the model uses the matrix framework developed in Caswell (2019), it is easy to incorporate prevalences of conditions, such as health conditions (Caswell, 2019;Feng, Song, and Caswell, 2023) or employment status (Song and Caswell, 2022) into the living or dead components of the kinship network.…”

Section: Discussionmentioning

confidence: 99%

“…One might want to combine first degree kin (mother, daughter, sisters), second degree kin (grandmother, grandchildren, aunts, nieces), etc. (e.g., Song and Caswell, 2022). Or one might want to weight different types of kin by their coefficient of genetic relatedness.…”

Section: Aggregation Of Types Of Kinmentioning

confidence: 99%

“…Social support and exchange can travel through this network of available kin (Daw, Verdery, and Margolis, 2016). However, in addition to help and support flowing within a kinship network, there are also negative events that can affect kinship network members, such as the experience of unemployment in one's kinship network (Song and Caswell, 2022) or death (Verdery et al, 2020) of a family member.…”

Section: Introductionmentioning

confidence: 99%

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The formal demography of kinship V: Kin loss, bereavement, and causes of death

Caswell¹,

Margolis²,

Verdery³

2023

Preprint

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Background. The death of kin has psychological, physical, and economic effects on other members of a kinship network. Recently developed formal demographic models provide the deaths of kin, of any kind, at any age of a Focal individual. However, causes of death have yet to be accounted for. Objectives. Our objective is to extend the matrix kinship model to analyze losses of kin by cause of death, given age-specific schedules of risk due to each cause. Methods. The projection matrix is enlarged to include multiple absorbing states representing the age at death and the cause of death of kin at each age of Focal. The fertility matrix is enlarged to include production of living kin and set births by dead kin to zero. Results. The model provides deaths experienced at each age and accumulated up to each age of Focal, by cause of death and age at death. Causes of death are competing risks, permitting the study how the elimination of one cause displaces bereavement across kin types and age groups of the bereaved. As an example, we analyze kin death experiences attributable to each of the leading 15 causes of death in the United States non-Hispanic white female population.Contribution. Studies of the death of kin and bereavement of survivors can now take into account diverse causes of death, each with its own age schedule of risks. These results provide novel understandings of how different causes of death influence kinship structures and bereavement experiences among surviving kin.

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Section: Discussionmentioning

confidence: 99%

Section: Aggregation Of Types Of Kinmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The formal demography of kinship V: Kin loss, bereavement, and causes of death

Caswell¹,

Margolis²,

Verdery³

2023

Preprint

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“…Additional state variables can be added as in the age×parity model of Caswell (2020). And, time variation can be incorporated as in the models of Caswell and Song (2021) and Song and Caswell (2022).…”

Section: Discussionmentioning

confidence: 99%

“…In the EU as of 2014, women earned from 1% (Romania) to 24% (Estonia) less than men, with an average gap of 14% (Boll and Lagerman 2018). Song and Caswell (2022) analyzed unemployment among kin, but had to rely on applying the GKP factors to a one-sex model, and thus could not incorporate sex-specific unemployment. Such an analysis would be possible using the two-sex model.…”

Section: Discussionmentioning

confidence: 99%

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

Caswell¹

2022

DemRes

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BACKGROUNDPrevious 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. OBJECTIVEThe 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. METHODSThe 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. RESULTSThe 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. CONTRIBUTIONMany 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.

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The formal demography of kinship VI: Demographic stochasticity, variance, and covariance in the kinship network

Caswell

2024

Preprint

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Background: The matrix model for kinship networks includes many demographic processes but is deterministic, projecting expected values of age-stage distributions of kin. It provides no information on (co)variances. Because kin populations are small, demographic stochasticity is expected to create appreciable inter-individual variation. Objectives: To develop a stochastic kinship model to project (co)variances of kin age-stage distributions, and functions thereof, including demographic stochasticity. Methods: Kin populations are described by multitype branching processes. Means and covariances are projected using matrices that are generalizations of the deterministic model. The analysis requires only an age-specific mortality and fertility schedule. Both linear and non-linear transformations of the kin age distribution are treated as outputs accompanying the state equations. Results: The stochastic model follows the same mathematical framework as the deterministic model, modified to treat initial conditions as mixture distributions. Variances in numbers of most kin are compatible with Poisson distributions. Variances for parents and ancestors are compatible with binomial distributions. Prediction intervals are provided, as are probabilities of having at least one or two kin of each type. Prevalences of conditions are treated either as fixed or random proportions. Dependency ratios and their variances are calculated for any desired group of kin types. An example compares Japan under 1947 rates (high mortality, high fertility) and 2019 rates (low mortality, low fertility). Contribution: Previous versions of the kinship model have acknowledged their limitation to expected values. That limitation is now removed; means and variances are easily and quickly calculated with minimal modification of code.

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The Role of Kinship in Racial Differences in Exposure to Unemployment

Cited by 5 publications

References 77 publications

The formal demography of kinship V: Kin loss, bereavement, and causes of death

The formal demography of kinship V: Kin loss, bereavement, and causes of death

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

The formal demography of kinship VI: Demographic stochasticity, variance, and covariance in the kinship network

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