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Latent variable models for multivariate dyadic data with zero inflation: analysis of intergenerational exchanges of family support

Author

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  • Kuha, Jouni
  • Zhang, Siliang
  • Steele, Fiona

Abstract

Understanding the help and support that is exchanged between family members of different generations is of increasing importance, with research questions in sociology and social policy focusing on both predictors of the levels of help given and received, and on reciprocity between them. We propose general latent variable models for analysing such data, when helping tendencies in each direction are measured by multiple binary indicators of specific types of help. The model combines two continuous latent variables, which represent the helping tendencies, with two binary latent class variables which allow for high proportions of responses where no help of any kind is given or received. This defines a multivariate version of a zero inflation model. The main part of the models is estimated using MCMC methods, with a bespoke data augmentation algorithm. We apply the models to analyse exchanges of help between adult individuals and their non-coresident parents, using survey data from the UK Household Longitudinal Study.

Suggested Citation

  • Kuha, Jouni & Zhang, Siliang & Steele, Fiona, 2023. "Latent variable models for multivariate dyadic data with zero inflation: analysis of intergenerational exchanges of family support," LSE Research Online Documents on Economics 116006, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:116006
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    References listed on IDEAS

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    1. Steele, Fiona & Grundy, Emily, 2021. "Random effects dynamic panel models for unequally-spaced multivariate categorical repeated measures: an application to child-parent exchanges of support," LSE Research Online Documents on Economics 106255, London School of Economics and Political Science, LSE Library.
    2. Bakk, Zsuzsa & Kuha, Jouni, 2018. "Two-step estimation of models between latent classes and external variables," LSE Research Online Documents on Economics 85161, London School of Economics and Political Science, LSE Library.
    3. John C. Henretta & Matthew F. Voorhis & Beth J. Soldo, 2018. "Cohort Differences in Parental Financial Help to Adult Children," Demography, Springer;Population Association of America (PAA), vol. 55(4), pages 1567-1582, August.
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    5. Merril Silverstein & Stephen J. Conroy & Haitao Wang & Roseann Giarrusso & Vern L. Bengtson, 2002. "Reciprocity in Parent–Child Relations Over the Adult Life Course," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 57(1), pages 3-13.
    6. repec:ehl:lserod:61889 is not listed on IDEAS
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    10. Qian-Li Xue & Karen Bandeen-Roche, 2002. "Combining Complete Multivariate Outcomes with Incomplete Covariate Information: A Latent Class Approach," Biometrics, The International Biometric Society, vol. 58(1), pages 110-120, March.
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    13. Fiona Steele & Emily Grundy, 2021. "Random effects dynamic panel models for unequally spaced multivariate categorical repeated measures: an application to child–parent exchanges of support," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(1), pages 3-23, January.
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    More about this item

    Keywords

    item response theory models; latent class analysis; mixture models; two-step estimation; non-equivalence of measurement; ES/P000118/1; ES/P000118/1;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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