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Journal Article

Random effects dynamic panel models for unequally spaced multivariate categorical repeated measures: an application to child-parent exchanges of support

Authors

Publication date

07 Nov 2020

Summary

Exchanges of practical or financial help between people living in different households are a major component of intergenerational exchanges within families and an increasingly important source of support for individuals in need. Using longitudinal data, bivariate dynamic panel models can be applied to study the effects of changes in individual circumstances on help given to and received from non‐coresident parents and the reciprocity of exchanges. However, the use of a rotating module for collection of data on exchanges leads to data where the response measurements are unequally spaced and taken less frequently than for the time‐varying covariates. Existing approaches to this problem focus on fixed effects linear models for univariate continuous responses. We propose a random effects estimator for a family of dynamic panel models that can handle continuous, binary or ordinal multivariate responses. The performance of the estimator is assessed in a simulation study. A bivariate probit dynamic panel model is then applied to estimate the effects of partnership and employment transitions in the previous year and the presence and age of children in the current year on an individual’s propensity to give or receive help. Annual data on respondents’ partnership, employment status and dependent children, and data on exchanges of help collected at 2‐ and 5‐year intervals are used in this study.

Published in

Journal of the Royal Statistical Society Series C (Applied Statistics)

DOI

https://doi.org/10.1111/rssc.12446

ISSN

16

Subjects

Statistical Analysis, Social Networks, Demography, Households, Family Formation And Dissolution, Life Course Analysis, and Surveys

Notes

Online Early; Open Access; © 2020 The Authors. Journal of the Royal Statistical Society: Series C (Applied Statistics) published by John Wiley & Sons Ltd on behalf of Royal Statistical Society; This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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