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

Steele, Fiona and Grundy, Emily (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: Applied Statistics, 70 (1). 3 - 23. ISSN 0035-9254

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Identification Number: 10.1111/rssc.12446

Abstract

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.

Item Type: Article
Official URL: https://rss.onlinelibrary.wiley.com/journal/146798...
Additional Information: © 2020 The Authors
Divisions: Statistics
Subjects: H Social Sciences > HA Statistics
Date Deposited: 27 Aug 2020 09:21
Last Modified: 20 Aug 2021 02:40
URI: http://eprints.lse.ac.uk/id/eprint/106255

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