Evidence Briefing: Intergenerational Support. March 2023.
This briefing summarises key findings about practical and financial support across generations within families in Britain, including their policy and practical relevance.
Burchardt T, Steele F, Grundy E, Karagiannaki E, Kuha J, Moustaki I, Skinner C, Zhang N and Zhang S. Welfare within Families beyond Households: Intergenerational Exchanges of Practical and Financial Support in the UK. LSE Public Policy Review. 2021; 2(1): 4, pp. 1–11. DOI: https://doi.org/10.31389/lseppr.41
Families extend well beyond households. In particular, connections between parents and their adult offspring are often close and sustained, and transfers may include financial assistance, practical support, or both, provided by either generation to the other. Yet this major engine of welfare production, distribution, and redistribution has only recently become the focus of research. Who are the beneficiaries and to what extent are the patterns of exchange socially stratified? This article discusses findings from a programme of research analysing data from two nationally representative longitudinal studies, the British Household Panel Study and its successor Understanding Society, which record help given by, and received by, respondents through exchanges with their non-coresident parents and offspring in the UK. Some families exhibit a high tendency to provide mutual support between generations; these tendencies persist over time. Financial and practical support are generally complementary rather than substitutes. Longer travel time between parents and their offspring makes the provision of practical help less likely, whilst social class, social mobility, and ethnicity exhibit complex patterns of association with intergenerational exchanges. The resulting conclusion is that exchanges within families are an important complement to formal welfare institutions in the UK and that social policies should be designed to work with the grain of existing patterns of exchange, enabling family members to continue to provide help to one another, but ensuring that those who are less well supported by intergenerational assistance can access effective social protection.
Kuha, Jouni, Zhang, Siliang and Steele, Fiona. (2023) Latent variable models for multivariate dyadic data with zero inflation: Analysis of intergenerational exchanges of family support. Annals of Applied Statistics, 17(2), pp. 1521-1542. Have a look at the preprint.
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.t
Skinner, Chris J. and Steele, Fiona (2020) Estimation of dyadic characteristics of family networks using sample survey data. Annals of Applied Statistics, 14 (2). pp. 706-726. ISSN 1932-6157, http://eprints.lse.ac.uk/102338/
We consider the use of sample survey data to estimate dyadic characteristics of family networks, with an application to non-coresident parent-child dyads. We suppose that survey respondents report either from a parent or child perspective about a dyad, depending on their membership of the dyad. We construct separate estimators of com- mon dyadic characteristics using data from both a parent and a child perspective and show how comparisons of these estimators can shed light on data quality issues including differential missingness and re- porting error. In our application we find that a simple missingness model explains some striking patterns of discrepancies between the estimators and consider the use of poststratification and a related re- definition of count variables to adjust for these discrepancies. We also develop approaches to combining the separate estimators efficiently to estimate means and frequency distributions within subpopulations.
Steele, Fiona and Grundy, Emily (2020) 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), pp. 3-23.Take a look at the article.
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 and employment status and dependent children and data on exchanges of help collected at 2- and 5-year intervals are used.
Tania Burchardt "Reciprocity and the Welfare State", Panel Discussion of the new issue of the LSE Public Policy Review, Beveridge 2.0: Reciprocity Across the Life-Cycle, LSE online public event, 28 September 2021. Take a look at the webinar podcast and video.
Tania Burchardt “Intergenerational exchanges of practical and financial support within families across households”, Beveridge 2.0 Reciprocity Across the Life-cycle, STICERD, LSE, 23 February 2021. https://sticerd.lse.ac.uk/_new/research/beveridge/reciprocity-symposium.asp
Irini Moustaki “Modelling intergenerational exchanges using models for multivariate longitudinal data with latent variables in the presence of zero excess”, City University of New York (CUNY) Graduate Center, 1 April 2019.
Irini Moustaki “Modelling intergenerational exchanges using models for multivariate longitudinal data with latent variables in the presence of zero excess”, Center for Practice and Research at the Intersection of Information, Society and Methodology (PRIISM), NYU Steinhardt, 17 April 2019.
Jouni Kuha “Latent variables models for intergenerational exchanges of family support”, International Meeting of the Psychometric Society, Santiago (Chile), 15-19 July 2109.
Irini Moustaki “multivariate longitudinal data with zero inflation: a study of intergenerational exchanges”, International Meeting of the Psychometric Society, Santiago (Chile), 15-19 July 2019.
Fiona Steele “Dynamic models for longitudinal multivariate data with responses measured at unequal intervals”, Statistical Analysis of Multi-Outcome Data, University of Manchester, 6-7 June 2019 (keynote).
Fiona Steele “Random effects dynamic panel models for unequally-spaced outcomes”, Understanding Society Scientific Conference, University of Essex, 3 July 2019.
Fiona Steele “Random effects dynamic panel models for unequally-spaced outcomes”, International Workshop on Statistical Modeling, Guimarães, Portugal, 8-12 July 2019.
Fiona Steele “Random effects dynamic panel models for unequally-spaced outcomes”, 12th International Conference of the ERCIM Working Group on Computational and Methodological Statistics, University of London, 14-16 December 2019 (invited presentation).