{"title":"Longitudinal analysis of exchanges of support between parents and children in the UK","authors":"F. Steele, Siliang Zhang, E. Grundy, T. Burchardt","doi":"10.1093/jrsssa/qnad110","DOIUrl":null,"url":null,"abstract":"\n We consider how exchanges of support between parents and adult children vary by demographic and socio-economic characteristics and examine evidence for reciprocity in transfers and substitution between practical and financial support. Using data from the UK Household Longitudinal Study 2011–19, repeated measures of help given and received are analysed jointly using multivariate random effects probit models. Exchanges are considered from both a child and parent perspective. In the latter case, we propose a novel approach to account for the correlation between mother and father reports and develop an efficient Markov chain Monte Carlo algorithm suitable for large datasets with multiple outcomes.","PeriodicalId":49983,"journal":{"name":"Journal of the Royal Statistical Society Series A-Statistics in Society","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Royal Statistical Society Series A-Statistics in Society","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1093/jrsssa/qnad110","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SOCIAL SCIENCES, MATHEMATICAL METHODS","Score":null,"Total":0}
引用次数: 1
Abstract
We consider how exchanges of support between parents and adult children vary by demographic and socio-economic characteristics and examine evidence for reciprocity in transfers and substitution between practical and financial support. Using data from the UK Household Longitudinal Study 2011–19, repeated measures of help given and received are analysed jointly using multivariate random effects probit models. Exchanges are considered from both a child and parent perspective. In the latter case, we propose a novel approach to account for the correlation between mother and father reports and develop an efficient Markov chain Monte Carlo algorithm suitable for large datasets with multiple outcomes.
期刊介绍:
Series A (Statistics in Society) publishes high quality papers that demonstrate how statistical thinking, design and analyses play a vital role in all walks of life and benefit society in general. There is no restriction on subject-matter: any interesting, topical and revelatory applications of statistics are welcome. For example, important applications of statistical and related data science methodology in medicine, business and commerce, industry, economics and finance, education and teaching, physical and biomedical sciences, the environment, the law, government and politics, demography, psychology, sociology and sport all fall within the journal''s remit. The journal is therefore aimed at a wide statistical audience and at professional statisticians in particular. Its emphasis is on well-written and clearly reasoned quantitative approaches to problems in the real world rather than the exposition of technical detail. Thus, although the methodological basis of papers must be sound and adequately explained, methodology per se should not be the main focus of a Series A paper. Of particular interest are papers on topical or contentious statistical issues, papers which give reviews or exposés of current statistical concerns and papers which demonstrate how appropriate statistical thinking has contributed to our understanding of important substantive questions. Historical, professional and biographical contributions are also welcome, as are discussions of methods of data collection and of ethical issues, provided that all such papers have substantial statistical relevance.