IDEAS home Printed from https://ideas.repec.org/a/spr/revepe/v4y2023i2d10.1007_s43253-022-00081-8.html
   My bibliography  Save this article

Multilevel modelling approach to analysing life course socioeconomic status and understanding missingness

Author

Listed:
  • Adrian Byrne

    (University of Nottingham)

  • Natalie Shlomo

    (University of Manchester)

  • Tarani Chandola

    (University of Hong Kong)

Abstract

This paper investigated the extent to which parental socioeconomic status was associated with life course socioeconomic status heterogeneity between adult cohort members of the 1958 National Child Development Study and how this association differed depending on methods used to address longitudinal missing data. We compared three variants of the full information maximum likelihood approach, namely available case, complete case and partially observed case and two methods designed to compensate for missing at random data, namely multilevel multiple imputation and multiple imputation chained equations. Our results highlighted the important contribution of parental socioeconomic status in explaining the divergence in achieved socioeconomic status over the adult life course, how the available case approach increasingly overestimated socioeconomic attainment as age increased and survey sample size decreased and how the complete case approach downwardly biased the effect of parental socioeconomic status on adult socioeconomic status.

Suggested Citation

  • Adrian Byrne & Natalie Shlomo & Tarani Chandola, 2023. "Multilevel modelling approach to analysing life course socioeconomic status and understanding missingness," Review of Evolutionary Political Economy, Springer, vol. 4(2), pages 275-297, July.
  • Handle: RePEc:spr:revepe:v:4:y:2023:i:2:d:10.1007_s43253-022-00081-8
    DOI: 10.1007/s43253-022-00081-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s43253-022-00081-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s43253-022-00081-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Denise Hawkes & Ian Plewis, 2006. "Modelling non‐response in the National Child Development Study," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 479-491, July.
    2. Bell, Andrew & Jones, Kelvyn, 2015. "Explaining Fixed Effects: Random Effects Modeling of Time-Series Cross-Sectional and Panel Data," Political Science Research and Methods, Cambridge University Press, vol. 3(1), pages 133-153, January.
    3. Martin Nybom & Jan Stuhler, 2016. "Heterogeneous Income Profiles and Lifecycle Bias in Intergenerational Mobility Estimation," Journal of Human Resources, University of Wisconsin Press, vol. 51(1), pages 239-268.
    4. Andrew Bell & Malcolm Fairbrother & Kelvyn Jones, 2019. "Fixed and random effects models: making an informed choice," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(2), pages 1051-1074, March.
    5. Steele, Fiona, 2008. "Multilevel models for longitudinal data," LSE Research Online Documents on Economics 52203, London School of Economics and Political Science, LSE Library.
    6. Stephen Nickell, 1982. "The Determinants of Occupational Success in Britain," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 49(1), pages 43-53.
    7. Martin Nybom & Jan Stuhler, 2017. "Biases in Standard Measures of Intergenerational Income Dependence," Journal of Human Resources, University of Wisconsin Press, vol. 52(3), pages 800-825.
    8. Yaojun Li & Fiona Devine, 2011. "Is Social Mobility Really Declining? Intergenerational Class Mobility in Britain in the 1990s and the 2000s," Sociological Research Online, , vol. 16(3), pages 28-41, August.
    9. Ganzeboom, H.B.G. & de Graaf, P.M. & Treiman, D.J. & de Leeuw, J., 1992. "A standard international socio-economic index of occupational status," WORC Paper 92.01.001/1, Tilburg University, Work and Organization Research Centre.
    10. Harvey Goldstein & James R. Carpenter & William J. Browne, 2014. "Fitting multilevel multivariate models with missing data in responses and covariates that may include interactions and non-linear terms," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 177(2), pages 553-564, February.
    11. Stanislav Kolenikov & Gustavo Angeles, 2009. "Socioeconomic Status Measurement With Discrete Proxy Variables: Is Principal Component Analysis A Reliable Answer?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 55(1), pages 128-165, March.
    12. Patrick Sturgis & Louise Sullivan, 2008. "Exploring social mobility with latent trajectory groups," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 65-88, January.
    13. Erzsebet Bukodi & Shirley Dex & John Goldthorpe, 2011. "The conceptualisation and measurement of occupational hierarchies: a review, a proposal and some illustrative analyses," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(3), pages 623-639, April.
    14. Fiona Steele, 2008. "Multilevel models for longitudinal data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 5-19, January.
    15. Asri Maharani & Gindo Tampubolon, 2014. "Unmet Needs for Cardiovascular Care in Indonesia," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-10, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Katia Begall, 2013. "How do educational and occupational resources relate to the timing of family formation? A couple analysis of the Netherlands," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(34), pages 907-936.
    2. Erzsébet Bukodi, 2012. "Serial Cohabitation among Men in Britain: Does Work History Matter? [Cohabitations successives des hommes en Angleterre : l’histoire professionnelle joue-t-elle un rôle ?]," European Journal of Population, Springer;European Association for Population Studies, vol. 28(4), pages 441-466, November.
    3. Gordey Yastrebov, 2021. "The Demographic Echo of War and educational attainment in Soviet Russia," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 45(22), pages 727-768.
    4. Guido Neidhöfer, 2019. "Intergenerational mobility and the rise and fall of inequality: Lessons from Latin America," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 17(4), pages 499-520, December.
    5. Chiswick, Barry R. & Wang, Zhiling, 2019. "Social Contacts, Dutch Language Proficiency and Immigrant Economic Performance in the Netherlands," GLO Discussion Paper Series 419, Global Labor Organization (GLO).
    6. Paul Gregg & Lindsey Macmillan & Claudia Vittori, 2017. "Moving Towards Estimating Sons' Lifetime Intergenerational Economic Mobility in the UK," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(1), pages 79-100, February.
    7. Yana Akhtyrska & Franz Fuerst, 2021. "People or Systems: Does Productivity Enhancement Matter More than Energy Management in LEED Certified Buildings?," Sustainability, MDPI, vol. 13(24), pages 1-35, December.
    8. Francesco Aiello & Graziella Bonanno, 2018. "Multilevel empirics for small banks in local markets," Papers in Regional Science, Wiley Blackwell, vol. 97(4), pages 1017-1037, November.
    9. Jirjahn, Uwe & Mohrenweiser, Jens, 2023. "Variable Payment Schemes and Productivity: Do Individual-Based Schemes Really Have a Stronger Influence than Collective Ones?," IZA Discussion Papers 16267, Institute of Labor Economics (IZA).
    10. Moshe Justman & Hadas Stiassnie, 2021. "Intergenerational Mobility in Lifetime Income," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(4), pages 928-949, December.
    11. Markus Jäntti & Stephen P. Jenkins, 2013. "Income Mobility," SOEPpapers on Multidisciplinary Panel Data Research 607, DIW Berlin, The German Socio-Economic Panel (SOEP).
    12. John Jerrim, 2014. "The link between family background and later lifetime income: how does the UK compare to other countries?," DoQSS Working Papers 14-02, Quantitative Social Science - UCL Social Research Institute, University College London.
    13. Celhay, Pablo & Gallegos, Sebastian, 2024. "Schooling Mobility across Three Generations in Six Latin American Countries," IZA Discussion Papers 17072, Institute of Labor Economics (IZA).
    14. Hillen, Judith & Fedoseeva, Svetlana, 2021. "E-commerce and the end of price rigidity?," Journal of Business Research, Elsevier, vol. 125(C), pages 63-73.
    15. Drasch, Katrin, 2011. "Do changing institutional settings matter? : educational attainment and family related employment interruptions in Germany," IAB-Discussion Paper 201113, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    16. Sharimakin, Akinsehinwa & Glass, Anthony J. & Saal, David S. & Glass, Karligash, 2018. "Dynamic multilevel modelling of industrial energy demand in Europe," Energy Economics, Elsevier, vol. 74(C), pages 120-130.
    17. Stefanie Heidrich, 2017. "Intergenerational mobility in Sweden: a regional perspective," Journal of Population Economics, Springer;European Society for Population Economics, vol. 30(4), pages 1241-1280, October.
    18. Fazio, Giorgio & Piacentino, Davide, 2018. "Convergence analysis for hierarchical longitudinal data," Economic Modelling, Elsevier, vol. 73(C), pages 89-99.
    19. Lara Abdel Fattah & Giuseppe Arcuri & Aziza Garsaa & Nadine Levratto, 2020. "Firm financial soundness and knowledge externalities: A comparative regional analysis," Papers in Regional Science, Wiley Blackwell, vol. 99(5), pages 1459-1486, October.
    20. Francesco Aiello & Graziella Bonanno & Stefania Patrizia Sonia Rossi, 2019. "Risk Aversion And Entrepreneurship: Financing Innovation For Smes Across Europe. Evidence From Multilevel Models," Working Papers 201902, Università della Calabria, Dipartimento di Economia, Statistica e Finanza "Giovanni Anania" - DESF.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:revepe:v:4:y:2023:i:2:d:10.1007_s43253-022-00081-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.