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Saving Behaviour and Biomarkers: A High-Dimensional Bayesian Analysis of British Panel Data

Author

Listed:
  • Sarah Brown

    (Department of Economics, University of Sheffield)

  • Pulak Ghosh

    (Indian Institute of Management (IIMB), Bangalore, India)

  • Daniel Gray

    (Department of Economics, University of Sheffield)

  • Bhuvanesh Pareek

    (Indian Institute of Management (IIM), Indore, India)

  • Jennifer Roberts

    (Department of Economics, University of Sheffield)

Abstract

Using British panel data, we explore the relationship between saving behaviour and health,as measured by an extensive range of biomarkers, which are rarely available in large nationallyrepresentative surveys. The effects of these objective measures of health are compared withcommonly used self-assessed health measures. We develop a semi-continuous high-dimensionalBayesian modelling approach, which allows different data-generating processes for the decision tosave and the amount saved. We find that composite biomarker measures of health, as well asindividual biomarkers, are significant determinants of saving. Our results suggest that objectivebiomarker measures of health have differential impacts on saving behaviour compared to selfreported health measures, suggesting that objective health measures can further our understanding ofthe effect of health on financial behaviours.

Suggested Citation

  • Sarah Brown & Pulak Ghosh & Daniel Gray & Bhuvanesh Pareek & Jennifer Roberts, 2017. "Saving Behaviour and Biomarkers: A High-Dimensional Bayesian Analysis of British Panel Data," Working Papers 2017005, The University of Sheffield, Department of Economics.
    • Handle: RePEc:shf:wpaper:2017005
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    File URL: http://www.sheffield.ac.uk/economics/research/serps/articles/2017_005
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    References listed on IDEAS

    as
    1. Hendrik Jürges & Eberhard Kruk & Steffen Reinhold, 2013. "The effect of compulsory schooling on health—evidence from biomarkers," Journal of Population Economics, Springer;European Society for Population Economics, vol. 26(2), pages 645-672, April.
    2. Dana A. Glei & Noreen Goldman & Germán Rodríguez & Maxine Weinstein, 2014. "Beyond Self-Reports: Changes in Biomarkers as Predictors of Mortality," Population and Development Review, The Population Council, Inc., vol. 40(2), pages 331-360, June.
    3. Böckerman, Petri & Bryson, Alex & Viinikainen, Jutta & Hakulinen, Christian & Pulkki-Råback, Laura & Raitakari, Olli & Pehkonen, Jaakko, 2017. "Biomarkers and long-term labour market outcomes: The case of creatine," Journal of Economic Behavior & Organization, Elsevier, vol. 142(C), pages 259-274.
    4. Petri Bockerman & Alex Bryson & Christian Hakulinen & Jaakko Pehkonen & Laura Pulkki-Raback & Olli Raitakari & Jutta Viinikainen, 2014. "Biomarkers and Long-term Market Outcomes: The Case of Creatine," CEP Discussion Papers dp1279, Centre for Economic Performance, LSE.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    bayesian modelling; biomarkers; household finances; saving; two-part model.;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance

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