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In and out of unemployment—Labour market transitions and the role of testosterone

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  • Eibich, Peter
  • Kanabar, Ricky
  • Plum, Alexander
  • Schmied, Julian

Abstract

Biological processes have provided new insights into diverging labour market trajectories. This paper uses population variation in testosterone levels to explain transition probabilities into and out of unemployment. We examine labour market transitions for 2004 initially employed and 111 initially unemployed British men from the UK Household Longitudinal Study (“Understanding Society”) between 2011 and 2013. We address the endogeneity of testosterone levels by using genetic variation as instrumental variables (Mendelian Randomization). We find that for both initially unemployed men as well as initially employed men, higher testosterone levels reduce the risk of unemployment. Based on previous studies and descriptive evidence, we argue that these effects are likely driven by differences in cognitive and non-cognitive skills as well as job search behaviour of men with higher testosterone levels. Our findings suggest that latent biological processes can affect job search behaviour and labour market outcomes without necessarily relating to illness and disability.

Suggested Citation

  • Eibich, Peter & Kanabar, Ricky & Plum, Alexander & Schmied, Julian, 2022. "In and out of unemployment—Labour market transitions and the role of testosterone," Economics & Human Biology, Elsevier, vol. 46(C).
  • Handle: RePEc:eee:ehbiol:v:46:y:2022:i:c:s1570677x22000193
    DOI: 10.1016/j.ehb.2022.101123
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    More about this item

    Keywords

    Labour market dynamics; Unemployment; Testosterone;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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