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The effects of cancer in the English labour market

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  • David Candon

    (School of Economics and Geary Institute, University College Dublin)

Abstract

The continued rise in overall cancer survival rates has ignited a field of research which examines the effect that cancer has on survivors’ employment. Previous estimates of the effect of cancer on labour market outcomes, using U.S. data, show a significant reduction in employment and hours of work in the first 6 months after diagnosis. However, this impact has been found to dissipate after 2 years. I use data from the English Longitudinal Study of Ageing (ELSA) and find that, not only does cancer have a negative impact in the first 6-month period following diagnosis, but also in the second 6-month period. I estimate that, in the second 6-month period after diagnosis, respondents with cancer are 20.7 percentage points less likely to work and work 24% less hours a week when compared to matched, healthy controls. This suggests that the negative effects from cancer can persist for longer than the 6 months identified in previous studies. Results are significant at the 1% level. These results have implications for government policy and employers, because it increases both the length of time that survivors may be on government supported sick pay and the expected time that workers will be absent from work due to illness.

Suggested Citation

  • David Candon, 2014. "The effects of cancer in the English labour market," Working Papers 201408, Geary Institute, University College Dublin.
  • Handle: RePEc:ucd:wpaper:201408
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    References listed on IDEAS

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    1. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 605-654.
    2. Andrea Ichino & Fabrizia Mealli & Tommaso Nannicini, 2008. "From temporary help jobs to permanent employment: what can we learn from matching estimators and their sensitivity?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 305-327.
    3. Tommaso Nannicini, 2007. "Simulation-based sensitivity analysis for matching estimators," Stata Journal, StataCorp LP, vol. 7(3), pages 334-350, September.
    4. Markus Frlich, 2004. "Finite-Sample Properties of Propensity-Score Matching and Weighting Estimators," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 77-90, February.
    5. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
    6. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
    7. Heinesen, Eskil & Kolodziejczyk, Christophe, 2013. "Effects of breast and colorectal cancer on labour market outcomes—Average effects and educational gradients," Journal of Health Economics, Elsevier, vol. 32(6), pages 1028-1042.
    8. Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November.
    9. Bradley, Cathy J. & Neumark, David & Bednarek, Heather L. & Schenk, Maryjean, 2005. "Short-term effects of breast cancer on labor market attachment: results from a longitudinal study," Journal of Health Economics, Elsevier, vol. 24(1), pages 137-160, January.
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    Cited by:

    1. repec:eee:jhecon:v:58:y:2018:i:c:p:151-175 is not listed on IDEAS
    2. Kolodziejczyk, Christophe & Heinesen, Eskil, 2016. "Labour market participation after breast cancer for employees from the private and public sectors: Educational and sector gradients in the effect of cancer," Economics & Human Biology, Elsevier, vol. 21(C), pages 33-55.

    More about this item

    Keywords

    Labour market; Cancer; Employment; Hours worked;

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply

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