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Long-term employment effects of surviving cancer

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Author Info

  • Moran, John R.
  • Short, Pamela Farley
  • Hollenbeak, Christopher S.
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    Abstract

    We compare employment and usual hours of work for prime-age cancer survivors from the Penn State Cancer Survivor Survey to a comparison group drawn from the Panel Study of Income Dynamics using cross-sectional and difference-in-differences regression and matching estimators. Because earlier research has emphasized workers diagnosed at older ages, we focus on employment effects for younger workers. We find that as long as two to six years after diagnosis, cancer survivors have lower employment rates and work fewer hours than other similarly aged adults.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0167629611000257
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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Health Economics.

    Volume (Year): 30 (2011)
    Issue (Month): 3 (May)
    Pages: 505-514

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    Handle: RePEc:eee:jhecon:v:30:y:2011:i:3:p:505-514

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    Web page: http://www.elsevier.com/locate/inca/505560

    Related research

    Keywords: Cancer Employment Matching;

    References

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    1. Tommaso Nannicini, 2006. "A Simulation-Based Sensitivity Analysis for Matching Estimators," North American Stata Users' Group Meetings 2006 6, Stata Users Group.
    2. Bradley, Cathy J. & Bednarek, Heather L. & Neumark, David, 2002. "Breast cancer survival, work, and earnings," Journal of Health Economics, Elsevier, vol. 21(5), pages 757-779, September.
    3. Cathy Bradley & David Neumark & Heather Bednarek & Maryjean Schenk, 2004. "Short-term Effects of Breast Cancer on Labor Market Attachment: Results from a Longitudinal Study," PPIC Working Papers 2004.01, Public Policy Institute of California.
    4. Ichino, Andrea & Mealli, Fabrizia & Nannicini, Tommaso, 2006. "From Temporary Help Jobs to Permanent Employment: What Can We Learn from Matching Estimators and their Sensitivity?," CEPR Discussion Papers 5736, C.E.P.R. Discussion Papers.
    5. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," NBER Working Papers 6699, National Bureau of Economic Research, Inc.
    6. Heckman, James J & Ichimura, Hidehiko & Todd, Petra E, 1997. "Matching as an Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Wiley Blackwell, vol. 64(4), pages 605-54, October.
    7. Imbens, Guido & Abadie, Alberto, 2008. "On the Failure of the Bootstrap for Matching Estimators," Scholarly Articles 3043415, Harvard University Department of Economics.
    8. Heckman, James J. & Robb, Richard Jr., 1985. "Alternative methods for evaluating the impact of interventions : An overview," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 239-267.
    9. Markus Frölich, 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.
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    Citations

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    Cited by:
    1. Emmanuel Duguet & Christine Le Clainche, 2012. "Une évaluation de l'impact de l'aménagement des conditions de travail sur la reprise du travail après un cancer," Working Papers 12-25, LAMETA, Universtiy of Montpellier, revised Sep 2012.
    2. 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.
    3. David Candon, 2014. "The Effects of Cancer in the English Labour Market," Working Papers 201409, School Of Economics, University College Dublin.

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