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On the effectiveness of case management for people with disabilities

Author

Listed:
  • Matthias Draheim

    (AXA Switzerland)

  • Peter Schanbacher

    (Furtwangen University)

  • Ruben Seiberlich

    (ZHAW School of Management and Law)

Abstract

Case managers provide individual and comprehensive support to employees who have become incapable of working. Using data from a large insurance company we find that overall, 43.9% of the people in our sample could be reintegrated. Controlling for personal characteristics, we analyze the effectiveness of case management by modelling the probability of reintegrating people being incapable of working into the labor market. Using parametric and semiparametric decomposition methods, we control for observational differences. We analyze how much of the difference in the reintegration rate between people who participate in case management and those who do not, is due to differences in characteristics and how much is due to case management itself. We find that the estimated probability of reintegration is 18.9% higher if people participate in case management. Moreover, our results show that no more than 15% are due to differences in characteristics and at least 85% can be attributed to case management itself.

Suggested Citation

  • Matthias Draheim & Peter Schanbacher & Ruben Seiberlich, 2021. "On the effectiveness of case management for people with disabilities," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 55(1), pages 1-16, December.
  • Handle: RePEc:spr:jlabrs:v:55:y:2021:i:1:d:10.1186_s12651-021-00299-9
    DOI: 10.1186/s12651-021-00299-9
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    1. Gesine Stephan & André Pahnke, 2011. "The Relative Effectiveness Of Selected Active Labor Market Programs: An Empirical Investigation For Germany," Manchester School, University of Manchester, vol. 79(6), pages 1262-1293, December.
    2. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
    3. Cardano, Mario & Costa, Giuseppe & Demaria, Moreno, 2004. "Social mobility and health in the Turin longitudinal study," Social Science & Medicine, Elsevier, vol. 58(8), pages 1563-1574, April.
    4. Michael Lechner & Anthony Strittmatter, 2019. "Practical procedures to deal with common support problems in matching estimation," Econometric Reviews, Taylor & Francis Journals, vol. 38(2), pages 193-207, February.
    5. Strittmatter, Anthony & Wunsch, Conny, 2021. "The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?," Working papers 2021/05, Faculty of Business and Economics - University of Basel.
    6. Jinyong Hahn, 1998. "On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects," Econometrica, Econometric Society, vol. 66(2), pages 315-332, March.
    7. Richard V. Burkhauser & Mary C. Daly & Nicolas R. Ziebarth, 2016. "Protecting working-age people with disabilities: experiences of four industrialized nations [Absicherung von Personen mit Erwerbsminderung: Erfahrungen aus vier Industrieländern]," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 49(4), pages 367-386, December.
    8. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    9. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2009. "Dealing with limited overlap in estimation of average treatment effects," Biometrika, Biometrika Trust, vol. 96(1), pages 187-199.
    10. Paul T E Cusack, 2020. "On Pain," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 31(3), pages 24253-24254, October.
    11. Stephan Gesine, 2008. "The Effects of Active Labor Market Programs in Germany: An Investigation Using Different Definitions of Non-Treatment," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(5-6), pages 586-611, October.
    12. repec:iab:iabjlr:v:53:i:1:p:art.9 is not listed on IDEAS
    13. Fortin, Nicole & Lemieux, Thomas & Firpo, Sergio, 2011. "Decomposition Methods in Economics," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 1, pages 1-102, Elsevier.
    14. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    15. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, January.
    16. Thomas Bauer & Mathias Sinning, 2008. "An extension of the Blinder–Oaxaca decomposition to nonlinear models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(2), pages 197-206, May.
    17. Fredriksson, Peter & Johansson, Per, 2008. "Dynamic Treatment Assignment," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 435-445.
    18. Alan S. Blinder, 1973. "Wage Discrimination: Reduced Form and Structural Estimates," Journal of Human Resources, University of Wisconsin Press, vol. 8(4), pages 436-455.
    19. Galizzi, Monica & Leombruni, Roberto & Pacelli, Lia, 2019. "Successful return to work during labor market liberalization: The case of Italian injured workers," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 53(1), pages 1-9.
    20. Jin-Won Noh & Jinseok Kim & Jumin Park & Hyun-jung Kim & Young Dae Kwon, 2015. "Gender Difference in Relationship between Health-Related Quality of Life and Work Status," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-8, December.
    21. Monica Galizzi & Roberto Leombruni & Lia Pacelli, 2019. "Successful return to work during labor market liberalization: the case of Italian injured workers," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 53(1), pages 1-24, December.
    22. Galizzi, Monica & Leombruni, Roberto & Pacelli, Lia, 2019. "Successful return to work during labor market liberalization: The case of Italian injured workers," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 53(1), pages .9(1-24).
    23. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
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    More about this item

    Keywords

    Return to work; Insurance; Case management; Labor force participation; Individual support on reintegration; Logistic regression; Decomposition; Propensity score matching;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private

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