IDEAS home Printed from https://ideas.repec.org/a/wly/econjl/v127y2017i600p363-392.html

Early Interventions and Disability Insurance: Experience from a Field Experiment

Author

Listed:
  • Per Engström
  • Pathric Hägglund
  • Per Johansson

Abstract

This paper estimates the effects of early interventions in the Swedish sickness insurance system. The aim of the interventions is to screen and, further to, rehabilitate sick listed individuals. We find that the early interventions – in contrast to what is expected – increase the inflow into disability benefits by around 20 percent. In order to explain the results, we develop a simple theoretical model based on asymmetric information of the health status. The model predicts that the treatment effect is larger for individuals with low incentives to return to work. In order to test this prediction we estimate effects for sick listed employed and unemployed separately. Consistent with the model's prediction, we find that the effect is larger for the unemployed than for the employed.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Per Engström & Pathric Hägglund & Per Johansson, 2017. "Early Interventions and Disability Insurance: Experience from a Field Experiment," Economic Journal, Royal Economic Society, vol. 127(600), pages 363-392, March.
  • Handle: RePEc:wly:econjl:v:127:y:2017:i:600:p:363-392
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/ecoj.2017.127.issue-600
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Stijn Baert & Bas van der Klaauw & Gijsbert van Lomwel, 2018. "The effectiveness of medical and vocational interventions for reducing sick leave of self‐employed workers," Health Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 139-152, February.
    2. Jing Jian Xiao & Chunsheng Tao, 2020. "Consumer finance/household finance: the definition and scope," China Finance Review International, Emerald Group Publishing Limited, vol. 11(1), pages 1-25, June.
    3. Kai Rehwald & Michael Rosholm & Bénédicte Rouland, 2015. "Does Activating Sick-Listed Workers Work? Evidence from a Randomized Experiment," Working Papers hal-01228454, HAL.
    4. Aakvik, Arild & Holmås, Tor Helge & Kjerstad, Egil, 2015. "Prioritization and the elusive effect on welfare – A Norwegian health care reform revisited," Social Science & Medicine, Elsevier, vol. 128(C), pages 290-300.
    5. Forslund, Anders, 2019. "Employment outcomes and policies in Sweden during recent decades," Working Paper Series 2019:15, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    6. Arni, Patrick, 2012. "Kausale Evaluation von Pilotprojekten: Die Nutzung von Randomisierung in der Praxis," IZA Standpunkte 52, Institute of Labor Economics (IZA).
    7. Nina Granqvist & Pathric Hägglund & Stina Jakobsson, 2017. "Caseworkers’ attitudes: Do they matter?," Empirical Economics, Springer, vol. 52(4), pages 1271-1288, June.
    8. Rehwald, Kai & Rosholm, Michael & Rouland, Bénédicte, 2018. "Labour market effects of activating sick-listed workers," Labour Economics, Elsevier, vol. 53(C), pages 15-32.
    9. Anna Jędrzychowska, 2022. "A Bridge Life Insurance for Households—Diagnosis and Motives," Risks, MDPI, vol. 10(4), pages 1-21, April.

    More about this item

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • H55 - Public Economics - - National Government Expenditures and Related Policies - - - Social Security and Public Pensions
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:econjl:v:127:y:2017:i:600:p:363-392. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/resssea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.