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Explaining Applications to the U.S. Disability Program: A Semiparametric Approach

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  • Kreider, Brent
  • Riphahn, Regina

Abstract

This study investigates the determinants of applications for U.S. disability benefits between 1986 and 1993 using a semiparametric discrete factor procedure separately for men and women. Approximating a dynamic optimization model, the estimation accounts for a variety of potential biases that were unaddressed in prior studies. Our results indicate different responses of men and women to variations in policy measures. Past labor earnings and fringe benefits as well as benefit eligibility and benefit amounts clearly affect application behavior.

Suggested Citation

  • Kreider, Brent & Riphahn, Regina, 2000. "Explaining Applications to the U.S. Disability Program: A Semiparametric Approach," Staff General Research Papers Archive 5184, Iowa State University, Department of Economics.
    • Handle: RePEc:isu:genres:5184
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    Cited by:

    1. Bound, John & Stinebrickner, Todd & Waidmann, Timothy, 2010. "Health, economic resources and the work decisions of older men," Journal of Econometrics, Elsevier, vol. 156(1), pages 106-129, May.
    2. Pudney, Stephen, 2009. "Participation in disability benefit programmes: a partial identification analysis of the British Attendance Allowance system," ISER Working Paper Series 2009-19, Institute for Social and Economic Research.
    3. Iskhakov, Fedor, 2008. "Dynamic Programming Model of Health and Retirement," Memorandum 03/2008, Oslo University, Department of Economics.
    4. Pagán Rodríguez, Ricardo, 2007. "Dynamic Analysis of Disability in Spain Using the European Community Household Panel/Análisis dinámico de la discapacidad en España con el Panel de Hogares de la Unión Europea," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 25, pages 499-522, Abril.
    5. Richard V. Burkhauser & J. S. Butler & Gulcin Gumus, 2004. "Dynamic programming model estimates of Social Security Disability Insurance application timing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(6), pages 671-685.
    6. Naoko Akashi-Ronquest & Paul Carrillo & Bruce Dembling & Steven Stern, 2011. "Measuring the biases in self-reported disability status: evidence from aggregate data," Applied Economics Letters, Taylor & Francis Journals, vol. 18(11), pages 1053-1060.
    7. Pagán, Ricardo, 2013. "Time allocation of disabled individuals," Social Science & Medicine, Elsevier, vol. 84(C), pages 80-93.
    8. Burkhauser, Richard V. & Butler, J. S. & Gumus, Gulcin, 2003. "Option Value and Dynamic Programming Model Estimates of Social Security Disability Insurance Application Timing," IZA Discussion Papers 941, Institute of Labor Economics (IZA).
    9. Seth Giertz & Jeffrey Kubik, 2011. "The Disability Screening Process and the Labor Market Behavior of Accepted and Rejected Applicants: Evidence from the Health and Retirement Study," Journal of Labor Research, Springer, vol. 32(3), pages 237-253, September.
    10. Burkhauser, Richard V. & Butler, J. S. & Gumus, Gulcin, 2003. "Dynamic Modeling of the SSDI Application Timing Decision: The Importance of Policy Variables," IZA Discussion Papers 942, Institute of Labor Economics (IZA).
    11. Zhou Yang & Donna B. Gilleskie & Edward C. Norton, 2004. "Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics," NBER Working Papers 10964, National Bureau of Economic Research, Inc.

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