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Partially Identifying Treatment Effects with an Application to Covering the Uninsured

  • Brent Kreider
  • Steven C. Hill

We extend the nonparametric literature on partially identified probability distributions and use our analytical results to provide sharp bounds on the impact of universal health insurance on provider visits and medical expenditures. Our approach accounts for uncertainty about the reliability of self-reported insurance status as well as uncertainty created by unknown counterfactuals. We construct health insurance validation data using detailed information from the Medical Expenditure Panel Survey. Imposing relatively weak nonparametric assumptions, we estimate that under universal coverage monthly per capita provider visits and expenditures would rise by less than 8 percent and 16 percent, respectively, across the nonelderly population.

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File URL: http://jhr.uwpress.org/cgi/reprint/44/2/409
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Article provided by University of Wisconsin Press in its journal Journal of Human Resources.

Volume (Year): 44 (2009)
Issue (Month): 2 ()
Pages:

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Handle: RePEc:uwp:jhriss:v:44:y:2009:i2:p409-449
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  1. Charles F. Manski & John V. Pepper, 1998. "Monotone Instrumental Variables: With an Application to the Returns to Schooling," Virginia Economics Online Papers 308, University of Virginia, Department of Economics.
  2. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843 Elsevier.
  3. Manski, C.F., 1992. "Identification Problems in the Social Sciences," Working papers 9217, Wisconsin Madison - Social Systems.
  4. Molinari, Francesca, 2005. "Missing Treatments," Working Papers 05-11, Cornell University, Center for Analytic Economics.
  5. Bound, John & Burkhauser, Richard V., 1999. "Economic analysis of transfer programs targeted on people with disabilities," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 51, pages 3417-3528 Elsevier.
  6. Jonathan Gruber & Brigitte C. Madrian, 2002. "Health Insurance, Labor Supply, and Job Mobility: A Critical Review of the Literature," JCPR Working Papers 255, Northwestern University/University of Chicago Joint Center for Poverty Research.
  7. Hugo Benitez-Silva & Moshe Buchinsky & Hiu Man Chan & Sofia Cheidvasser & John Rust, 2000. "How Large is the Bias in Self-Reported Disability?," Working Papers 2000-01, Brown University, Department of Economics.
  8. Bollinger, Christopher R., 1996. "Bounding mean regressions when a binary regressor is mismeasured," Journal of Econometrics, Elsevier, vol. 73(2), pages 387-399, August.
  9. Mark C. Berger & Dan A. Black & Frank A. Scott, 1998. "How Well Do We Measure Employer-Provided Health Insurance Coverage?," Contemporary Economic Policy, Western Economic Association International, vol. 16(3), pages 356-367, 07.
  10. Kreider, Brent & Pepper, John V., 2003. "Disability and Employment: Reevaluating the Evidence in Light of Reporting Errors," Staff General Research Papers 10229, Iowa State University, Department of Economics.
  11. Craig A. Olson, 1998. "A comparison of parametric and semiparametric estimates of the effect of spousal health insurance coverage on weekly hours worked by wives," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(5), pages 543-565.
  12. Horowitz, Joel L & Manski, Charles F, 1995. "Identification and Robustness with Contaminated and Corrupted Data," Econometrica, Econometric Society, vol. 63(2), pages 281-302, March.
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