IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/15085.html
   My bibliography  Save this paper

Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care

Author

Listed:
  • Amanda E. Kowalski

Abstract

The extent to which consumers respond to marginal prices for medical care is important for policy. Using recent data and a new censored quantile instrumental variable (CQIV) estimator, I estimate the price elasticity of expenditure on medical care. The CQIV estimator allows the estimates to vary across the skewed expenditure distribution, it allows for censoring at zero expenditure nonparametrically, and it allows for the insurance-induced endogenous relationship between price and expenditure. For identification, I rely on cost sharing provisions that generate marginal price differences between individuals who have injured family members and individuals who do not. I estimate the price elasticity of expenditure on medical care to be stable at -2.3 across the .65 to .95 conditional quantiles of the expenditure distribution. These quantile estimates are an order of magnitude larger than previous mean estimates. I consider several explanations for why price responsiveness is larger than previous estimates would suggest.

Suggested Citation

  • Amanda E. Kowalski, 2009. "Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care," NBER Working Papers 15085, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:15085
    Note: AG HC
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w15085.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Manning, Willard G, et al, 1987. "Health Insurance and the Demand for Medical Care: Evidence from a Randomized Experiment," American Economic Review, American Economic Association, vol. 77(3), pages 251-277, June.
    2. Mullahy, John, 1998. "Much ado about two: reconsidering retransformation and the two-part model in health econometrics," Journal of Health Economics, Elsevier, vol. 17(3), pages 247-281, June.
    3. Newey, Whitney K., 1987. "Efficient estimation of limited dependent variable models with endogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 36(3), pages 231-250, November.
    4. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 38(2), pages 112-134.
    5. Buntin, Melinda Beeuwkes & Zaslavsky, Alan M., 2004. "Too much ado about two-part models and transformation?: Comparing methods of modeling Medicare expenditures," Journal of Health Economics, Elsevier, vol. 23(3), pages 525-542, May.
    6. Hausman, Jerry A, 1985. "The Econometrics of Nonlinear Budget Sets," Econometrica, Econometric Society, vol. 53(6), pages 1255-1282, November.
    7. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
    8. Newhouse, Joseph P. & Phelps, Charles E. & Marquis, M. Susan, 1980. "On having your cake and eating it too : Econometric problems in estimating the demand for health services," Journal of Econometrics, Elsevier, vol. 13(3), pages 365-390, August.
    9. Willard G. Manning Jr. & Charles E. Phelps, 1979. "The Demand for Dental Care," Bell Journal of Economics, The RAND Corporation, vol. 10(2), pages 503-525, Autumn.
    10. Duan, Naihua, et al, 1983. "A Comparison of Alternative Models for the Demand for Medical Care," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 115-126, April.
    11. Keeler, Emmett B. & Rolph, John E., 1988. "The demand for episodes of treatment in the health insurance experiment," Journal of Health Economics, Elsevier, vol. 7(4), pages 337-367, December.
    12. Chernozhukov, Victor & Hansen, Christian, 2008. "Instrumental variable quantile regression: A robust inference approach," Journal of Econometrics, Elsevier, vol. 142(1), pages 379-398, January.
    13. Hong H. & Chernozhukov V., 2002. "Three-Step Censored Quantile Regression and Extramarital Affairs," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 872-882, September.
    Full references (including those not matched with items on IDEAS)

    More about this item

    JEL classification:

    • I1 - Health, Education, and Welfare - - Health

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:nbr:nberwo:15085. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: () or (Joanne Lustig). General contact details of provider: http://edirc.repec.org/data/nberrus.html .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.