IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/10516.html
   My bibliography  Save this paper

HIV Breakthroughs and Risk Sexual Behavior

Author

Listed:
  • Dana Goldman
  • Darius Lakdawalla
  • Neeraj Sood

Abstract

Recent breakthroughs in the treatment of HIV have coincided with an increase in infection rates and an eventual slowing of reductions in HIV mortality. These trends may be causally related, if treatment improves the health and functional status of HIV+ individuals and allows them to engage in more sexual risk-taking. We examine this hypothesis empirically using access to health insurance as an instrument for treatment status. We find that treatment results in more sexual risk-taking by HIV+ adults, and possibly more of other risky behaviors like drug abuse. This relationship implies that breakthroughs in treating an incurable disease like HIV can increase precautionary behavior by the uninfected and thus reduce welfare. We also show that, in the presence of this effect, treatment and prevention are social complements for incurable diseases, even though they are substitutes for curable ones. Finally, there is less under-provision of treatment for an incurable disease than a curable one, because of the negative externalities associated with treating an incurable disease.

Suggested Citation

  • Dana Goldman & Darius Lakdawalla & Neeraj Sood, 2004. "HIV Breakthroughs and Risk Sexual Behavior," NBER Working Papers 10516, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:10516
    Note: EH
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w10516.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Nelson, Charles R & Startz, Richard, 1990. "Some Further Results on the Exact Small Sample Properties of the Instrumental Variable Estimator," Econometrica, Econometric Society, vol. 58(4), pages 967-976, July.
    2. Philipson, Tomas, 2000. "Economic epidemiology and infectious diseases," Handbook of Health Economics, in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 33, pages 1761-1799, Elsevier.
    3. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yacine Ait-Sahalia & Jonathan A. Parker & Motohiro Yogo, 2001. "Luxury Goods and the Equity Premium," NBER Working Papers 8417, National Bureau of Economic Research, Inc.
    2. Richard Blundell & Stephen Bond, 2000. "GMM Estimation with persistent panel data: an application to production functions," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 321-340.
    3. Abonazel, Mohamed R., 2016. "Bias Correction Methods for Dynamic Panel Data Models with Fixed Effects," MPRA Paper 70628, University Library of Munich, Germany.
    4. Bensch, Gunther & Gotz, Gunnar & Peters, Jörg, 2020. "Effects of rural electrification on employment: A comment on Dinkelman (2011)," Ruhr Economic Papers 840, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    5. Bhattacharya, Jayanta & Goldman, Dana & Sood, Neeraj, 2003. "The link between public and private insurance and HIV-related mortality," Journal of Health Economics, Elsevier, vol. 22(6), pages 1105-1122, November.
    6. Blundell, Richard & Bond, Stephen, 2023. "Reprint of: Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 234(S), pages 38-55.
    7. Iglesias Emma M., 2011. "Constrained k-class Estimators in the Presence of Weak Instruments," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(4), pages 1-13, September.
    8. Russell Davidson & James G. MacKinnon, 2006. "The case against JIVE," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 827-833, September.
    9. Bekker, Paul & Kleibergen, Frank, 2003. "Finite-Sample Instrumental Variables Inference Using An Asymptotically Pivotal Statistic," Econometric Theory, Cambridge University Press, vol. 19(5), pages 744-753, October.
    10. Guilhem Bascle, 2008. "Controlling for endogeneity with instrumental variables in strategic management research," Post-Print hal-00576795, HAL.
    11. Áureo De Paula & Gil Shapira & Petra E. Todd, 2014. "How Beliefs About Hiv Status Affect Risky Behaviors: Evidence From Malawi," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(6), pages 944-964, September.
    12. Erik Biørn, 2002. "Handling the measurement error problem by means of panel data: Moment methods applied on firm data," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 B6-1, International Conferences on Panel Data.
    13. Keisuke Hirano & Jack R. Porter, 2015. "Location Properties of Point Estimators in Linear Instrumental Variables and Related Models," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 720-733, December.
    14. Hoogerheide, Lennart & Kleibergen, Frank & van Dijk, Herman K., 2007. "Natural conjugate priors for the instrumental variables regression model applied to the Angrist-Krueger data," Journal of Econometrics, Elsevier, vol. 138(1), pages 63-103, May.
    15. Bekker, Paul A. & Lawford, Steve, 2008. "Symmetry-based inference in an instrumental variable setting," Journal of Econometrics, Elsevier, vol. 142(1), pages 28-49, January.
    16. Faff, Robert & Gray, Philip, 2006. "On the estimation and comparison of short-rate models using the generalised method of moments," Journal of Banking & Finance, Elsevier, vol. 30(11), pages 3131-3146, November.
    17. Marcelo Moreira & Geert Ridder, 2019. "Efficiency loss of asymptotically efficient tests in an instrumental variables regression," CeMMAP working papers CWP03/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    18. Daniel Aaronson & Eric French, 2004. "The Effect of Part-Time Work on Wages: Evidence from the Social Security Rules," Journal of Labor Economics, University of Chicago Press, vol. 22(2), pages 329-352, April.
    19. MacKinnon, James G., 2023. "Fast cluster bootstrap methods for linear regression models," Econometrics and Statistics, Elsevier, vol. 26(C), pages 52-71.
    20. Charles L. Baum & Christopher J. Ruhm, 2016. "The Changing Benefits of Early Work Experience," Southern Economic Journal, John Wiley & Sons, vol. 83(2), pages 343-363, October.

    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:10516. 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.

    If CitEc recognized a bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.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.