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Risk compensation among men in Zambia’s national program of voluntary medical male circumcision

Author

Listed:
  • Nicolas Grau

    (Ministry, Government of Chile)

  • Paul Hewett

    (U.S. NationalInstitutes of Health Center for Scientific Review)

  • Shreemayi Samujjwala

    (University of Pennsylvania)

  • Petra E. Todd

    (University of Pennsylvania)

Abstract

After initial RCTs demonstrated the effectiveness of voluntary medical male circumcision (VMMC) in reducing HIV transmission, 14 eastern and southern African countries implemented VMMC programs on a broad scale. Zambia was one of the first countries to adopt VMMC as part of its HIV prevention strategy. However, the demand for VMMC fell short of initial projections and there were also concerns that men may have increased their risky sexual behaviors after getting the procedure, offsetting the HIV risk reduction benefits. This paper uses a new longitudinal dataset for Zambia to investigate the determinants of VMMC demand and to test for risk compensation in the context of Zambia’s largescale VMMC implementation. The results show that most men understand VMMC benefits but express concerns about potential discomfort and missing work. Also, VMMC demand depends significantly on clinic proximity. Using six different measures of risky behavior and a variety of econometric panel data estimators, including ones that allow for unobserved heterogeneity and endogeneity, we find robust evidence that men who obtain VMMC do not increase risky behavior.

Suggested Citation

  • Nicolas Grau & Paul Hewett & Shreemayi Samujjwala & Petra E. Todd, 2025. "Risk compensation among men in Zambia’s national program of voluntary medical male circumcision," PIER Working Paper Archive 25-015, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    • Handle: RePEc:pen:papers:25-015
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    References listed on IDEAS

    as
    1. Jobiba Chinkhumba & Susan Godlonton & Rebecca Thornton, 2014. "The Demand for Medical Male Circumcision," American Economic Journal: Applied Economics, American Economic Association, vol. 6(2), pages 152-177, April.
    2. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects, and Econometric Policy Evaluation," Econometrica, Econometric Society, vol. 73(3), pages 669-738, May.
    3. Magne Mogstad & Andres Santos & Alexander Torgovitsky, 2018. "Using Instrumental Variables for Inference About Policy Relevant Treatment Parameters," Econometrica, Econometric Society, vol. 86(5), pages 1589-1619, September.
    4. repec:plo:pmed00:0020298 is not listed on IDEAS
    5. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    6. Peltzman, Sam, 1975. "The Effects of Automobile Safety Regulation," Journal of Political Economy, University of Chicago Press, vol. 83(4), pages 677-725, August.
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