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Risky sexual behavior: biological markers and self-reported data

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  • Corno, Lucia
  • de Paula, Aureo

Abstract

Self-reported data on sexual behaviors have been criticized to be unreliable. In recent studies, risky sexual behaviors have therefore been measured using biomarkers for curable sexually transmitted infections (STIs). Nevertheless, no previous research have tested how reliable such data are. In this paper, we first build an epidemiological model to assess the relative performance of biomarkers versus self-reported data. We then suggest an econometric strategy that combines both types of measures, biomarkers and self-reported data, to improve the estimation of correlates of risky sexual behaviors. Using the Demographic and Health Survey from Zambia, we calibrate the model and provide conditions under which self-reported data are a better proxy for risky sexual behaviors than biomarkers. In countries with low STIs prevalence, the biomarker has a higher probability of misclassification of risky behaviors than self-reported answers. Finally, we apply our estimation strategy to these data.

Suggested Citation

  • Corno, Lucia & de Paula, Aureo, 2014. "Risky sexual behavior: biological markers and self-reported data," CEPR Discussion Papers 10271, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:10271
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    Cited by:

    1. Oriana Bandiera & Niklas Buehren & Robin Burgess & Markus Goldstein & Selim Gulesci & Imran Rasul & Munshi Sulaiman, 2020. "Women's Empowerment in Action: Evidence from a Randomized Control Trial in Africa," American Economic Journal: Applied Economics, American Economic Association, vol. 12(1), pages 210-259, January.
    2. Martina Björkman Nyqvist & Lucia Corno & Damien de Walque & Jakob Svensson, 2018. "Incentivizing Safer Sexual Behavior: Evidence from a Lottery Experiment on HIV Prevention," American Economic Journal: Applied Economics, American Economic Association, vol. 10(3), pages 287-314, July.
    3. Wilson, Nicholas, 2016. "Antiretroviral therapy and demand for HIV testing: Evidence from Zambia," Economics & Human Biology, Elsevier, vol. 21(C), pages 221-240.
    4. Kibrom A. Abay & Leah E. M. Bevis & Christopher B. Barrett, 2021. "Measurement Error Mechanisms Matter: Agricultural Intensification with Farmer Misperceptions and Misreporting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(2), pages 498-522, March.
    5. Gong, Erick & de Walque, Damien & Dow, William H., 2019. "Coping with risk: Negative shocks, transactional sex, and the limitations of conditional cash transfers," Journal of Health Economics, Elsevier, vol. 67(C).
    6. Lépine, Aurélia & Treibich, Carole, 2020. "Risk aversion and HIV/AIDS: Evidence from Senegalese female sex workers," Social Science & Medicine, Elsevier, vol. 256(C).
    7. David Mmopelwa & Oliver Morrissey & Trudy Owens, 2021. "HIV/AIDS and sexual behaviour in Botswana," Discussion Papers 2021-03, University of Nottingham, CREDIT.

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    More about this item

    Keywords

    Biomarker; Misclassification; Risky behaviour; Self-reported;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I15 - Health, Education, and Welfare - - Health - - - Health and Economic Development

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