Risky Sexual Behaviours: Biological Markers and Self-reported Data

High-risk sexual behaviours are generally unobserved and difficult to identify. In this paper, we investigate the accuracy of two risky-behaviour measures: biomarkers for sexually transmitted infections (STIs) and self-reported data. We 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 to estimate actual unobserved risky sexual behaviours. Using data from the Demographic and Health Survey in 28 countries, we calibrate the model and provide conditions under which self-reported data are a better proxy for risky sexual behaviours than biomarkers. In countries with low STI prevalence, biomarkers have a higher probability of misclassification than self-reported answers. We apply our econometric strategy to the data and show that the probability of actual risky behaviour is much higher than the probability of self-reported risky behaviour and of testing positive for an STI.