By Lucia Corno and Aureo de Paula
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.