Corruption estimates rely largely on self-reports of affected individuals and officials. Yet survey respondents are often reticent to tell the truth about sensitive subjects, leading to downward biases in surveybased corruption estimates. This paper develops a method to estimate the prevalence of reticent behavior and reticence-adjusted rates of corruption using survey responses to sensitive questions. A statistical model captures how respondents answer a combination of conventional and randomresponse questions, allowing identification of the effect of reticence. GMM and maximum likelihood estimates are obtained for ten countries. Adjusting for reticence dramatically alters the perceptions of the extent of corruption.