We develop an algorithm for detecting teacher cheating that combines information on
unexpected test score fluctuations and suspicious patterns of answers for students in a classroom.
Using data from the Chicago Public Schools, we estimate that serious cases of teacher or
administrator cheating on standardized tests occur in a minimum of 4-5 percent of elementary
school classrooms annually. The observed frequency of cheating appears to respond strongly to
relatively minor changes in incentives. Our results highlight the fact that high-powered incentive
systems, especially those with bright line rules, may induce unexpected behavioral distortions
such as cheating. Statistical analysis, however, may provide a means of detecting illicit acts,
despite the best attempts of perpetrators to keep them clandestine.