Searching for a big score: Analyzing drug yield from search warrant executions

In this study, we investigated the extent to which law enforcement efforts predicted drug and other kinds of illicit yield in search warrant executions. The data are drawn from one major metropolitan police department during 2005, 2009, and 2012. Using multilevel random intercept logistic regression models and multilevel random intercept multinomial logistic regression models, we regress high yields of various kinds of drugs and other illicit items seized during searches on the investigative activities that led to search warrant applications and the enlistment of teams of officers or other agencies in executing the search. Investments in high-effort search warrant work should generate higher yields than would be possible using less intensive law enforcement endeavors; yet our findings show that neither high-effort investigative activities, such as surveillance or controlled buys, nor the mobilization of specialized teams or agencies actually predict drug yield, even when search warrants lead to at least one felony drug arrest. This pattern raises questions about the efficacy of high-effort law enforcement activities and the costs, both financial and symbolic, of drug-related search warrant applications and executions. We discuss these findings in the context of police resources and inefficiencies associated with search warrant activity.