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Law enforcement by the U.S. Coast Guard (USCG) is characterized by soft penalties for safety violations, low incidence of penalties relative to the number of violations, and substantial resources devoted to inspections of vessels. Under what conditions can such an enforcement strategy be effective? And is it? This article seeks answers to these two questions. Harrington's (1988 ) model is motivated by such facts about U.S. regulation in general, and provides an answer to the first question via targeting of good and poor performers. The model generates hypotheses about optimal regulation in the context of pollution prevention activities of the USCG. In order to answer the second question, an organization‐level panel data set consisting of thousands of U.S. flag tank barges is constructed and those hypotheses tested. A count model that controls for vessel heterogeneity yields mixed evidence. If USCG inspections are considered exogenous variables (as the theory presumes), they appear to prevent pollution spills. But if inspections are endogenous and respond to previous spills, then correcting for endogeneity reverses the earlier result. In addition, violations are found to be good predictors of pollution occurrences, suggesting that inspections are not as effective as they could be. Targeting, as in Harrington's model, therefore appears to be incomplete, and the findings suggest that more complete targeting could increase performance. An interesting finding is that stronger penalties could increase performance.  相似文献   
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