Optimum Corporation Criminal Sanctions

9309871阿伦这个项目将首次对刑事制裁对公司预防和侦查犯罪(“执法”)支出的影响进行经济分析。公司执行成本值得考虑，因为公司刑事制裁的一个核心目标是通过诱使公司将资源用于预防员工犯罪来阻止犯罪活动。该项目的第一部分将考虑当前量刑改革的趋势，即增加对公司罪犯的刑事罚款，以及增加刑事罚款会增加公司愿意花费资源防止员工犯罪的传统智慧的有效性。然后，该项目将确定在目前严格的替代公司责任制度下，公司刑事罚款的数额会导致公司将有效数额的资源用于预防和侦查犯罪。这个项目有望产生重要的见解，因为它对公司执行支出的关注迫使人们第一次认识到公司相互冲突的激励措施。一方面，刑事责任增加了公司在侦破犯罪上花费资源的动机，因为这些支出阻止了员工犯罪；另一方面，公司认识到，他们的执法努力可能会增加其代理人的罪行被发现的可能性，从而增加公司本身承担刑事责任的可能性。首席调查员将采用数学建模技术。***

9309871 ARLEN This project will conduct the first economic analysis of the impact of criminal sanctions on corporations' expenditures on crime prevention and detection ("enforcement"). Corporate enforcement costs warrant consideration because a central goal of corporate criminal sanctions is to deter criminal activity by inducing corporations to spend resources on preventing employee crime. The first section of the project will consider the current trend in sentencing reform towards increased criminal fines for corporate offenders, and the validity of the conventional wisdom that higher criminal fines increase corporations' willingness to spend resources to prevent their employees from committing crimes. The project then will determine what magnitude of corporate criminal fine induces corporations to spend the efficient amount of resources on crime prevention and detection under the current regime of strict vicarious corporate liability. This project can be expected to yield important insights because its focus on corporate enforcement expenditures forces recognition, for the first time, of corporations' conflicting incentives. On the one hand, criminal liability increases a corporation's incentives to spend resources on crime detection because these expenditures deter employees from committing crimes; on the other hand, corporations recognize that their enforcement efforts may increase the probability that their agents' crimes will be detected, thereby increasing the probability that the corporation itself will be subject to criminal liability. The Principal Investigator will employ mathematical modelling techniques. ***