922 resultados para Traffic law enforcement


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Agency Performance Report

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State Audit Reports

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FY 2006 Annual report for the Iowa Law Enforcement Academy as directed by the Director E.A. "Penny" Westfall

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FY 2005 Annual Report Per Director Westfall

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Annual Report

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Audit report on the Iowa Law Enforcement Academy for the year ended June 30, 2006

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FY2007 Annual Report

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Audit report on the Webster County Metropolitan Law Enforcement Telecommunications Board for the years ended June 30, 2007 and June 30, 2006

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Audit report on the Iowa Law Enforcement Academy for the year ended June 30, 2007

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This paper extends the optimal law enforcement literature to organized crime.We model the criminal organization as a vertical structure where the principal extracts some rents from the agents through extortion. Depending on the principal's information set, threats may or may not be credible. As long as threats are credible, the principal is able to fully extract rents.In that case, the results obtained by applying standard theory of optimal law enforcement are robust: we argue for a tougher policy. However, when threats are not credible, the principal is not able to fully extract rents and there is violence. Moreover, we show that it is not necessarily true that a tougher law enforcement policy should be chosen when in presence of organized crime.

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Agency Performance Plan, Iowa Law Enforcement Academy

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In this paper, we take an organizational view of organized crime. In particular, we study the organizational consequences of product illegality attending at the following characteristics: (i) contracts are not enforceable in court, (ii) all participants are subject to the risk of being punished, (iii) employees present a major threat to the entrepreneur having the most detailed knowledge concerning participation, (iv) separation between ownership and management is difficult because record-keeping and auditing augments criminal evidence.

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This report outlines the strategic plan for Iowa Law Enforcement Academy, goals and mission.

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We incorporate the process of enforcement learning by assuming that the agency's current marginal cost is a decreasing function of its past experience of detecting and convicting. The agency accumulates data and information (on criminals, on opportunities of crime) enhancing the ability to apprehend in the future at a lower marginal cost.We focus on the impact of enforcement learning on optimal stationary compliance rules. In particular, we show that the optimal stationary fine could be less-than-maximal and the optimal stationary probability of detection could be higher-than-otherwise.

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In this paper, we focus on the problem created by asymmetric informationabout the enforcer's (agent's) costs associated to enforcement expenditure. This adverse selection problem affects optimal law enforcement because a low cost enforcer may conceal its information by imitating a high cost enforcer, and must then be given a compensation to be induced to reveal its true costs. The government faces a trade-off between minimizing the enforcer's compensation and maximizing the net surplus of harmful acts. As a consequence, the probability of apprehension and punishment is usually reduced leading to more offenses being committed. We show that asymmetry of information does not affect law enforcement as long as raising public funds is costless. The consideration of costly raising of public funds permits to establish the positive correlation between asymmetry of information between government and enforcers andthe crime rate.