112,853 research outputs found

    A Model of NGO Regulation with an Application to Uganda

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    We develop a model of regulation of service-delivery NGOs, where future grants are conditional on prior spending of some minimal proportion of current revenue on direct project-related expenses. Such regulation induces some NGOs to increase current project spending, but imposes wasteful costs of compliance verification on all NGOs. Under a large class of parametric configurations, we find that regulation increases total discounted project expenditure over a regime of no regulation, when verification costs constitute no more than 15% of initial revenue. We characterize the optimal regulatory policy under these configurations. We apply our analysis to a large sample of NGOs from Uganda, and find regulation to be beneficial in that context.regulation of non-governmental organizations, developing countries, Uganda

    A Model of NGO Regulation with an Application to Uganda

    Get PDF
    We develop a model of regulation of service-delivery NGOs, where future grants are conditional on prior spending of some minimal proportion of current revenue on direct project-related expenses. Such regulation induces some NGOs to increase current project spending, but imposes wasteful costs of compliance verification on all NGOs. Under a large class of parametric configurations, we find that regulation increases total discounted project expenditure over a regime of no regulation, when verification costs constitute no more than 15% of initial revenue. We characterize the optimal regulatory policy under these configurations. We apply our analysis to a large sample of NGOs from Uganda, and find regulation to be beneficial in that context.Regulation of non-governmental organizations, developing countries, Uganda

    The use of multilegged arguments to increase confidence in safety claims for software-based systems: A study based on a BBN analysis of an idealized example

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    The work described here concerns the use of so-called multi-legged arguments to support dependability claims about software-based systems. The informal justification for the use of multi-legged arguments is similar to that used to support the use of multi-version software in pursuit of high reliability or safety. Just as a diverse, 1-out-of-2 system might be expected to be more reliable than each of its two component versions, so a two-legged argument might be expected to give greater confidence in the correctness of a dependability claim (e.g. a safety claim) than would either of the argument legs alone. Our intention here is to treat these argument structures formally, in particular by presenting a formal probabilistic treatment of ‘confidence’, which will be used as a measure of efficacy. This will enable claims for the efficacy of the multi-legged approach to be made quantitatively, answering questions such as ‘How much extra confidence about a system’s safety will I have if I add a verification argument leg to an argument leg based upon statistical testing?’ For this initial study, we concentrate on a simplified and idealized example of a safety system in which interest centres upon a claim about the probability of failure on demand. Our approach is to build a BBN (“Bayesian Belief Network”) model of a two-legged argument, and manipulate this analytically via parameters that define its node probability tables. The aim here is to obtain greater insight than is afforded by the more usual BBN treatment, which involves merely numerical manipulation. We show that the addition of a diverse second argument leg can, indeed, increase confidence in a dependability claim: in a reasonably plausible example the doubt in the claim is reduced to one third of the doubt present in the original single leg. However, we also show that there can be some unexpected and counter-intuitive subtleties here; for example an entirely supportive second leg can sometimes undermine an original argument, resulting overall in less confidence than came from this original argument. Our results are neutral on the issue of whether such difficulties will arise in real life - i.e. when real experts judge real systems

    Dynamic Consistency of Conditional Simple Temporal Networks via Mean Payoff Games: a Singly-Exponential Time DC-Checking

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    Conditional Simple Temporal Network (CSTN) is a constraint-based graph-formalism for conditional temporal planning. It offers a more flexible formalism than the equivalent CSTP model of Tsamardinos, Vidal and Pollack, from which it was derived mainly as a sound formalization. Three notions of consistency arise for CSTNs and CSTPs: weak, strong, and dynamic. Dynamic consistency is the most interesting notion, but it is also the most challenging and it was conjectured to be hard to assess. Tsamardinos, Vidal and Pollack gave a doubly-exponential time algorithm for deciding whether a CSTN is dynamically-consistent and to produce, in the positive case, a dynamic execution strategy of exponential size. In the present work we offer a proof that deciding whether a CSTN is dynamically-consistent is coNP-hard and provide the first singly-exponential time algorithm for this problem, also producing a dynamic execution strategy whenever the input CSTN is dynamically-consistent. The algorithm is based on a novel connection with Mean Payoff Games, a family of two-player combinatorial games on graphs well known for having applications in model-checking and formal verification. The presentation of such connection is mediated by the Hyper Temporal Network model, a tractable generalization of Simple Temporal Networks whose consistency checking is equivalent to determining Mean Payoff Games. In order to analyze the algorithm we introduce a refined notion of dynamic-consistency, named \epsilon-dynamic-consistency, and present a sharp lower bounding analysis on the critical value of the reaction time \hat{\varepsilon} where the CSTN transits from being, to not being, dynamically-consistent. The proof technique introduced in this analysis of \hat{\varepsilon} is applicable more in general when dealing with linear difference constraints which include strict inequalities
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