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dc.contributor.authorLillestøl, Jostein
dc.date.accessioned2018-09-25T15:14:15Z
dc.date.available2018-09-25T15:14:15Z
dc.date.issued2018-09-25
dc.identifier.issn1500-4066
dc.identifier.urihttp://hdl.handle.net/11250/2564537
dc.description.abstractThis report deals with the analysis of data used by tax officers to support their claim of tax fraud at a pizzeria. The possibilities of embezzlement under study are overreporting of take-away sales and underreporting of cash payments. Several modelling approaches are explored, ranging from simple well-known methods to presumably more precise tools. More specifically, we contrast common methods based on normal assumptions and models based on Gamma-assumptions. For the latter, both maximum likelihood and Bayesian approaches are covered. Several criteria for the choice of method in practice are discussed, among them, how easy the method is to understand, justify and communicate to the parties. Some dilemmas present itself: the choice of statistical method, its role in building the evidence, the choice of risk factor, the application of legal principles like “clear and convincing evidence” and “beyond reasonable doubt”. The insights gained may be useful for both tax officers and defenders of the taxpayer, as well as for expert witnesses.nb_NO
dc.language.isoengnb_NO
dc.publisherFORnb_NO
dc.relation.ispartofseriesDiscussion paper;12/18
dc.subjectGamma-Beta analysisnb_NO
dc.subjectBayesian Gamma-analysisnb_NO
dc.subjectRisk analysisnb_NO
dc.titleSample statistics as convincing evidence: A tax fraud casenb_NO
dc.typeWorking papernb_NO
dc.source.pagenumber31nb_NO


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