Estimating a COVID-19 crisis effect using AI techniques electrónico Christian Schwarz... [et al.]
Contributor(s): Schwarz, Christian
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Item type | Current location | Home library | Call number | Status | Date due | Barcode |
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Recursos electrónicos | IEF | IEF | ITPJ/2022/3-11 (Browse shelf) | Available | ITPJ/2022/3-11 |
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Disponible únicamente en formato electrónico
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In December 2020, the OECD released guidance on certain aspects of transfer pricing in view of the disruptive situation created by the COVID-19 pandemic. The comparability analysis was addressed therein as one of the main focus areas with regard to benchmarking and the collection of other quantitative evidence usually employed by corporate taxpayers in their transfer pricing documentation. As the burden of proof remains with the taxpayers and the question which quantitative approaches they could adopt has become highly relevant, this article provides some concrete examples for industry practitioners and other interested stakeholders demonstrating which kind of statistical methods and artificial intelligence-supported quantitative approaches can be employed to deliver robust empirical evidence ex ante for taxpayers’ compliance with the arm’s length principle in their intercompany transactions during a crisis situation like the COVID-19 pandemic and beyond.
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