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MAXIMIZING THE TAX REVENUES FROM THE AUTOMATIC FINANCIAL ACCOUNT INFORMATION EXCHANGE SYSTEM

Description du projet

Un système efficace d’échange d’informations automatique

L’évasion et la fraude fiscales sont un problème mondial qui prive les gouvernements et la société de revenus substantiels essentiels au financement des dépenses publiques. La transparence fiscale est un outil politique essentiel pour s’attaquer à ce problème. En conséquence, plusieurs initiatives en matière de transparence fiscale ont été lancées, notamment un système mondial d’échange d’informations automatique (AEOI). Cependant, l’efficacité d’un tel système n’est pas bien comprise. Le projet TAXFAIR, financé par le programme MSCA, déterminera les caractéristiques qu’un système AEOI devrait avoir afin de maximiser l’extraction des recettes fiscales. Il combinera des informations provenant de deux ensembles de données: l’un comprenant des données administratives sur les résidents norvégiens et l’autre contenant des informations institutionnelles sur les systèmes AEOI mis en œuvre au niveau local. Dans l’ensemble, TAXFAIR fournira aux gouvernements du monde entier un cadre fondé sur la connaissance pour mettre en œuvre un système efficace d’échange d’informations automatique.

Objectif

Tax evasion represents a pervasive phenomenon and a substantial portion can be attributable to income held abroad. The general consensus at global level is that cross-border tax evasion can be fought effectively by further increasing information exchange between countries. Anecdotal evidence suggests that introducing a system for the automatic exchange of information (AEOI) is extremely costly. Yet, we lack a direct assessment of the related benefits. TAXFAIR aims to analyze the effectiveness of the AEOI system to mobilize tax revenues and to determine the characteristics of an AEOI system that maximizes tax revenue extraction. Specifically, 1. I will create a high-quality novel dataset based on administrative data on Norwegian residents and a dataset containing institutional information on locally implemented AEOI systems; 2. I will apply state-of-the-art regression models to the administrative dataset to quantify the tax revenue recovered from the introduction of a AEOI system; 3. By combining the institutional information dataset and the administrative dataset, I will empirically analyze the traits that maximize the tax revenues recovered from the local AEOI systems. Overall, TAXFAIR will provide a knowledge based framework for governments and policymakers which will allow them to increase the monetary resources highly needed for financing the recovery from the massive negative economic shock induced by the COVID19 pandemic.

While working on the action, I will develop new methodological skills (especially on machine learning), cross-sectorial skills (through the research stay at the IMF), stronger communication skills (by presenting at international conferences and via video clips), and further teaching and organizational skills (especially by organizing a case study competition joint with the industry). Overall, the MSCA fellowship will undoubtedly jump-start my career allowing me to emerge as an independent researcher with multiple attractive career pathways.

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Coordinateur

NORGES HANDELSHOYSKOLE
Contribution nette de l'UE
€ 226 751,04
Adresse
Helleveien 30
N-5045 Bergen
Norvège

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Région
Norge Vestlandet Vestland
Type d’activité
Higher or Secondary Education Establishments
Liens
Contribution de l’UE
Aucune donnée

Partenaires (1)