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

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.