Data di Pubblicazione:
2024
Abstract:
In this paper, I describe the key features of big data in the social sciences, highlighting the essential role of theories in guiding researchers and practitioners. Theories are crucial because they (i) help focus attention on
conceptually significant variables and (ii) enable the exploration of causal relationships between these variables. I then examine how big data and machine learning techniques are being integrated into tax auditing practices, with a particular focus on the United States and Italy. Drawing on recent experimental evidence (Neuman and Sheu, 2022), I suggest that the impact of these technological advancements on overall tax morale might significantly depend on their transparency and the initial willingness of taxpayers to be equally transparent in
their taxable activities.
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
Big data, Tax evasion, Tax auditing, Tax morale, Machine learning, Reciprocity, ISA, evasione fiscale, accertamento tributario, disciplina fiscale, reciprocità
Elenco autori:
Puglisi, Riccardo
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