2-step gradient boosting approach to selectivity bias correction in tax audit: an application to the VAT gap in Italy

DOI10.1007/s10260-022-00643-4zbMath1519.91168arXiv1912.03781MaRDI QIDQ6163506

Giovanna Tagliaferri, Daria Scacciatelli, Pierfrancesco Alaimo Di Loro

Publication date: 26 June 2023

Published in: Statistical Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1912.03781

zbMATH Keywords

selection biasmachine learninggradient boostingtax gap

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Macroeconomic theory (monetary models, models of taxation) (91B64)

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