How Useful Are Tax Disclosures in Predicting Effective Tax Rates? A Machine Learning Approach

نویسندگان

چکیده

ABSTRACT We investigate (1) how well a machine learning algorithm can predict one-year ahead effective tax rates (ETRs) and (2) which items in the financial statements notes are most useful for these predictions. compare our machine-generated ETR predictions with those from ETRs implied by analysts’ earnings forecasts find algorithm’s less biased, more precise, explain of variance future ETRs. then use Explainable AI (based on Shapley values) to measure usefulness each disclosure item that while some tax-related useful, others offer minimal value. Using information as benchmark, we further values examine is underweighted or overweighted analysts. Overall, results help inform standard setters relevance certain disclosures achieving objective predicting JEL Classifications: G17.

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ژورنال

عنوان ژورنال: The Accounting Review

سال: 2023

ISSN: ['1558-7967', '0001-4826']

DOI: https://doi.org/10.2308/tar-2021-0398