The Intersection Between Tax Credits and Trade or Business

Abstract

This note analyzes the appeal of the Tax Court’s 2022 decision in Olsen v. Commissioner before the Tenth Circuit. A central dispute in the case involved determining whether the Olsens’ activity constituted a trade or business — a crucial question with significant financial consequences for deductions, credits, exemptions, disqualifications, and penalties. The Tax Court held for the commissioner, deciding that the taxpayers were not engaged in a trade or business, and thus not entitled to specific deductions, credits, and exemptions.

Using Blue J’s machine-learning algorithm, we had earlier predicted with greater than 95 percent confidence that the Tenth Circuit would hold for the commissioner. Even when adopting the most favorable characterization of the facts presented by the taxpayer, Blue J’s algorithm still predicted with 86 percent confidence that the commissioner’s position would prevail, based solely on the position taken in the taxpayer’s submissions.

Our prediction proved accurate when the Tenth Circuit recently affirmed the Tax Court’s decision that the taxpayers were not engaged in a trade or business. This outcome demonstrates the effectiveness of machine-learning models in analyzing legal issues, particularly regarding trade or business status, an area in which the case law is extensive and the fact-intensive inquiry is complex. It also emphasizes the importance of understanding the trade or business question and highlights the potential of machine learning in evaluating the strength of legal arguments.

Keywords: tax credits, trade or business, income taxation, machine-learning

JEL Classification: H0