Blue J Predicts: The Debt-Equity Distinction And Tribune Media

• Published date: 23 May 2022
• Subject Matter: Finance and Banking, Tax, Debt Capital Markets, Financial Services, Tax Authorities
• Law Firm: Blue J Legal
• Author: Blue J Legal

Common law debt-equity characterization depends on the synthesis of more than a dozen factual and circumstantial elements. In real-world situations, with so many considerations in play, ambiguity is endemic. The threshold challenge for taxpayers, the IRS, and, ultimately, the courts is to determine the most appropriate characterization for a given financing, all things considered. This is particularly difficult to do in cases that are close calls, in which there are balanced sets of factors alternately favoring debt and equity. Those cases often lead to judicial squinting to identify distinctions. This can magnify slight differences that, in the ordinary course, would unlikely be influential, let alone dispositive.

Indeed, when there is a balanced set of factors in play, it can be difficult to reach reliable conclusions and produce compelling reasons. Historically, judges have occasionally confessed their uneasiness in these kinds of close situations. As Sir Wilfred Greene, Master of the Rolls, remarked in 1937, "There have been many cases which fall upon the borderline: indeed, in many cases it is almost true to say that the spin of a coin would decide the matter almost as satisfactorily as an attempt to find reasons."¹

In cases in which a difficult judgment must be made with reasonably balanced factors, it can be worthwhile to garner the "wisdom of crowds"² to base one's analysis on the entirety of the case law. Fastidiously collecting training data, and identifying the facts and circumstances of past cases along with the resulting debt or equity characterization, provides a data-rich foundation to train a machine-learning model to reliably and accurately assess the likelihood that a decision-maker would reach a characterization of debt or equity.

Blue J has done just that by assembling a detailed data set of debt-equity decisions from 1956 on. The Blue J debt-equity model yields 95.6 percent agreement with the decisions of the courts. It has been thoroughly back-tested against historical case law and, for the past few years, has been making accurate predictions of new debt-equity cases as they are decided. It is being used as a teaching tool to inform debt-equity analyses in leading university tax law courses and programs. Practitioners increasingly leverage Blue J's debt-equity predictor to produce evaluations of the strength of novel situations involving new variations of facts and circumstances, many of which have never been directly judicially...