Sunday, September 16, 2018
Susan C. Morse (Texas), Seeking Comparable Transactions in Patent and Tax, 37 Rev. Litig. Brief 1 (2018):
Most business firms do not go around licensing their crown jewel intellectual property to unrelated third parties. This presents a problem for both patent law and tax law. In patent litigation, setting damages for a reasonable royalty under Georgia Pacific invites the use of a benchmark royalty rate that would have been agreed to had the litigating parties negotiated a market rate in advance. This counterfactual analysis repeats in tax law when firms allocate taxable income among affiliates located in different tax jurisdictions. Transfer pricing rules similarly seek a price, such as a royalty, that would have been agreed to had the related affiliates negotiated a market rate as adverse, or “arm’s length,” parties.
In their Article, Tax Solutions to Patent Damages, Jennifer Blouin and Melissa Wasserman argue that tax transfer prices can provide some of the data needed to set patent litigation damages. One could also ask the converse, which is whether patent litigation outcomes can provide some data that tax transfer pricing needs. If patent law looks to tax transfer prices, it sees the advantage that the tax transfer prices are set ex ante when IP developed by one affiliate was first used by another affiliate. This roughly aligns with patent law’s touchstone of a “hypothetical negotiation” that produces an “ex ante” license. If tax law looks to patent law, it sees the advantage that patent damages emerge from an adversarial process. Patent damages may be set ex post, but their validity is bolstered by the fact that they are contested.
Blouin and Wasserman argue that parties and courts should make use of the large body of tax transfer price information to help support reasonable royalty calculations in patent damages cases. Perhaps so. But transfer pricing data is messy. Using tax transfer prices sets for parties and courts the challenging task of understanding the prices in context. The risk exists that the analysis will fail because of the weight of its own complexity.