RoyaltyStat Blog

Multi-Year Analysis of Profit Indicators

Posted by Ednaldo Silva

The OECD Transfer Pricing Guidelines (2017, ¶ 6.192) makes a perfunctory reference to multi-year data analysis covering intangibles. The guidance about using multi-year analysis of profit indicators is described on ¶ 3.75 to ¶ 3.79 (“examining multiple year data is often useful in a comparability analysis, but it is not a systematic requirement.”). One expects more competence in economics and statistical principles from the OECD Guidelines, instead of the misleading quote. Unsystematic requirement is nonsense.

The Limited Risk Transfer Pricing Canard During a Pandemic

Posted by Harold McClure

Transfer pricing practitioners fell in love with the concept of a “limited risk distribution” (LRD) on the hope that they could convince tax authorities in high tax jurisdictions to accept the premise that the local distribution affiliate should be happy with a low operating margin. This pandemic, however, has generated a lot of new transfer pricing advice that appears to contradict the original LRD argument.

Creating Defensible Transfer Pricing Reports

Posted by Ednaldo Silva

“We shall renounce . . . the subterfuges.”

Arm’s Length Profit Margin in Transfer Pricing

Posted by Ednaldo Silva

We estimated the equilibrium OMAD [operating (profit) margin after depreciation] of certain U.S. retailers using an autoregressive (AR(1)) model built-in RoyaltyStat®. We use the Gauss run-time engine, so the regression estimates are reliable.

Arm's Length Range - Most Reliable Measure

Posted by Ednaldo Silva

In statistics, we consider a random variable in terms of a reliable estimate of its central value (center) and spread from the center. The center is measured by the mean, and the spread by the standard deviation from the mean. In practice, data samples (such as the usual judgement selection of comparables in transfer pricing practice) contain outliers that distort the estimates of mean and standard deviation. As a result, statistical (confidence or tolerance) intervals based on the mean and standard deviation may not be reliable. See Gerald Hahn & William Meeker, Statistical Intervals (John Wiley, 1991) for a detailed coverage of tolerance and confidence intervals.