RoyaltyStat Blog

Adjusted COGS is a Proxy for Purchases

Posted by Ednaldo Silva

Adjusting cost of goods sold (COGS) to remove the effect of one-year changes in inventory is important before determining the arm’s length gross profits resulting from crossborder related-party purchases of goods and services. Adjusted COGS produce also a more reliable measure of the operating profits of the tested party (audited taxpayer) and the selected comparable companies.

Hard-to-Value Intangibles sans mystere

Posted by Ednaldo Silva

Unlike the debutant affection of the OECD, we discourage using projected profits or cash flows to measure hard-to-value-intangibles (HTVI) for transfer pricing purposes because this method is speculative and based on several impeachable assumptions.

Arm’s Length Profit Margin

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.

Equilibrium Arm’s Length Profit Ratios

Posted by Ednaldo Silva

An autoregressive (AR) model can produce more reliable measures of comparable company profit ratios (operating margin or profit rate) than the naive profit model prescribed by the OECD transfer pricing guidelines. We prefer to work with profit margins because they are pure numbers, unlike profit rates over assets of different vintages. Here, we show a fixed-point equilibrium and variance of an AR(1) model allowing the computation of a comparable profit ratio interval to benchmark related party transfers of goods and services. This AR(1) model can be used also to benchmark routine functions (manufacturing, distribution, retail) under the residual profit split method.

Company Profits in Transfer Pricing

Posted by Ednaldo Silva

It's useful to model company profits using a first-order autoregressive AR(1) process. However, “duality” (invertibility) between an AR(1) model and a weighted sum of random errors tempers theoretical or long-term ambitions. Duality is a metamorphosis from one dynamic process to another such that an AR(1) model can be converted into a moving average of random errors model. Moving average models lack X-factors explanation.

Residual Profit Split is an Avoidable Cul-de-Sac

Posted by Ednaldo Silva

The claim that it is impossible to find comparable royalty rates and that from the start we should use the residual profit split method for high-value intangibles needs revisiting. This claim is made prima facie without regard for the license agreements available in curated databases such as RoyaltyStat, which as of today contains over 17,875 unique and unredacted license agreements. Also, adopting the residual profit split method, when separate tested party methods such as the TNMM could suffice, creates unwarranted costs and audit management challenges for both the taxpayer and the tax administration.

Forecasting Profit Margin Under CWI

Posted by Ednaldo Silva

We can consider a first-order autoregressive (AR(1)) model to determine an arm’s length profit margin of a “tested party” subject to transfer pricing audit compliance:

Properties of the AR(1) Model of the Profit Margin

Posted by Ednaldo Silva

It’s useful to study the mean and variance of the first-order autoregressive model (AR(1)), which is postulated as univariate:

Determining Arm's Length Profit Margins Using the AR(1) Model

Posted by Ednaldo Silva

We can determine an arm's length profit margin (expressed as operating profit divided by net sales) of a controlled taxpayer (“tested party”) by using a first-order autoregressive model, which we can show (like any stable first-order difference equation) to be equivalent to a range of comparable “routine” profit margins plus a weighted random error time series.

Operating Profit Margins Don't Obey the Normal Distribution

Posted by Ednaldo Silva

The operating profit margin (measured after depreciation and amortization (OMAD)) of 23,151 companies listed in many countries, reflecting fiscal year-end 2015 accounting results, departs from the usually presumed normal distribution. In this sample, OMAD gets a better fit using the Gamma distribution.