A complete statistical procedure for transfer pricing practitioners. Transfer pricing practice usually determines the arm’s length range using the interquartile range of the chosen profit indicator, defined as a ratio m(i) = Y(i)/X(i) across comparable companies.
Return on Assets and the Harmonic Mean
On May 23, 2017, the OECD released a draft of Action 8 of the Base Erosion and Profit Shifting (BEPS) plan, providing taxpayers and tax administrations with a new transfer pricing approach to measure hard-to-value-intangibles (HTVI):
From Equation Counting to Class Conflict: A Mathematical Reading of Political Economy
Analysts often work with ratios. Whether examining price-to-earnings ratios in finance or profit indicators in transfer pricing, the ratio m(i) = Y(i) / X(i) is often reported. However, this simple ratio masks a systematic bias that affects quartile estimates and other location parameters.
Controlling producer price inflation (PPI) doesn’t require austerity.
Using a less reliable (higher variance) adjusted profit indicator violates the scientific principle of minimizing measurement error. Avoiding error propagation is essential for producing credible and reproducible estimates.
The profit rate identity can be estimated as a dynamic framework using an autoregressive distributed lag (ARDL) model.
Some basic rules of differential calculus are useful for understanding economic discourse, such as discussions in business or financial media about U.S. economic performance.
This blog presents a basic analytical framework for understanding the relationship between GDP growth and public debt commitments. The Harrod-Domar principle, which posits that increased gross private domestic fixed non-residential investment drives GDP growth, does not apply to the recent GDP growth of many countries.
Microeconomics are detached from the reality of corporate profits behavior. Here, I explore the operating profits (before depreciation and amortization) of a major group of U.S. corporations (consolidated entities) that make up a large fraction of U.S. gross domestic product.
The operating profit margin (OMBD or OMAD) can be derived from the profit markup by indirect least squares (ILS). This is the most theoretically defensible and reliable operating profit indicator that can be obtained from comparable data.
U.S. 26 CFR 1.482-5(b)(4)(i-ii) claim that the “return on capital employed” (return on assets) is less sensitive to “functional differences” than the operating profit margin or the operating profit markup. This claim is based on the unrealistic premise that “capital flows” to equalize profit rates (return on assets) among companies in the same (or in different) industries by some "invisible hand."
Data suggest that “big oil” forms an oligopoly industry. Noise about oil and gas prices being determined by supply and demand is suspect.
Quartiles are the most elementary form of univariate (single variable) data summary, because no statistical technique beyond sorting and slicing (tagging) of the data is employed. Distributions of profit indicators have long tails, suggesting that the Median is a good measure for only 50% of the dataset.
Determining an arm’s length profit indicator (profit ratio) requires two equations, and not one equation, as prescribed in financial statement analysis textbooks. E.g., Bernstein (1993), Drake & Fabozzi (2012). An accounting critique of univariate profit ratios is found in Whittington (1986).
EdgarStat® contains an internal regression model to calculate the beta-risk coefficient of an individual enterprise stock price return compared to the return of the S&P 500 stock price (market) index. This stock price return regression model is known as CAPM.
Regression analysis yields more reliable profit indicators than the linear equation without intercept specified in US and OECD transfer pricing guidelines.
Dr. Ednaldo Silva illustrates why asset intensity adjustments to the Return on Assets profit indicator are redundant and unviable.
Notwithstanding its acceptance in Coca Cola Co. v. Commissioner of the IRS, Return on Assets is a controversial profit indicator to use in transfer pricing. At the very least it must be subject to economic analysis to corroborate a relationship between operating profit and operating assets.
Ad hoc adjustments are a risky endeavor in transfer pricing. Using regression analysis, we can test if asset intensity is relevant to explain the behavior of the operating profit markup or profit margin and calculate a reliable adjustment to the profit indicator.
The prevalent use of quartiles to determine profit indicators often results in a wide (unreliable range) and ad hoc assets adjustments. These problems can be solved by using regression analysis, which produces more defensible statistical ranges of the profit indicator resistant to audit scrutiny.