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Amount B: Facts and Circumstances Matter—Even for Routine Distributors

Feb. 5, 2021, 8:00 AM

The OECD Pillar One Blueprint (referred to herein as “Pillar One”) consists of several key elements grouped into three components: Amount A (a new taxing right for market jurisdictions), Amount B (a fixed return for certain baseline marketing and distribution activities), and Tax Certainty (dispute prevention and resolution mechanisms).

Of the three components, Amount B may be the “neglected child,” having received far less attention than other policy proposals in the Blueprints. For example, Amount B is one chapter of about 7,000 words, less than 6% of Pillar One’s word length; Amount A, on the other hand, occupies the bulk of the text with six chapters and three annexes. Of the 38 questions on Pillar One in the OECD Public Consultation Document, on Pillar One, only seven questions pertain to Amount B compared to 26 for Amount A. The OECD Economic Impact Assessment (EIA) of Pillars One and Two even omits Amount B from the impact calculations on the grounds that its modelling would be too difficult. The EIA also notes that the “revenue effect of Amount B is likely to be modest, as it does not provide market jurisdictions with a new taxing right but is merely designed to simplify the administration of the current transfer pricing system.”

While Amount B has received less attention than the other Blueprint proposals, Pillar One (page 160) argues that Amount B does matter for three reasons: it may enhance tax certainty, reduce tax compliance costs, and provide additional revenues for jurisdictions with low tax administrative capacity (e.g., some market jurisdictions in developing countries). We agree that Amount B does deserve more attention from tax practitioners and policymakers. The proposal is more than “merely designed to simplify the administration” of the existing transfer pricing rules. We take a closer look at the proposed design of Amount B, addressing the question: Do facts and circumstances matter, even for “baseline marketing and distribution activities”? We argue in the affirmative: Facts and circumstances do matter, even for routine activities. We ask questions and provide recommendations for enhancing the clarity and application of Amount B such that it may be consistent with the arm’s-length principle (ALP) and reduce tax and administrative burdens.


Pillar One (page 11) defines Amount B as a “fixed return for certain baseline distribution and marketing activities taking place physically in a market jurisdiction.” The goal is to standardize the remuneration of related-party distributors performing “baseline marketing and distribution activities” (BMDA). Amount B is intended to approximate the results that would have been generated by applying the ALP and the transactional net margin method (TNMM) in the 2017 OECD Transfer Pricing Guidelines. The calculations to implement Amount B would therefore involve benchmarking related-party distributors that perform BMDA against comparable unrelated entities performing similar BMDA. Amount B has three proposed key design features: scope, quantum, and implementation, which we summarize below, before moving to our own commentary. All page, paragraph, and chapter references are to the Pillar One Blueprint.


  • Entities and Transactions: Amount B applies only to related-party distributors that: (i) buy from related parties and sell to unrelated parties, and (ii) have a “routine distributor functionality profile” (page 15). A key element of the scope is that the entities are not limited to firms in automated digital services (ADS) and consumer-facing businesses (CFB), unlike Amount A. Both foreign subsidiaries and permanent establishments (branches) are included, including marketing and distribution hubs if they distribute products for the multinational enterprise (MNE) group.
  • Activities and Indicators: In-scope activities are defined first by a positive (angel) list of typical functions performed, assets employed, and risks assumed (FAR) at arm’s-length by routine (limited risk) distributors. The listed functions include (pages 164-165): importing or purchasing products for local resale; managing customer relationships; negotiating pricing and contract terms; processing of orders and contracts; management of logistics, warehousing, transport, and inventory; general administrative functions; and marketing activities. Entities are excluded from Amount A if their activities are either lower/fewer than or higher/more than the listed BMDA. First, a distributor performing fewer activities and assuming less risk that BMDA is deemed out of scope. Second, a negative list of typical FARs is used to remove distributors that perform more activities or higher levels. Specifically listed out-of-scope activities are: DEMPE (development, enhancement, maintenance, protection, and exploitation) activities for marketing intangibles; strategic sales and marketing functions in the local market; activities that involve assuming entrepreneurial risks and responsibilities with respect to the controlled transaction; and activities related to resale of products mainly to government entities/contractors.
  • Quantitative Indicators: In-scope BMDA are first defined by reference to a list of “typical” functions, assets, and risks by “routine” distributors (paragraph 664), which are outlined on pages 163-166. Pillar One proposes (page 167) that quantitative indicators could be used to help identify in-scope and out-of-scope activities for Amount B. Examples include: the ratio of marketing and advertising expenses to total costs and the ratio of R&D expenses to total costs (as indicators of DEMPE activities); these two indicators plus the ratio of amortization costs to total costs (as indicators of ownership of valuable marketing intangibles); and the ratio of finished inventory to turnover, the ratio of inventory write-downs to total inventory, and the ratio of accounts receivable to finished inventory (as indicators of entrepreneurial risk and responsibilities). When the indicators are above some pre-determined level, the activity would be defined as out of scope.
  • Other Entity Types: Chapter 8 also discusses two types of entities. The first, multifunctional entities that perform not only BMDA but also activities such as R&D, manufacturing or services, would either require segmentation or need to be excluded. The second, commissionaires and sales agents, are assumed to be out of scope because of their activities are below the BMDA.


  • Structure: The profit level indicators (PLIs) that are expected to be used to determine the fixed return for BMDA are those recommended for the TNMM, in particular, return on sales (ROS) or earnings before interest and tax (EBIT).
  • Differentiated Returns: Possible differentiation by region and industry is considered likely. Differentiation by functional intensity is not, on the grounds that it might increase complexity and areas for dispute.
  • Process: In order to determine the specific fixed return for BMDA, reference benchmarking sets for each geographic region would need preparation together with a set of industry definitions. A search strategy “cookbook” would also need to be adopted and followed. Then, the recommended PLI would determine the range of “potentially appropriate returns” (page 171).


  • Chapter 8 recommends that Amount B should be implemented in a coordinated and uniform fashion, probably using a narrow scope to facilitate consensus among the members of the Inclusive Framework.
  • A variety of legal and regulatory changes would also be needed including:

— Domestic laws would need to be changed so that Amount B would determine the arm’s-length return (ALR), rather than the existing transfer pricing rules (i.e., Amount B would replace the IRS Section 482 Regulations for activities deemed to be BMDA).

— A new treaty-based resolution process could be needed where two tax authorities disagree over the ALR and they either do not have a double tax treaty or they do but one jurisdiction has adopted Amount B and the other has not.

— Additional guidance might also be needed.

  • If Amount B were broadened over time by widening the definition of in-scope activities, amendment of the OECD Model Tax Treaty might also be required.


The stated objective of Amount B is to achieve an alignment with the ALP (paragraphs 650 and 654). We argue that this alignment must be quantified in terms of the variances that are deemed reasonable and justified if Amount B is to meet its goals of reduced taxpayer compliance costs and enhanced tax certainty (paragraph 651). In addition, the OECD’s technical work program needs to establish acceptable levels of “false positives” and “false negatives” vis-a‘-vis the ALP and their magnitude as a fundamental design criterion. As described below, we have substantial concerns as to whether a satisfactory alternative to the current “facts and circumstances” approach under the ALP can exist in practice if the Amount B proposal were to be adopted by members of the Inclusive Framework.

Entities and Transactions


With respect to industry scope, the OECD has gone beyond its careful scoping exercise conducted for Amount A and appears to treat all industries as within the scope of Amount B, not only automated digital services and consumer-facing businesses. In our experience, this may prove to be a Herculean task, mainly because while CFB marketing and distribution models and operations are relatively well understood and their activities fall neatly into the positive or the negative list, this may not be true for marketing and distribution models in ADS.

Long-standing transfer pricing guidelines were designed based on a CFB two-party trading model with tangible goods and services. An ADS entity does not perform marketing and distribution activities in the same way as a CFB entity does. ADS entities are primarily engaged in technical market research, negotiating and generating advertising revenues, and acting as in-country liaison offices for regulatory/governance bodies. ADS entities do not manage “supply chains” in the same way as CFB entities do. Their functions, risks and assets need to be defined differently than what is listed in paragraphs 668 and 669.

In addition, non-CFBs such as capital goods and intermediate goods (business-to-business) industries, extractive industries, and certain financial services sectors have little or no “distribution” activity and perhaps very little investment in the traditional sales generation activities like those in the positive list. As such, the inclusion of these industries into Amount B presents several problems in classifying their activities into the positive and negative lists. We believe that tax certainty and reduced disputes will be well served by distinguishing the existing positive and negative lists into one for ADS and one for CFB, with a possibility of separate lists for extractive industries or financial services in the future.

Hybrids and Going Digitals

Moreover, as the CFB MNEs accelerate their digitalization of supply chains and value chains and all MNEs adopt the tools of Industry 4.0, they will evolve from “brick and mortar” companies to hybrid and pure digital companies. These hybrid companies or “going digitals” may have large annual changes in their digital and non-digital product mix or product delivery modality, making it difficult to delineate and place these dynamic functions into static positive and negative lists.

How should one treat the very common situation where some of an MNE’s activities fall into the positive list while others fall into the negative list? Future iterations of Amount B should provide clearer guidance. Two possible ways to reduce controversy are suggested below.

  • Apply a majority rule when more than, say, 75% of the MNE activities fall into either the positive list or the negative list would define the applicability of Amount B.
  • When the MNE’s activities are equally distributed across the positive and negative lists, apply the rebuttable presumption “rule” and include them in Amount B but giving the MNE the burden of proof to show otherwise.

Activities and Indicators

We agree with the identified positive and negative lists of activities as an initial classification of potential candidates for the standardization approach, subject to verification in terms of empirical proof and further refinement. We disagree, however, with the expectation that this approach to standardization would yield a practically manageable subdivision by industry, region, and FAR. Our experience over many decades of benchmarking marketing and distribution functions in multiple industries and geographies indicates that the drivers of arm’s-length profitability are multidimensional and idiosyncratic in nature. For example, an MNE may have marketing synergies that span many different business units or product lines and sales “rainmakers” who are dispersed across multiple geographies but working to achieve a single program objective. The marketing cost base may be split between operating expense and cost of goods sold or some items classified above or below the EBIT line.

The existing OECD BEPS framework provides substantial guidance in determining adjustments and other outside evidence needed to account for these potentially material differences that would otherwise undermine the reliability of the results or create illusory certainty and opportunities for abuse. Moreover, existing OECD guidance concerning selection of the most appropriate transfer pricing method provides a needed dynamic principle to drive comprehensive solutions considering all relevant factors. This essential principle appears to be missing from the current Pillar One proposal.

Quantitative Indicators

Amount B lists a variety of quantitative indicators that could help identify in-scope and out-of-scope activities. To illustrate the quantitative significance of these different profitability drivers, we identify features of distributors on the positive list that would give rise to material adjustments for Amount B. For example, consider a typical positive list distributor with a baseline arm’s-length EBIT of 3%. The following differences in underlying facts drive material variances in the arm’s-length EBIT.

  • Differences in net payment terms (i.e., receivables less payables) can amount to 180 days or more, or approximately half a year’s sales, implying differences in operating profit of 2.5% of sales or more, financed at 5% per annum.
  • Differences in inventories amounting to 90 to 180 days or more, can be driven by differences in specific market requirements as well as variations in sales volumes, supply chain factors, and the business cycle, financed at 5% or more per annum, implying differences in operating profit of 1% to 2%, or more.
  • Differences in fixed assets including logistics facilities and equipment, marketing and sales offices, and after-market service capabilities can amount to 25% to 50% of sales, implying variances of 2.5% of sales or more financed at the cost of capital.
  • Differences in warranty and other liabilities of similar magnitude that drive similar percentage differences in operating margins.
  • Differences in routine marketing and sales functions resulting in SG&A expense ratios to sales ranging from 10% to 20% and implied differences in EBIT of 1% to 3% or more.
  • Differences in cost of capital between industries, geographies, and firms of different size that can amount to 5% to 10% or more per annum and drive differences in operating margins of 1% to 3% or more depending upon capital intensity.
  • Differences in market and economic conditions such as competitive landscape, perceived country risk, etc., that vary substantially over time and across industry sectors can create substantial differences in arm’s-length outcomes in any given year or context, amounting to several percentage points in EBIT outcomes.

Other Entity Types

In general, the broader the scope of activities that constitute acceptable BMDA the higher the likelihood of the OECD accomplishing its stated goals for Pillar One, i.e., establishing clarity and certainty of an ALR for such activities and lowering the compliance burden for MNEs and tax authorities. We believe that broadening the scope to include commissionaires and sales agents is constructive for both MNEs and tax authorities. Our reasoning is outlined below.

Commissionaires and Sales Agents

In our experience, BMDA as defined by activities in the positive list typically include those performed by commissionaires and sales and marketing agents. Not including commissionaires and sales agents would leave significant opportunities for manipulation (e.g., MNEs could easily set up a commissionaire structure to avoid being included in the scope of Amount B and the associated remuneration). When conducting transfer pricing audits, tax authorities may conclude that commissionaires, sales agents, and other business models that create permanent establishment concerns are operating as “low- or limited-risk entities.” Including them in the scope of Amount B and providing for a fixed ALR provides greater certainty for both tax authorities and MNEs. We understand that inclusion of businesses that provide sales and marketing functions without taking title to goods into the scope of the Amount B will take some additional work when determining the fixed renumeration. However, given the potential avoidance strategy discussed above, this additional work seems to be necessary and worthwhile, especially as marketing and distribution activities are the subject of significant scrutiny, and transfer pricing disputes often center on commissionaires and low-risk entities.

Multifunctional Entities

In general, entities that perform BMDA should be eligible to apply Amount B as long as the financial results for the different activities can be segmented in an economically sound and reliable manner. This type of segmented financial information for related entities is unlikely to be available in their audited financial statements. In addition, segmented financial data that is available from management reports, such as division or business segment reports or contribution margin analysis for product lines, may not be sufficiently detailed for this purpose and may need further refinement. For example, division or business segment results may allocate direct expenses only, leaving indirect or other corporate-level operating expenses at the headquarter entity level. Segmentation analysis would need to carefully examine the listed BMDA and identify all relevant revenue and expense items. Balance sheet items would also need to be identified if any of the other activities were valued using a balance sheet based PLI and if comparability adjustments such as working capital are implemented.

Segmenting the BMDA listed in Pillar One (paragraph 668) from the high value-added marketing and distribution activities that create marketing intangibles, as defined in paragraph 669, is potentially more challenging than segmenting BMDA from say, R&D, manufacturing, or back-office services. For example, activities related to development and maintenance of local customer relationships, which is listed as a BMDA, from activities related to strategic sales and marketing functions in the local market can be difficult to identify and quantify separately. Similarly, the dividing line between negotiating pricing within the MNE’s pricing guidelines, which is included as a BMDA, versus negotiation of pricing outside the guidelines, which is listed as an out-of-scope activity, can be impossible to distinguish. Pricing, whether it is in within the MNE’s guidelines or outside of it, is typically handled by the same group or team and allocating the group’s total expense across these marginally different activities would be extremely onerous if any measure of accuracy were required. As is true with all aspects of transfer pricing, segmentation of financial data is fact driven, and there is no universal standard as to how to segment financial information, and thus, it will need to be evaluated on a case-by-case basis.


Quantitative indicators or thresholds are needed if the objective is for Amount B to deliver a result that is consistent with the ALP. In this section we discuss the Pillar One proposals for selection of a PLI, differentiating returns by industry and region with adjustments for comparability.


Pillar One proposes to use EBIT to measure Amount B (paragraph 653). Given the choice between EBIT and Profit Before Tax (PBT), we support the former because EBIT, under normal circumstances, measures profits or losses related to the MNE’s operating activities. PBT contains additional items that are mainly concerned with financing activities and only relate indirectly to operating activities, if at all. Examples of these items are interest revenue and expenses, gains and losses on sale of investments, foreign exchange gains and losses.

However, in applying the EBIT, our experience has shown that there are significant differences in how different accounting standards used around the world classify as either above or below the EBIT line, items such as one-time extraordinary expenses, write-downs of impaired assets, acquisition costs, depreciation and amortization expenses, etc. If EBIT is derived from book operating income without adjusting for the effect of one-time extraordinary expenses or income, it would distort the results of an entity related to its operating activities. Thus, we would recommend excluding the impact of extraordinary expenses or income from consideration for the purpose of computing the profit under the Amount B.

In addition, revenue generated from sales to unrelated customers does not necessarily capture all possible levels of activities of a distributor in different industries. In our experience, activities of sales and distribution subsidiaries of multinational groups that are considered “normal” or “baseline” vary greatly among industries. Goods with high value per unit (e.g., minerals, machinery) may require relatively low sales and marketing effort per dollar of sales, while products with low per-unit value may take proportionately higher sales and marketing effort (e.g., luxury clothing, cosmetics). Consequently, if a uniform EBIT indicator is applied to both sellers of “high-value/low-effort” goods and “low-value/high-effort” goods, it would, in relative terms, overcompensate the FARs of the former group and undercompensate FARs of the latter.

Differentiated Returns

Pillar One recognizes that measuring Amount B should be adjusted for differences among regions and industries but proposes that differences in functional intensities should be ignored on the grounds that this would introduce significant complexities and disputes.

Differentiation by Region

Capturing regional differences by determining Amount B based on benchmark BMDA for each major region may not be sufficient to account for the impact of country-specific factors and firm profitability. Country-specific political and economic risks warrant a commensurate return that may be quite different from regional averages. For example, countries facing higher risks due to political, economic, social, and other developments can only attract investors when their returns compensate for the higher risk profile. The returns on operating expenses and, to some extent returns on assets are relatively straightforward to benchmark using market evidence. We are well aware of the challenges associated with identifying independent comparables for certain industries and in certain areas of the world. Nonetheless, we believe that workable approaches are available to deal with these challenges. For example, these approaches may take a form of adjustments to the results of the independent comparables sourced from a different geographical market to the economic conditions of the given geographical market.

Similarly, Amount B needs to take account of changes in the business cycle and the economic impacts of supply and demand shocks that may affect the comparable benchmarks and related entities differently. For instance, economic crises such as those brought on by the current Covid-19 pandemic have significant impacts on many industries and sectors, including companies that perform BMDA. If Amount B were in effect in 2020, it would not deliver a result in accordance with the ALP for these entities. Pre-determined fixed returns would not capture the impact of Covid-19 on BMDA and would severely penalize integrated companies with related-party distributors relative to companies dealing with unrelated distributors.

Differentiation by Industry

As a practical matter, Amount B can be expressed as a matrix of EBIT percentages by industries and geographies. We suggest this matrix be prepared with EBIT as the primary PLI, but several supplemental tables with different PLIs (e.g., return on capital employed or cost-plus profit percentages) could be made available to transfer pricing professionals who would then apply primary and corroborative PLIs to document the broad range of ADS and CFB marketing and sales entities.

Differentiation by Functional Intensity

Pillar One proposes that Amount B should ignore differences in functional intensities. We disagree. Differences in the intensity of operating expenses (i.e., the ratio of operating expenses to revenue) among the sales and distribution entities must be considered. Differences in the intensity of operating expenses between controlled and uncontrolled transactions can result in distortions in the arm’s-length profit. Therefore, SG&A intensity relative to sales could be a good indicator of type and intensity of marketing and distribution functions. Routine distributors with higher (lower) SG&A-to-sales ratios are found to generally earn higher (lower) EBIT, reflecting the fact that profit margins are correlated with functions performed.

Similarly, differences in capital intensity between controlled and uncontrolled transactions can also result in material distortions in the arm’s-length profit. Asset intensity of distributors (e.g., ratios of accounts receivable, inventories, and fixed assets per revenue) also varies greatly among industries and must be taken into account for comparability purposes. These types of quantitative indicators should be computed on a rolling three-or five-year average basis to limit the impact of single-year changes in sales force or IT investments. In our view, Amount B has to accommodate variability of returns across industries and geographical markets, and, possibly, incorporate adjustments for an unforeseeable economic crisis, such as a global financial downturn, pandemic, or other event outside of an MNE’s control. Thus, our recommendation would be to quantify Amount B in the manner that accounts for differences in both the intensity of operating expenses and the intensity of assets across industries and/or geographical regions.

Commissionaires and sales agents would, presumably, have a lower intensity of assets per volume of sales than buy-sell distributors, and most of their remuneration is represented by the return on operating expenses. The benefit of the focus on the intensity of operating expenses and the intensity of assets is that the same factors would be considered as drivers of remuneration for both full-fledged distributors and commissionaires / sales agents, which provides a basis to include commissionaires and similar entities into the scope of the Amount B.


Pillar One proposes that reference benchmarking sets for each geographic region be prepared along with a consistent set of definitions for the industries in each benchmarking set. The benchmarking sets would include potentially comparable independent firms for each industry and region, necessitating a specific search strategy for their identification. PLIs would then need to be calculated to establish a range of “potentially appropriate fixed returns” (paragraph 694).

Our concern is that available benchmark companies performing BMDA, which might be candidates for determining the Amount B profitability ratios, even if they vary by industry or region, are not expected to be, in an absolute sense, very closely comparable. For example, many industries have no independent distribution companies that are comparable to the distribution subsidiaries of the major competitors; thus, there are no independent sales and marketing companies that distribute automobiles at the same level of market as automotive OEMs in North America. Comparable distribution companies that are typically used to benchmark automotive distribution include wholesale distributors of products that are quite different from automobiles, such as IT products, hardware, and building materials. These comparable companies tend to be more asset intensive with longer receivable and inventory days due partly to the different level of market in which they operate (i.e., first-tier distributors selling to a second tier of independent dealers). Measuring BMDA returns using EBIT for these potentially comparable companies without considering the major differences in working capital intensity will lead to significant distortions in the determination of Amount B for BMDA and will not deliver results that approximate the ALP.


In principle, the adoption of Amount B should lead to a reduction in disputes relating to the characterization of the entity, the appropriate methods to use, and the arm’s-length operating margin. We believe that the intent of Amount B does that and would be welcomed by MNEs and tax authorities alike. We also believe that there can be unwanted spill-overs and external side effects of applying a fixed PLI, which must be thought through and addressed rather than by defaulting to mandatory binding arbitration processes. The spill-over effects that we anticipate include the following:

  • Applicability of both the current positive and negative lists to ADS business models.
  • Debate over what constitutes “at least sufficient activities” (paragraph 667) for an entity to be considered a routine distributor, especially for ADS marketing entities.
  • Differences between the EBIT targets established in an advance pricing agreement (APA) and those under Amount B. While the OECD has clearly stated that the APA terms will be respected and the renumeration will be grandfathered through the current term of the APA, the OECD must issue further guidance on how a renewal should be handled when there is no change in the MNE marketing and distribution operating model and Amount B is significantly different from the terms of the expiring APA.
  • How would Amount B fixed returns be adjusted, amended or ignored by tax authorities that have already established guidelines or rules of thumb? For example, the Australian Tax Authority has published routine distribution EBIT guidelines by industry, and several other countries have “generally accepted” cost plus or EBIT amounts applied in transfer pricing audits, MAPs, etc.
  • In countries that currently have a gross or net level digital tax or are on the verge of legislating one, will Amount B still be relevant?
  • Are the Amount B EBIT rates relevant for tax valuation work, e.g., in computing routine returns for a valuation of intangible property?
  • If the negative list in Amount B leads to a recharacterization of an entity from low- or limited-risk to high value-added/strategic, is the MNE liable for some form of business reorganization tax such as an exit tax?
  • How will Amount B interact with Covid-19 guidelines to provide clear guidelines for transfer pricing during a temporary business recovery period (for 2020 and potentially for 2021)?
  • Will Amount B be subject to revision to account for future crises affecting local, regional, or global economies?
  • While Amount B could reduce disputes and lower compliance costs for MNEs and tax administrations, the indicative (not exhaustive) questions above must be addressed before any finalization of the proposal. Otherwise, the fixed return to BMDA proposed by Amount B will likely conflict with the results obtained by independent entities trading at arm’s length in the open market.


We recognize that a significant amount of work has gone into the preparation of the OECD Blueprints. The OECD/IF is addressing highly complex issues and it is likely that in this context, additional conceptual developments will be needed.

Overall, we believe that it will not be possible to maintain consistency between Pillar One and the arm’s-length principle. The OECD/IF will have to make a choice as to whether or not to maintain the ALP, given that the approach currently proposed is openly inconsistent with the ALP and with established intercompany pricing processes that achieve results substantially equivalent to those achieved by independent companies trading at arm’s length.

We are also of the opinion that the approach proposed by the OECD/IF does not fully reflect the way multinational enterprises deploy their assets and employees to conduct business in “market” jurisdictions. In other words, the creation of value by MNEs is linked to the people they employ and the assets they own and develop. The fact that an MNE has sales in a country does not in itself mean it should be subject to corporate income tax in that country. In particular, an MNE that does not have any FAR in a country therefore does not conduct any activities that create value in that country and should not be taxed via a corporate income tax by that country.

In our opinion, the arm’s-length principle is a better way to handle the issues that Pillar One is attempting to address. We believe that it is important to give the ALP a chance, particularly now as the BEPS Action Plan is being implemented. The 2017 OECD Transfer Pricing Guidelines are also just beginning to be relied upon in tax audits and it is not yet possible to assess their impacts.

This column does not necessarily reflect the opinion of The Bureau of National Affairs, Inc. or its owners.

Author Information

Harlow Higinbotham is a Managing Director and former Chair of NERA’s Transfer Pricing practice in Chicago, IL where he focuses on both litigation and advisory work for pharmaceutical, electronics, and automotive industry clients among others ( Dr. Niraja Srinivasan is a transfer pricing Director at NERA Economic Consulting’s Washington DC office ( Dr. Vladimir Starkov is a Director at NERA Economic Consulting based in Chicago, IL ( Nihan Mert-Beydilli is an Associate Director at NERA Economic Consulting based in Los Angeles, CA ( Lorraine Eden is Professor Emerita of Management and Research Professor of Law at Texas A&M University, College Station, TX ( The authors appreciate helpful comments from Ralph Meghames and Emmanuel Llinares. An earlier version of this paper was submitted by NERA on 14 December 2020 as a Commentary to the OECD’s Public Consultation Document on the Reports on the Pillar One and Pillar Two Blueprints. This article represents the independent views of the authors and not necessarily those of NERA, Texas A&M University, or any other person or institution. Please address comments to Lorraine Eden at