The OECD/G20 (2019) Inclusive Framework on BEPS: Some Unresolved Issues
Kluwer International Tax Blog
August 30, 2019
Please refer to this post as:, ‘The OECD/G20 (2019) Inclusive Framework on BEPS: Some Unresolved Issues’, Kluwer International Tax Blog, August 30 2019, http://kluwertaxblog.com/2019/08/30/the-oecd-g20-2019-inclusive-framework-on-beps-some-unresolved-issues/
The OECD Work Programme published in May of this year under the OECD/G20 Inclusive Framework on BEPS aims to achieve a consensus solution to the problems of taxing the digital economy.
The OECD Work Programme is broad in scope and considers radical departures from long established rules for international taxation, for example current transfer pricing rules and rules relating to the existence of a permanent establishment. However in many ways the work programme is constrained by portraying the digital economy as a development of pre-digital business structures rather than as a radical departure.
The Work Programme for example, considers that existing rules in relation to transfer pricing may continue to play an important role in international allocation of sales revenues and profits. In one suggested solution, the “Modified Residual Profit Split Method”, it is proposed that profits would be split into two components “routine” and “non-routine”. “Routine” profits could be assessed using current transfer pricing rules and non-routine profits would be assessed using the new rules.
A key aspect of the proposed solution is to ensure that “all internationally operating businesses pay a minimum level of tax”. But what is not explained is what is this minimum rate, and how it should be measured.
The Effective Tax Rate
It is proposed that the minimum rate of tax be assessed by determining the current “effective tax rate”. This measure of “effective tax rate” would then be used to “tax back”, “where other jurisdictions have not exercised their primary taxing rights or the payment is otherwise subject to low levels of effective taxation”.
Measuring effective tax rates is difficult. It requires an estimate of the tax base, that is a tax base that has not been determined by tax planning considerations, but rather where value added is derived. Many studies of effective tax rates use company accounts as a data source. The most common measure of effective tax rates focuses on the tax charge rather than a preferable measure which is “cash tax payment”.
Losses pose a particular difficulty in measuring “effective tax rates” as estimated effective tax rates will be negative in the accounting period in which the loss is declared (T/-P, where T is Tax paid and P is pretax profits). Estimated effective tax rates could also be negative where firms receive tax refunds in a particular period (perhaps due to losses reported in a previous accounting period ( –T/P) . Estimated tax rates could also be positive where firms receive tax refunds in an accounting period and declare losses (-T/-P). A possible solution of omitting all firms which declare losses or receive tax refunds in an accounting period poses additional problems as firms have choices in relation to the recognition of losses.
The Work Programme refers to the need to consider the “suitability of using accounting rules” for measuring profits, but does not give any further clarification.
Market Structure and Profit
Monopoly and oligopoly are identified as a key feature of the digital economy in BEPS Action 1. There is one reference to this important feature in OECD (2018) and no reference in the Work Programme. This is despite repeated reports of regulator concerns about market dominance.
Fines for abuse of market structures may be higher than tax payments in a particular year. For example, Google shows a tax charge of $4.1 billion for 2017, and accrued expenses of European Commission fines of $5.1 for the same year. A similar position is likely to arise for Facebook and Apple in future years.
Market structure as a source of value added has considerable implications for effective tax rates and how they might change as a result of regulatory intervention.
Sources of Value Creation in the Digital Economy
The source, and hence location of value added and profit are fundamental issues in determining how much additional (if any) revenue will be raised and to which jurisdiction revenues be allocated.
OECD Action 1 noted a key issue “was how to attribute value created from the generation of data through digital products and services”. Action 1 also states that the nature of the digital economy “raises fundamental questions as to how enterprises in the digital economy add value and make their profits”.
However sources of value added, and how added value is created are not discussed in the Work Programme. However, OECD 2018 does have a considerable discussion of the creation of value in the digital eonomy. This latter report notes “that value increases as the number of users increase” implying that users create value. The Report also describes value creation as value chains, value networks or value shops. Value chains as an analysis of value creation are largely associated with Porter, a U.S. academic heavily influenced by U.S. business models as they existed pre 1980. As such, it is of little relevance in understanding the process of value creation by modern business enterprise. Value networks and value shops are again at variance with modern production processes associated with outsourcing and “factory less production”.
Sources of value creation by largely digitalised firms is often unclear. An exception is Zuboff. Value creation appears associated with:
- collecting and analysing vast amounts of data, from different sources;
- market dominance;
- operating in a largely regulatory free environment;
- use of intellectual property, business practices and organisational structure that are secretive.
Secrecy in relation to organisational structure is partly related to tax planning but is also connected with hiding business strategies. Apple for example reports nine subsidiaries in its annual Form 10 K report to the SEC for 2018. There have been recent filings in Ireland for one of these subsidiaries (Apple Operations International, lists 76 subsidiaries).
These factors are combined to yield effective organisational forms and superior predictive tools for advertisers to shape and control demand. Zuboff argues “total information tends towards certainty and the promise of guaranteed outcomes”.
Information management via data centres by firms such as Amazon, Facebook, Google and Microsoft are often clustered in certain countries, for example the U.S., Ireland and the Netherlands. Given the central role of data collection and analysis in the business strategy of digital firms, there is little analysis of how profit is allocated to data centres or “cloud data centres” and their role in value creation.
It is unlikely that an equitable and sustainable solution to the problem of taxing the digital economy will be found without an adequate explanation of how value is created. If data accumulation and analysis is the source of value creation and not users, the challenge is to determine how this might be taxed. Given this absence it is likely that individual countries will pursue own country solutions to taxing the digital economy, although it is also likely to be associated with increased intercountry co-ordination as in the case of some EU countries.