Comparables

Identifying comparables when using the transactional net margin method (TNMM)

The nature of the data that we are all often forced to use is such that, a comparable profits analysis focusing on results as opposed to prices is all that is possible. The Transactional Net Margin Method ("TNMM") is widely used in New Zealand.

The TNMM examines the net profit margin relative to an appropriate base (eg costs, sales, assets) that an entity realises from a controlled transaction (or transactions if aggregated). TNMM is based on transactional data in the same way as, for example the Resale Price Method, but the comparison of profit margins is made at the operating profit level instead of the gross profit level. In New Zealand, the operating profit level is usually defined as earnings before interest, tax and exceptional items (so-called "EBITE").

The most widely available and reliable data comprises operating profit figures – in particular, small differences in product or level of the market are likely to have a greater effect on prices and gross margins than they are on operating margins. The 2010 OECD Transfer Pricing Guidelines at paragraph 2.62 recognises this.

"One strength of the transactional net margin method is that the net profit indicators (e.g. return on assets, operating income to sales, and possibly other measures of net profit) are less affected by transactional differences than is the case with price, as used in the CUP method. Net profit indicators also may be more tolerant to some functional differences between controlled and uncontrolled transactions than gross profit margins. Differences in the functions performed between enterprises are often reflected in variations in operating expenses. Consequently, this may lead to a wide range of gross profit margins but still broadly similar levels of net operating profit indicators."

In constructing a rage of arm's length outcomes, data covering several years should be used to cover off the vagaries of business and product life cycles. Typically this means three to five years of data should be compiled. Combined with the careful selection of comparables, it should be possible to establish a range of returns which are reasonably close to what an equivalent industry participant would expect over the long run.

Functional analysis

It is crucial that an analysis of functions, risks and assets (especially intangibles) is taken out before any search for comparables is started. In our experience, the most common process failure is a rush to an analysis of potential comparables in reliance on a familiar business description (such as "wholesale distributor" or "contract manufacturer").

Once the business is well understood, the selection process then involves the following:

• identification of companies with similar products/services
• identification of companies with similar functions performed in the supply chain
• exclusion of companies which are too small (distorted due to shareholder transactions), too large, or in financial distress, and
• exclusion of companies which have associated party dealings, unless those dealings are not material.

OECD guidance

In chapter I-III of the 2010 OECD Transfer Pricing Guidelines, detailed guidance is provided on comparability issues and transactional profit methods. We consider the material to be recommended reading for practitioners.

A key message contained in Chapter III is that comparability is about seeking to arrive at arm’s-length pricing. It discourages:

• the use of extensive database selections to provide quantity over quality
• the formulaic use of, for instance, capital intensity adjustments
• the use of comparability adjustments when the underlying data is simply not comparable.

It also suggests that the use of comparability adjustments is only justified to the extent that comparability is improved. It also contains some helpful information on the use of multiple year data.

The lack of hard data on transfer prices is a major obstacle to objective empirical work. Comparables are almost always very approximate. In New Zealand, we are forced to use small samples (where the addition or deletion of one data point can sometimes lead to significant swings in the end result) increased by broad industry data such as sector averages and consolidated global returns.

The "same or similar market" principle is important in New Zealand. Australia is generally recognised as our closest reference country in terms of demographics, size of economy and stage of economic development. The New Zealand economy is closely connected to the Australian economy, basically forming a single market. This means the economic results reflected in Australian data are equally likely to be felt by a New Zealand company with international trade.

To find practical solutions, we often have to look beyond Australia to markets in Europe (in particular the United Kingdom) and North America where reliable data may exist. Provided the industry and functions in question are similar, less emphasis is placed on the country from which a comparable is taken, but recognition must still be given to greater economies of scale and competition as well as New Zealand’s higher cost of capital and higher distribution costs resulting from low population density.

Country risk premium

In normal circumstances, operating in New Zealand is riskier than larger and more diversified markets such as Australia, the United Kingdom and the United States. In capital markets, New Zealand pays a small country risk margin over other "western" economies. This risk margin needs to be factored into transfer pricing studies which rely wholly on overseas comparables.

Industry data dumps don't work

The best comparables are those that exhibit key economic characteristics closest to the targeted company or transaction. Our policy guidelines require the consistent use of one or more reliable comparables. "Industry data dumps" are not acceptable, even if additional statistical analysis is provided using various measures of central tendency (such as interquartile ranges, medians and averages). Statistical tools may to some extent enhance the reliability of data carefully selected, but can not enhance inappropriately selected comparables. Regression analysis too, is only as good as the robustness of the model employed, the underlying assumptions and the data input.

Working capital adjustments

Should adjustments be made routinely for the opportunity cost of money tied up in working capital (inventory, accounts payable and receivable)? Our view is that the complex algebra is generally not worth the trouble as the resulting adjustments are very minor. The underlying assumption is that all companies are efficient profit maximisers, but poor management may be the simple reality. Rather than embarking on adjustments, questions should really be asked as to why the tested party or suggested comparables have material deviations in working capital levels. The answer may highlight un-commercial trade terms.

Watching out for IFRS aberrations

The wider adoption of International Financial Reporting Standards (“IFRS”) should assist comparability analysis as fewer adjustments are required to take into account country differences in accounting standards. Close inspection of potential comparables is required in the transition period, especially where material one-off adjustments arise.

Extreme results

In the context of comparable ranges, economic theory does not support the presence of extreme results in a long-run competitive scenario. This means that losses and unusually high profits should be excluded from such ranges as they are unlikely to be representative of normal business conditions  - rather, these results will most probably have arisen due to more risks being borne than by the controlled company under examination.

It may be that an otherwise perfect comparable experiences an aberrant year due to a one-off event. As a matter of practice, it may be that this single observation should be excluded if there is an identifiable reason for the event, but observations for other years should not be automatically ruled out.

Regional price lists.

Care is also needed in using regional price lists and trade association data. High comparability standards are required where the Comparable Uncontrolled Price method is applied. Such materials generally include both controlled and uncontrolled transactions and do not provide details as to terms, conditions and risks assumed.

Analysis of multiple year comparables

Typically, when multiple year data is utilised in forming an arm’s length range, the multiple year data is converted to a weighted average profit level indicator (“PLI”) for each comparable. The range is constructed using the weighted average PLI of each comparable ("the weighted average approach").

An alternative method, known as "the pooled approach", is to construct a range using each annual PLI data point for each comparable. That is, if five years of data exists for each of the five comparables in the set, the range is constructed of 25 data points (the pooled approach), including the highest and lowest points. In contrast, five data points are produced for the weighted average approach. Inland Revenue does not accept the use of pooled ranges.

The 2010 OECD Transfer Pricing Guidelines discuss the use of multiple year data in paragraph 3.77. as follows:

"Multiple year data will also be useful in providing information about the relevant business and product life cycles of the comparables. Differences in business or product life cycles may have a material effect on transfer pricing conditions that needs to be assessed in determining comparability. The data from earlier years may show whether the independent enterprise engaged in a comparable transaction was affected by comparable economic conditions in a comparable manner, or whether different conditions in an earlier year materially affected its price or profit so that it should not be used as a comparable."

Consistent with the OECD Guidelines, we will accept the use of multiple year data for the purposes of assessing and improving comparability and may allow the use of weighted average comparable data points for this purpose.

In contrast, the pooled approach suffers from several major defects, in particular:

• The pooled approach treats each year of data for a comparable company as a discrete data point, thereby giving each point an equal weighting. This approach is inconsistent with the purpose of multiple year data use.
• The approach results in the inclusion of extreme data points which renders the resulting range less reliable.
• The number of data points available for each comparable has a greater bearing on the resulting range than the comparability and reliability of each comparable.
• The approach can result in a tested party's position being compared to a data point that occurred up to five years ago.

We have also noticed recently some questionable practices as to the selection of an appropriate arm’s length point within a range of comparable data. As noted in paragraph 168 of Inland Revenue’s Transfer Pricing Guidelines, rather than opting for statistical measures, we consider that it is the reliability of a comparable or comparables that is the more relevant issue. Paragraph 169 of our Transfer Pricing Guidelines outlines this. See "Forms and guides".

This statement does not imply that any point within a range will be accepted by Inland Revenue, or that we are necessarily prohibited from pursuing a transfer pricing adjustment if the circumstances require. By way of clarification, where a range comprises results of relatively equal and high reliability, then any point in the range can be regarded as arm's length. For example, this could occur where the comparable uncontrolled price method is used and the range comprises highly reliable uncontrolled prices.

Where a range comprises results of relatively equal but not high reliability then any point in the range cannot be regarded as arm’s length. In these circumstances it is not appropriate to argue that provided the tested party is within the range, albeit at the low end of the range, then the result of the tested party is arm's length.

 

Date published: 01 Dec 2010

Back to top