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Taking into account the practical constraints in obtaining comparable data in New Zealand and balancing compliance costs, see our expectations for a comparability analysis.

OECD guidance 

New Zealand’s transfer pricing rules are to be applied consistently with the OECD's Transfer Pricing Guidelines for Multinational Enterprises and Tax Administrations - July 2022, including the guidance on comparability analysis contained in Chapter III. This guidance is detailed and recommended reading for practitioners.

Transfer Pricing Guidelines for Multinational Enterprises and Tax Administrations (OECD)

A key message contained in the guidance 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 provides that the use of comparability adjustments is only justified to the extent that comparability is improved. 

We recognise there are practical difficulties in obtaining comparable data in New Zealand and a need to balance compliance costs. With this in mind, we outline below our expectations taking into account the practical constraints faced in New Zealand. 

Functional analysis 

Prior to undertaking a search for comparable data, it is crucial that an analysis of functions, risks and assets (especially intangibles) is undertaken. 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 'limited risk distributor' or 'contract manufacturer'). The process steps outlined in the OECD guidance are extremely useful in this regard. 

The economic factors that are critical to the specific transfer pricing issue being addressed must be identified and their impact fully discussed. It might also be useful to identify and explain why certain factors are not considered to be relevant. It is important that functional analyses are tailored to the situation at hand. 

Reflect economic characteristics 

The best comparables are those that exhibit key economic characteristics closest to the targeted company or transaction. In New Zealand, comparables are almost always very approximate and we are forced to use small samples. The quality of comparable data is more important than the number of comparables identified. 

Industry data dumps are not acceptable, even if additional statistical analysis is provided using various measures of central tendency. Statistical tools can't enhance inappropriately selected comparables. Regression analysis is only as good as the robustness of the model employed, the underlying assumptions and the data input. 

We will not accept the use of statistical tools that do not increase the reliability of the data. For example, we don't accept the use of pooled ranges (in other words, where the range is constructed by selecting each annual data point of every comparable, as opposed to a single weighted average data point for each comparable). 

Controlled data, obtained from transactions between two related parties, is not accepted. If there are difficulties in obtaining uncontrolled comparable data, it cannot be assumed that the relationship between two controlled entities has not affected the price or outcomes of a transaction. 

Overseas data

Appropriately selected overseas data is accepted. The 'same or similar market' principle is important in New Zealand. The New Zealand economy is closely connected to the Australian economy, often forming a single market. This is supported by both Government’s commitment to a process called the Single Economic Market agenda, designed to create a seamless trans-Tasman business environment. Australia is recognised as our closest reference country in terms of demographics, size of economy and stage of economic development. This means the economic results reflected in Australian data are equally likely to be felt by a New Zealand company with international trade.

Single Economic Market | New Zealand Ministry of Foreign Affairs and Trade (

In the absence of Australasian comparable data, to find practical solutions, we may have to look beyond Australia to markets in Europe (in particular the United Kingdom) and North America where reliable data may exist. Provided all comparability factors are fully considered and the industry and functions in question are similar, less emphasis may be placed on the country from which a comparable is taken. More caution is required in these situations to ensure that recognition is 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 and geographic remoteness. 

Capital adjustments 

Capital adjustments are neither mandatory nor routinely made in New Zealand. Our experience is that the complex algebra is generally not worth the trouble as the resulting adjustments are very minor. 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. 

Multiple year data 

Multiple year data is often useful, particularly when applying the Transactional Net Margin Method. Weighted average data for each comparable, based on the most recently available 3 to 5 years of data, will in our experience typically be reflective of the New Zealand business cycle.

Frequency of comparability analyses

Taxpayers are encouraged to review the continued applicability of comparability analyses each year, particularly bearing in mind any changes in the underlying transactions or business operations.

Where no significant changes are identified, and comparable data relied upon remains current, it will not be necessary to complete a new comparability analysis. Comparable data is likely to remain current if there is high degree of confidence that it reflects the current market and business cycle, particularly where an analysis of multiple year data demonstrates low market volatility over time. 

Last updated: 11 Apr 2024
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