No Australian wool price hedonic studies have separated auction data into different end product-processing groups (PPR) on the basis of all fibre attributes that affect the suitability of wool sale lots for PPR. This study was conducted to assess: (1) whether including information about PPR groupings is more useful in understanding price than clustering by broad fibre diameter (FD) categories, and (2) if the ‘noise’ of macroeconomic effects on price can be reduced by using a clean price relative to the market indicator (RelPrice) formula or a log RelPrice formula compared with log price or clean price. Hedonic models using data derived from 369 918 Australian auction sale lots in 2010–2011 were estimated for these four dependent price variables. Linear FD models predicted less of price’s variance than quadratic or exponential models. Segmenting wool sale lots into 10 PPR before wool price analyses was found to increase the proportion of price variance explained and thus be worthwhile. The change in price with a change in FD, staple length and staple strength differs significantly between PPR. Calculating RelPrice or log RelPrice appears a better price parameter than clean price or log price. Comparing the RelPrice and clean price models, the mean absolute percentage errors were 6.3% and 16.2%, respectively. The differences in price sensitivity to FD, staple length and staple strength across PPR implies a complex set of price-setting mechanisms for wool as different users place different values on these wool properties. These price-setting mechanisms need to be incorporated in hedonic models for agricultural products that possess this characteristic. The wool price premiums can be used to estimate relative economic values when constructing sheep breeding selection indexes and can help determine the most profitable wool clip preparation strategies.
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