Stability Analysis of Australia’s Wool Exports- A Markov Chain Model

The present study is an attempt to analyse growth, instability and direction of trade of wool exports from Australia. Compound Annual Growth Rate, Cuddy-Della Valle Index and Markov chain analysis are the tools used for analysing data from 2008 to 2017. The growth rate of export in terms of quantity is negative and very low (-0.59% per annum) and the growth rate of exports in terms of value is positive (3.99% per annum). The instability index is low (2.78%) for exports in quantity terms and is medium (18.10%) for exports in value terms. China is the most stable market for export of wool from Australia with retention probability of 80.08%. The other reliable importers are Republic of Korea and Czech Republic. The study suggested the need to diversify Australian wool market.

Quotidian Routines: The Cooperative Practices of a Business Elite

Cooperative corporate behavior has often been explained through the social anatomy of business leaders and structural ties among firms. Our alternative approach investigates how quotidian interactions built trust and routines among a group of major firms in the Australian wool trade—a sector that required regular interaction to be effective. Deploying extensive archives of their meetings, we use social network analysis to examine interactions among the key group of firms and individuals. Through content analysis we infer the behavior and atmosphere of meetings. Finally, an evaluation of meeting agendas and outcomes demonstrates cooperation and a shared commitment to improving the operation of the wool trade in the 1920s.

Fabric and greasy wool handle, their importance to the Australian wool industry: a review

Handle-related properties of woollen fabrics have been demonstrated to be major factors affecting consumer buying attitudes. Handle is the combination of both textural and compressional attributes. Compressional handle has demonstrated processing advantages in woven and knitted fabrics. The handle of processing lots can be manipulated using a variety of technologies but direct manipulation of textural greasy wool handle pre-processing is still crude. On-farm, there is documented evidence that including handle assessment in a selection index provides additional improvements in genetic gain. However, the assessment of greasy wool handle is based on a tactile evaluation of the wool staple by sheep and wool classers, and its application is affected by a lack of framework that instructs assessors on a standard method of assessment. Once a reliable and repeatable protocol is developed, further understanding of the effect greasy wool handle has on final garment quality will be possible.

Do price premiums for wool characteristics vary for different end products, processing routes and fibre diameter categories?

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.