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Thursday, June 16, 2016

What underpins demand for wool?

By Andrew Woods  |  Source: World Bank, OECD, BIS, AWEX, RBA, ICS

Key points

  • GDP measures have a weak relationship with wool prices.
  • BIS calculated changes in credit have a high positive correlation with changes in wool prices during the past 14 years.
  • The correlation between credit and wool prices allows a more accurate estimate of the effect that changes in supply are likely to have.
  • Monitoring changes in credit will help assess what is happening to gross demand for wool and other commodities.

2016-06-16 Wool Fig 1

2016-06-16 Wool Fig 2

In the 1980s the rule of thumb used by Australian Wool Corporation economists (who were good at their job but ignored by the board) was that an OECD GDP growth rate of 3% or more was a precursor to rising wool prices. The story was more complex than that as the level of wool stocks played a big role in wool prices. This article takes a look at the relationship between wool prices and GDP, and proposes an alternative measure of macro demand for the wool market.

Figure 1 compares the year on year change in the 21 MPG (in US dollar terms) and the year on year change in the GDP of advanced economies from 2002 onwards. Starting around 2002 works for the wool market as it corresponds to the beginning of the post stockpile market. An average GDP across advanced economies is used as a proxy for economic growth which traditionally underpins the price cycles seen in the wool market (and other apparel fibre prices.) The major components of the cycles seen in the GDP measure are reflected in the change in the wool prices but the correlation is a very weak one.

The Bank for International Settlements (BIS) has put together a range of time series data for credit in a wide range of countries in recent years. Change in the stock of credit has traditionally not been a focus of record keeping but this is changing as changes in the stock of credit is seen as an indicator of economic activity. Figure 2 shows the same year on year change in wool price as Figure 1, with the year on year change in private non-financial credit for advanced economies from 2002 onwards.

In the decade to 2012 the correlation between the change in private credit and wool price is 0.64, meaning that changes in private credit in the advanced economies explained some two thirds of the year to year change in the wool price (21 MPG in US dollar terms). Since 2012 the correlation has dropped away although betting against the trend in the credit cycles is still a risky proposition for wool prices, especially if a lag of 3-4 months is added between the credit cycle and wool prices.

The credit series produced by the BIS appears to offer the best view of the macro demand for wool (and other fibres/commodities). By understanding how much price is influenced by the demand side of the market we can more accurately assess how changes in the supply side (which we have good information on) are likely to affect price. 

What does this mean?

A clear link between supply/demand and price is something of an El Dorado for market analysis. It is an El Dorado because the world is a complex and changing place, so such links come and go. However the credit series from the highly regarded Bank for International Settlements allows us to link wool prices to economic activity in the advance economies. This allows us to better understand where we are in terms of demand cycles (high, middling or low), which in turn allows us to better assess price risk.

Mecardo information is provided to assist in your marketing decisions. It contains a range of data and views on the current market. It is not intended to constitute advice for a specific purpose. Before taking any action in relation to information contained within this report, you should seek advice from a qualified professional. The information is obtained from a variety of sources and neither Mecardo nor Ag Concepts Advisory will be held liable for any loss or damage whatsoever that may arise from the use of information or for any error or mis-statement contained in this report. 


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