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What forecast commodity prices mean for Australian regions

Agribusiness Bulletin

In a previous Agribusiness Bulletin, we considered the role of global agricultural commodity prices in driving farm revenue and, by extension, the prosperity of agriculturally dependent regional economies. In this article, we turn our gaze from the recent past to the future, and what forecast commodity prices mean for Australian regions.

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What forecast commodity prices mean for Australian regions

In a recent Agribusiness Bulletin article A free lunch for some we considered the role of global agricultural commodity prices in driving farm revenue and, by extension, the prosperity of agriculturally dependant regional economies. We looked at what historical and current prices meant for regional economies and found that, at the time, high beef, lamb, wool and sugar prices were driving increased revenues particularly in Queensland and the Tablelands region of New South Wales. While, on the contrary, depressed dairy and cotton prices were impacting Victorian dairy regions and North West New South Wales respectively.

In this article, we turn our gaze from the recent past to the future, and what forecast commodity prices mean for Australian regions.

Commodity price forecasts

Given the inherent uncertainty in supply and demand variables that influence agricultural commodity prices, any forecasts are also uncertain. Typically forecasts are based on supply and demand settings at the time, the supply and demand fundamentals of the forecast period, and a number of broad assumptions for unknown factors (such as an assumption for “average” weather conditions).

The below table shows two views of price changes over the next five years – one from ABARES and another from the Food and Agriculture Organisation of the United Nations (FAO). Clearly, there are divergent views on these two global price forecasts. In general, the differences relate to how quickly supply responds to increased or decreased demand and other underlying model assumptions. This reflects the inherent uncertainty in forecasting commodity prices. The numbers here are the average annual real price movement for key commodities for the next five years (2017-18 to 2021-22) compared to the average price for the last three years (2014-15 – 2016-17).

Table 1: Price change – average prices for 2014-15 to 2016-17 to average forecast prices (2017-18 to 2021-22)

 

Wool

Beef**

Lamb

Milk

Canola

Wheat

Sugar

Cotton

Coarse grains

Price change (ABARES)

7%

4%

-1%

5%

-6%

-15%

15%

5%

-14%

Price change* (FAO)

-

-15%

-

2%

-4%

-4%

-12%

-12%

-10%

* International forecasts are for real price change, in USD, for 2018-2021 period relative to 2014-2017 period. Dairy price based on whole milk powder price. ** USDA projection

In general, ABARES expects livestock industries (particularly wool, beef and dairy) to have a higher average price (in the next five years) than the last average price of the last three years. Beef, however, is coming off high prices in 2016-17 and is expected to decline in price every year (Table 1 shows a 4% increase which is due to a low 2014-15 beef price). The USDA has a similar expectation for beef prices to come down from its recent highs.

In relation to grains (wheat, canola and coarse grains) ABARES and FAO both expect weaker prices across the board. The expected decrease in the wheat price reflects abundant world supplies (from four successive years of record global production) and increased competition from other feed grains (corn and barley) on the global market.

With respect to sugar, ABARES has the average 5-year forecast price being 15% higher than the 3-year average historical price, reflecting the expectation that world sugar consumption will grow faster than the expected increase in production. Strong demand is being driven from the growing food-processing and beverage industries in developing countries, which in turn are driven by rising incomes and urbanisation. While the FAO notes the strong demand, particularly from Asia, and high prices at the beginning of the forecast period, it expects production to expand in many areas to meet increasing demand earlier than ABARES does.

Cotton prices are expected to increase slightly according to ABARES but decline according to FAO. ABARES expects cotton consumption to continue to outpace production over the medium leading to decreases in global stocks. A projected increase in oil prices also means the competition (in this case, synthetic fibre products) will increase in price. FAO, however, considers cotton prices to be relatively stable and decreasing in real terms in the next five years.

The increase in the wool price expected by ABARES is driven by stronger demand for fine wool from wool processors outstripping supply. As fine wool is a luxury product, higher incomes in developing countries (particularly China which is Australia’s largest export destination) are largely responsible for this increased in demand. On the supply side, good seasonal conditions have actually resulted in a higher volume and proportion of stronger and broader wools being produced and a lower proportion of the finer wools. This reduced proportion of finer wools has led to a higher average price for these wools and offset lower production.

Price impact on regions

When we translate the forecast price impacts into the agricultural production profiles of regions we can get a sense of the potential revenue impacts in particular Australian agricultural regions. Figure 1 maps the ABARES price impact on regions.

A particularly good news story here is that the fortunes of Victorian dairy regions are expected to turn around. The relatively modest 5% increase in milk price impacts these regions where a high proportion (sometimes as high as 80%) of agricultural production comes from dairy (e.g. Gippsland and south west Victoria in particular). Similarly, the intensive sugar producing regions on the northern Queensland coast (Cairns, Mackay and Burdekin) are also likely to receive higher revenues as a result of global price increases.

On the flipside, the sheep-wheat belt of eastern Australia and Western Australia are likely to experience reduced revenues. This is in spite of these regions being key wool producing regions because of the relatively low proportion of income from wool compared with grain income.

Regions that specialise in just one or two commodities are certainly more exposed to revenue changes, while regions that have diverse commodity production profiles are less exposed.

Figure 1: Average annual revenue impact of forecast commodity prices

Forecast commodity prices
Conclusion

Global commodity price changes are inevitable. For the period 1960 through to 2000, real food prices gradually fell (with the exception of a spike in 1974 related to the oil embargo imposed on the US which caused the global oil price to spike). This is because the increase in supply has kept pace with or exceeded any increase in demand, through the release of new land and/or increased productivity. However, from 2006 real food prices have increased for a number of reasons including a strong El Nino event affecting weather worldwide, increasing demand from population growth, impacts from the global financial crisis, increased energy and fertiliser prices, and policies promoting the production of biofuels.

Figure 2: Real food price index

Real food prices
Source: Food and Agriculture Organisation Food Price Index 2017

Looking forward, a rapidly growing and wealthier global population inevitably means that productive land will reach its limits (if it hasn’t already). In this reality, any supply increases will have to come from productivity increases alone or production techniques that do not rely so heavily on land resources – such as more intensive farming. Differentiation strategies for Australia, its regions or individual brands are also important to carve out higher value market segments and escape the negative phases of global commodity price cycles.

Sources

1 ABARES, Agricultural Commodities March quarter 2017 p59
2 ABARES, Agricultural Commodities March quarter 2017 p101

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