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Unstable prices

Agricultural crops, and other ‘soft’ commodities are susceptible to random, sudden and unpredictable changes in market conditions – known as demand and supply-side shocks.

Commodities such as wheat, coffee and cotton, are commonly produced under conditions of uncertainty which result from bad weather, disease and natural disasters. This can lead to volatile incomes received by farmers and growers, unstable prices, and unpredictable export revenue.

Underlying conditions

Sudden changes in market conditions are often amplified as a result of a particular mix of underlying factors commonly found in these markets.

Relatively elastic long run supply

Supply of agricultural commodities in the long run is likely to be relatively elastic given that many farmers and growers are able to convert their land from one use to another, and therefore increase or decrease supply depending on the expected relative prices of the commodities they can produce. Supply in the long run will be based on expected trends which will be used to plan for any future expansion of capacity.  For example, in Bangladesh, like many other producing countries, significant areas of land can be used to produce either wheat or a range of other crops. An expected rise in the price of cotton in the long run would, for example, encourage producers to switch from away from wheat to cotton.

So, long run supply for a specific commodity tends to be elastic, and the long run supply curve will be relatively ‘flat’ with its origin coming out of the ‘Y’ axis, as shown.

long run supply

Perfectly inelastic short run supply

However, in the short run output cannot easily be increased (or decreased) quickly, meaning that short run elasticity of is likely to be much lower than 1.0. This is because the cultivation of crops follows a particular sequence, beginning with planting and ending with harvesting and processing. This cycle can take many months.

For example, in Bangladesh cotton seeds are sown between July and September, which is towards the end of the rainy season, and cotton is harvested between November and March, which are typically the dry seasons. Any change in demand or price after the start of the growing season will not lead to a change in the amount of output available during the harvesting season. This is unlike how manufacturing and services can respond to market conditions.

An increase in the demand for manufactured goods, or an increase in their price will encourage an increase in production - which is only constrained by the availability of factor inputs. Factories can work extra shifts when demand is high, or when price rises. Given that this is not possible for many farmers and growers, price elasticity of supply in the short run is perfectly inelastic, with a numerical value approaching zero.

Small scale producers

The fact that many producers of crops and foodstuffs are small scale and widely dispersed is significant in limiting their ability to respond effectively to changing market conditions. Many lack a sophisticated understanding of the market, and how changing trends affect them, or have no access to market intelligence and new technology. Hence, they may not respond rationally to price changes or changes in other market conditions.

Dynamic price instability

When we put this together, we can see how periods of instability can arise. Awareness of the regularity of ‘price cycles’ goes back over 100 years (1). The starting point for most analysis is to pose the question ‘why are many commodity prices’ so volatile when basic market theory suggests that markets move quickly towards establishing a stable equilibrium price.

The cobweb theorem

The formalisation of the ‘cobweb’ theorem is closely associated with American economist, Mordecai Ezekiel who, in 1938, laid out various cases of unstable prices (2).

Ezekiel identified three main cases of unstable prices: ‘divergent’ fluctuation, ‘convergent’ fluctuation and ‘continuous’ fluctuation. What differentiates these is the relationship between demand and long run supply.

Case one

In case one, long run elasticity of supply is greater than demand, which means that even a small change in market conditions can trigger an extended period of diverging price fluctuations. If we take wheat as our example crop, the following diagram represents the starting point of the analysis, with a stable equilibrium price of $250 per metric ton, and with 10 million tons going to market.

The cobweb diagram

As the graph indicates, long run supply is relatively elastic (the curve originates from the Y-axis), with the intersection point at ‘a’ in year 1 (say, 2020). If we now assume that, in 2020 there is a negative supply shock in the form of flooding during the harvesting season, with a 10% loss of output. The new output is represented by the short run supply curve S1, with only 9 million tons harvested and taken to market. The effect of this can be added to the diagram, as shown.

The cobweb diagram

Assuming demand for wheat is relatively inelastic (with a large share of demand coming from the main bread producers), the price in 2020 will be driven up to point ‘b’, at price $280. When growers plan how much to produce in 2021, they will base their output on their long run view of supply, represented by the long run supply curve. If we read across, we can see that, at $280, producers will increase output to 12 million tons. (Shown as short run supply, S2.)

The cobweb diagram

This now triggers a period of diverging price fluctuations. Assuming that in 2021 there are no further supply shocks, the price will be driven down to just $200. At such a low price, farmers now decide to switch away from wheat to a better performing crop and reduce planned output for 2022 to just 5 million tons. The effect of this relative shortage of crops going to market is to drive price up to $380 – nearly double the price in the previous year.

If we follow this sequence, the price path diverges with increasingly large changes from year to year. The price movements are increasingly large, starting at $250, falling to $200 and ending the sequence on $380. Eventually the price would fall to such a low level that producers would move out of this crop altogether.

The cobweb diagram

So, rational producers will base next year's output on this year's price, even though this could trigger a prolonged period of price instability. This would create a significant problem for countries as farmers and growers might eventually leave the land when prices fall to an unsustainable level, with a subsequent collapse commodity production.

Case two

In case two, elasticity of supply in the long run is less than demand, and the initial supply shock eventually works is way out through smaller and smaller price changes – the ‘convergent’ cobweb.

The cobweb diagram

Case three

In case three, elasticities of demand and supply are counter balancing, with ‘neutral’ elasticities, so that an initial shock results in continuous fluctuations between a relatively fixed range of price.

The cobweb diagram

Criticisms of the theorem

As with many neo-classical approaches, the assumption is that competition is perfect and that no single producer or consumer can influence price. In reality, producers can combine and act together to help stabilise price and hence dampen any price fluctuation.

Also, governments can intervene to absorb the initial shock and dampen future price movements by operating various price stabilisation schemes. The model also assumes that, during the production cycle, producers have little effect on output, but with modern cultivation techniques using new technologies, producers may possess a greater ability to influence output, by changing production levels during the season.

In addition, as noted by Ezekiel (p272), growers can reduce excess output simply by not harvesting it, which would limit the downward effect on market price of previous excess production.

Finally, the model assumes that farmers can readily increase the quantity of crops in response to higher prices, but there are limits to this, meaning that the extreme reactions to price rises may not be found.

However, despite the limitations of the model it is clear that commodity prices in the real world do exhibit price cycles, even allowing for the dampening effect of intervention schemes (such as buffer stock schemes) and other counter-cyclical factors. A quick look at global wheat prices in recent years suggest that even with improvements in technology and modern storage methods, prices can still become very unstable. 


The case of unstable agricultural commodity prices is still regarded as a significant example of market failure, where intervention may be required to remove or control some of the underlying factors that contribute to such instability.

(1) S. Benner, Benner's Prophecies of Future Ups and Downs in Prices, Cincinnati, 1876. 

(2) Mordecai Ezekiel (February 1938). "The Cobweb Theorem" (PDF). Quarterly Journal of Economics. 52 (2): 255–280. doi:10.2307/1881734. Archived from the original (PDF) on 2015-06-16. Retrieved 2020-09-28.


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