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Prices for all commodities vary over time. The degree of instability for each commodity reflects characteristics of the industry. In the non agricultural industries the technology has certain input-output relationships. Few random factors affect the output. However, in agriculture some random factors make these relationships uncertain. Weather and biological conditions can result in output that is far from that planned by the producer. The coordination system within the marketing chain is also different for the two groups. In many non agricultural industries marketing arrangements, such as vertical integration and contacts ensure that the quantity produced will match the expected demand. So, within the marketing channels supply and demand are effectively coordinated. This is because mechanisms have been established to deal with the potential uncertainty of the system. Common uncertainties for agricultural and non agricultural industries are the competitive behavior of participants, changes in consumer preferences, prices of substitutes and complements, foreign supply and demand conditions, the potential development of new technology, governmental policies and so on. Both predictable and unpredictable instability are of concern. So as a measure it is better to choose one of instability rather than a measure of predictability. In this paper I will try to measure the variability caused by participants and random factors by three methods for 57 commodities and to compare the classification the three methods rank the 57 commodities.


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