Agricultural Marketing: Structural Models for Price Analysis by James Vercammen

By James Vercammen

The rate of nutrition has turn into very risky lately for a number of purposes, together with a bolstered connection among the costs of agricultural commodities and different commodities equivalent to oil and metals, extra risky creation because of extra widespread droughts and floods, and a emerging call for for biofuels. figuring out the determinants of agricultural commodity costs and the connections among costs has turn into a excessive precedence for teachers and utilized economists who're attracted to agricultural advertising and marketing and exchange, coverage research and overseas rural development.

This publication builds at the a number of theories of commodity expense relationships in aggressive markets over area, time and shape. It additionally builds at the numerous theories of commodity expense relationships in markets which are non-competitive simply because processing agencies make the most marketplace energy, inner most details distorts commodity bidding, and bargaining is needed to set up costs whilst the selling transaction contains a unmarried vendor and customer. every one bankruptcy includes a spreadsheet version to investigate a specific real-world case learn or believable situation, and matters thought of include:

  • the purposes for commodity expense transformations throughout regions
  • the connection among the discharge of data and the swift adjustment in a community of commodity prices
  • the particular linkage among strength and meals prices
  • bidding thoughts via huge exporters who compete in import tenders.

The simulation effects which are received from the spreadsheet versions display many vital positive factors of commodity costs. The types also are like minded for extra "what if" research similar to reading how the trend of exchange in agricultural commodities could switch if transport turns into costlier as a result of tremendous bring up on this planet fee of oil.

Model development and the research of the simulation effects is a powerful strategy to enhance serious pondering talents and to view agricultural commodity costs in a rigorous and distinct approach. this is often a terrific source for economics scholars seeking to achieve increase talents within the components of Agricultural advertising, Commodity cost research, versions of Commodity Markets, Quantitative equipment and Commodity Futures Markets.

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Extra resources for Agricultural Marketing: Structural Models for Price Analysis

Sample text

Storage has an important price stabilizing role across production periods. Storage creates a pricing buffer by shifting stocks forward through time from periods of above average stocks to periods where stocks are expected to be average or below average. Commercial firms typically require “pipeline” stocks to ensure that processing facilities and feedlots do not run short of key production inputs. Of particular interest in this analysis is speculative storage, which is storage in excess of these pipeline stock requirements.

An analytical solution most effectively illustrates the intertemporal properties of commodity prices for a storable commodity. Similar to the previous section, assume that production is exogenously fixed at level h and is thus independent of price. Also assume that market demand is linear and the marginal physical cost of storage is constant at level m. The LOP equilibrium is solved for by choosing the level of storage that maximizes the sum of producer revenue and consumer surplus minus the cost of storage over a T period time horizon.

The values in parentheses beside each region are the equilibrium prices. The solid arrows between regions identify the flow of shipments, and the dashed lines between regions indicate zero trade. The values near the lines that connect the regions are the unit transportation costs in dollars per ton. The pricing and unit transportation cost data allow for easy verification of the LOP. For example, notice that Latin America ships to Canada, the US and the EU. In all cases, the price in the importing region is higher than the Latin American price by (approximately) the corresponding unit transportation cost.

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