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0 Table 1 COMOYDITY MWOELING METHODOLOGIES AND THE MOXELING PROCESS

|Methodologies|What is the purpose<br>of the methodology?|What quantitative<br>method is used?|What economic behavior<br>is specified?|Examples of Commodity<br>Applications|
|---|---|---|---|---|
|Market Models|Demand, supply,<br>inventories<br>interact<br>to produce an<br>equilibrium price in com-<br>petitive or noncompetitive<br>markets|Dynamic micro econometric<br>system composed of dif-<br>ference or differential<br>equations|Interaction<br>between decision<br>makers in reaching<br>market<br>equilibriun based on demand,<br>supply inventories, prices,<br>trade, etc.|Cocoa<br>Coffee<br>Jute<br>Sugar<br>Tin|
|Soatial Ecuilibrium<br>and Programming Models<br>Linear<br>and Quadratic<br>Prograoming|Spatial flows of demand<br>and supply and equilibrium<br>conditions<br>assigned<br>optimally<br>in equilibrium<br>depending on configuration<br>of transportation<br>network|Activity analysis of a<br>spatial and/or temporal<br>form.<br>Degree of complex-<br>ity deperds on endogeneity<br>and method of incorpora-<br>ting<br>demand and supply<br>functions|Interaction between de-<br>cision makers in allocating<br>shipments (exports) and<br>consumption<br>(imports)<br>optimized<br>through maxi-<br>mizing<br>sectoral<br>revenues<br>or minimizing<br>sectoral<br>costs|Iron<br>and Steel<br>Lead<br>and Zinc|
|Mixed Integer<br>Programming|Spatial and temporal<br>equilibrium<br>embodying<br>production-process,<br>transportation, and<br>project investment<br>tomponents|Activity analysis involv-<br>ingspatial<br>andtemporal<br>optimization<br>but also in-<br>cluding integer (0,1)<br>variables<br>to represent<br>capacity<br>additions|Interaction between de-<br>cisionmakers in finding<br>minimum discounted costs<br>of meeting specific market<br>requirements,<br>i.e.,<br>project<br>selection|Aluminum<br>Copper<br>Fertilizers<br>Iron ore|
|Optimization<br>Models|Supply and demand<br>analyzed<br>in relation<br>to optimal resource<br>exhaustion over time<br>and cartel behaviour|Dynamic microeconometric<br>system featuring<br>formal<br>cartel-fringe models such<br>as that of monopoly,<br>Stackelberg or Mash-<br>Cournot|Interaction between decision<br>makers in optimizing<br>resource<br>allocation and prices over<br>time in noncompetitive<br>markets involving bargaining<br>activity|Aluminum<br>Copper<br>Crude Oil|
|SystemsDynamics<br>Models|Demand, supply, inven-<br>tories interact to<br>produce an equilibrium<br>price emphasizing role<br>of amplifications and<br>feedback delays|Dynamic micro econometric<br>differential equation<br>system which features<br>lagged feedback relations<br>and variables in rates<br>of change|Interaction between decision<br>makers in adjusting rate of<br>production to maintain a<br>desired<br>level<br>of inventory<br>in relationship to rate of<br>consumption|Altuinum<br>Broilers<br>Cattle<br>Copper<br>Hogs<br>Orange Juice|
|Ifrut-Outout<br>Models|System regarded as process<br>that converts<br>raw materials<br>into<br>intermediate<br>and final<br>products<br>via intermediate<br>processes|Irput-output<br>model com-<br>bined with macro economic<br>framework or disaggregated<br>raw materials<br>balance<br>framework|Interaction<br>between non-fuel<br>and fuel<br>commodities<br>and<br>macro markets in reaching<br>materials<br>and energy balance<br>including<br>supply-demand<br>determination|Minerals<br>Energy<br>Agriculture|

Source: W. C. Labys, **_wd_** P. K. Pollak, Conmodit lodels fOI Pub!p