In this study, the demand for different types of meat including red meat, Poultry and fish have been analyzed from 1368 to 1390 in urban areas of Iran. In order to select the most Suitable model for demand, the SUR method out of Rotterdom, ”Almost Ideal Demand System” (AIDS) and CBS models have been used. Results from comparison of these models demonstrated that, “Almost Ideal Demand System “(AIDS) is selected as the superior model for prediction in the study period. Then the prediction of major demand for meat groups in areas that mentioned above, Performed until 2025(twenty-year vision of Islamic Republic of Iran). The results of this prediction, using genetic algorithm method and based on presupposition of continuation for previous incoming and pricing conditions, demonstrated that the share of the budget devoted to red meat, will gradually reduce for urban consumer and the share of the budget devoted to poultry and fish will increase. The demand rate of households from each these three groups for red meat, poultry and fish will increase. It means that the total demand rate for all kinds of meat will reduce as 2.59 percent every year. And also red meat, poultry and fish are essential (normal) and Successor commodities for urban consumer. On the other hand, red meat and poultry are inelastic commodities and fish is an elastic commodity.
Rahimi Baigi, S., Kohansal, M. R., & Dourandish, A. (2014). Prediction of Meat Demand in IRAN for Urban Areas Using Genetic Algorithm. Agricultural Economics, 8(3), 49-64.
MLA
Somayyeh Rahimi Baigi; Mohammad Reza Kohansal; Arash Dourandish. "Prediction of Meat Demand in IRAN for Urban Areas Using Genetic Algorithm". Agricultural Economics, 8, 3, 2014, 49-64.
HARVARD
Rahimi Baigi, S., Kohansal, M. R., Dourandish, A. (2014). 'Prediction of Meat Demand in IRAN for Urban Areas Using Genetic Algorithm', Agricultural Economics, 8(3), pp. 49-64.
VANCOUVER
Rahimi Baigi, S., Kohansal, M. R., Dourandish, A. Prediction of Meat Demand in IRAN for Urban Areas Using Genetic Algorithm. Agricultural Economics, 2014; 8(3): 49-64.
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