Application of Generalized Maximum Entropy (GME) as a procedure in demand function estimation was the main purpose of this study. The demand functions of 35 major agricultural products were estimated in the form of 14 commodity groups. The own and cross demand price elasticities were calculated for these groups. Required data were obtained from average prices and aggregated consumption quantities of Iran agricultural products in 2008. Results showed that demand quantities of the most commodity groups are less elastic to price changes. On the other hand, since the model includes the major part of agricultural products, it is similar to an agricultural sector equilibrium model. Therefore, a change in consumption amount of each commodity group should affect consumption amount of other groups. Consequently, the signs of majority of cross elasticities were positive, which shows substitution relation among commodity groups. In other words, by decreasing the amount of one commodity group in consumption basket, people substitute commodity of other groups. Comparing the results of the current study with previous studies in Iran upholds maximum entropy method as a suitable alternative for econometrics methods for estimation functions, especially when sufficient data is not available or collecting sufficient data needs much time and costs.
Sabouhi, M., & Ahmadpour, M. (2012). Estimation of iran agricultural products demand functions using mathematical programming (Application of maximum entropy method). Agricultural Economics, 6(1), 71-91.
MLA
Mahmood Sabouhi; Mahmood Ahmadpour. "Estimation of iran agricultural products demand functions using mathematical programming (Application of maximum entropy method)". Agricultural Economics, 6, 1, 2012, 71-91.
HARVARD
Sabouhi, M., Ahmadpour, M. (2012). 'Estimation of iran agricultural products demand functions using mathematical programming (Application of maximum entropy method)', Agricultural Economics, 6(1), pp. 71-91.
VANCOUVER
Sabouhi, M., Ahmadpour, M. Estimation of iran agricultural products demand functions using mathematical programming (Application of maximum entropy method). Agricultural Economics, 2012; 6(1): 71-91.
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