This study investigates consistency in aggregation of wheat production in Iran’s provinces using data over period 1983-2007 to answer the question of whether one can aggregate all provinces with respect to wheat production and apply a unique economic policy to wheat production in all provinces. To this end, the Mean Scaling Hypothesis (MSH), developed by Coyle based on the Generalized Composite Commodity Theorem, was used as a basis for testing the aggregation consistency. Results indicate that only 10 provinces can be consistently aggregated, implying that an aggregate production function can only be defined for these 10 provinces and a unique policy be formulated just for these provinces. Therefore, aggregation of all provinces is not supported by the MSH. Such aggregation will result in an aggregation bias and consequently, to inappropriate policy decisions.
Salami, H., & Tahamipour, M. (2011). Testing aggregation over wheat producers in Iran: a mean scaling hypothesis approach. Agricultural Economics, 5(1), 1-15.
MLA
Habiballah Salami; Morteza Tahamipour. "Testing aggregation over wheat producers in Iran: a mean scaling hypothesis approach". Agricultural Economics, 5, 1, 2011, 1-15.
HARVARD
Salami, H., Tahamipour, M. (2011). 'Testing aggregation over wheat producers in Iran: a mean scaling hypothesis approach', Agricultural Economics, 5(1), pp. 1-15.
VANCOUVER
Salami, H., Tahamipour, M. Testing aggregation over wheat producers in Iran: a mean scaling hypothesis approach. Agricultural Economics, 2011; 5(1): 1-15.
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