The aim of this study was to determine factors affecting wheat insurance demand by the farmers of Neyshabour region as well as to compare the estimated parameters by classical and Bayes approaches in large and small samples. Data were collected from 125 farmers (large sample) and 50 farmers (the small sample) were randomly selected among the large sample. Logit model was applied to the data for pursuing the objectives of this study and Maximum Likelihood Estimation (MLE) and Metropolis Hastings Sampling (MHS) were applied to estimate parameters of the model. In large sample, the results showed that variables such as family size, having non- agriculture occupation, type of ownership and risk taking have negative and variables such as education level, participating in extension classes and cultivated land have positive effects on insurance demand with both MLE (classical) and MHS (Bayes) approaches. Moreover, in small sample, the results indicated that the estimators of Bayes approach are more robust than classical approach. Therefore, it is possible to increase farmers demand for crop insurance by using policies such as increasing the farmers' education level, holding extension classes and conceding incentives such as credit.
Karbasi, A., Ziaee, S., & Abdeshahi, A. (2010). Determining Factors Affecting Wheat Insurance Demand: The Comparison of Classical and Bayes Econometric Approaches. Agricultural Economics, 4(2), 149-163.
MLA
Alireza Karbasi; Saman Ziaee; Abbas Abdeshahi. "Determining Factors Affecting Wheat Insurance Demand: The Comparison of Classical and Bayes Econometric Approaches". Agricultural Economics, 4, 2, 2010, 149-163.
HARVARD
Karbasi, A., Ziaee, S., Abdeshahi, A. (2010). 'Determining Factors Affecting Wheat Insurance Demand: The Comparison of Classical and Bayes Econometric Approaches', Agricultural Economics, 4(2), pp. 149-163.
VANCOUVER
Karbasi, A., Ziaee, S., Abdeshahi, A. Determining Factors Affecting Wheat Insurance Demand: The Comparison of Classical and Bayes Econometric Approaches. Agricultural Economics, 2010; 4(2): 149-163.
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