Bayesian Analysis of Spatial Probit Models for Investigating the Adoption of High Yielding Wheat Varieties

The aim of this study, firstly, is to investigate and identify the factors leading to the adoption of high yielding wheat varieties grown by farmers. Secondly, it is to consider the impacts of neighborhood on farmers’ decisions about adoption of wheat varieties as spatial data. For this purpose, Spatial Probit Discrete Choice model and Bayesian method will be used to estimate the model by using MATLAB software. The data are collected by 214 farmers in central part of Qazvin city via Simple Random Sampling. The results of the models estimated by using Bayesian method shows that adoption of high yielding wheat varieties are affected by variables such as rural production cooperatives, farming experience, age, quantity of wheat production and Spatial Autoregressive Coefficient