By analysing technologies which have not yet been adopted, ex ante IAs are
severely constrained by the quality and availability of data. In the literature,
cross-sectional comparisons of average cropping budgets (e.g. May, 2003; Flannery
et al., 2004) ignore heterogeneity of farmers and underestimate the ex ante
impact of technologies caused by homogeneity bias. Therefore, this article develops
and demonstrates an improved method for ex ante IA in the context of
monopolistically priced technologies by modelling farmer heterogeneity under
imperfect information. The article is organised as follows. Section 2 provides a
background of natural endowment, policies, plantings, pests, yields and protection
of crops in the two NMS. In section 3 we develop our modelling framework.
Section 4 discusses our methodology of data collection and stochastic
modelling of imperfect information. In section 5 we present the results and section
6 concludes.