Quantitative Methods for Analysis of Factors Influencing Farmers’ Adoption of Technology.

Abstract

A study on factors influencing the adoption of farm innovation aims at understanding of farmers’ socio-economic characteristics, which affect farmers adoption. This paper reviews quantitative methods employed in the recent studies of adoption determinants and compares empirical results of the 6 methods applied to adoption of grass strip in integrated soil water conservation cropping systems in Mae Hong Son highlands, include ; (i) Spearman rank correlation (ii) chi-square test (iii) A model with grass strip area as dependent variable using the least square (LS) technique (iv) A logit model of grass strip ratio to total land holding of adopters with LS technique (v) A binary dependent model using LS technique and (vi) Finally Logit model for the binary dependent variable with maximum likelihood estimation. Since the tests of the independence of nonparametric methods rest on the impact of a given factor and ignore the influence of the others, their results are not all consistent with obtained by parametric methods. The techniques applied to models (iii), (iv) and (vi) are considered appropriate as the tests indicated that the specified models explain correctly. Nevertheless, the choice of the model depends on the information available for the dependent variable and its implication. The method (v) is not acceptable theoretically as the predicted value possibly goes beyond 0 and 1 and moreover, accuracy of prediction is only 77% as compare to 90% obtained from likelihood estimation.