Farm Landowners' Objectives in Finland: Two Approaches for Owner Classifications

Abstract

Two landowner classification methods based on owner objectives have been used to describe the heterogeneous group of farmland owners. As accurate information on landowner preferences is essential in policy planning and evaluation of the effects of various policy instruments, there is a need to develop feasible methods for classifying landowners. In this study we applied objective-based classification to Finnish farmland owners. The two classification methods compared in terms of their criterion validity were traditional cluster analysis and latent class analysis. Comparison of the convergent, concurrent, discriminant, and predictive components of criterion validity revealed that latent class analysis, particularly if sociodemographic covariates were included, was a slightly better classification method. Classification of farmland owners according to their ownership objectives was shown to be a relevant predictor of landowner behavior, and thus to provide valuable information for agricultural policymakers.