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Bayesian Clustering of Farm Types Using the Mixtures Model
Author(s) -
Tiffin Richard
Publication year - 2006
Publication title -
journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.157
H-Index - 61
eISSN - 1477-9552
pISSN - 0021-857X
DOI - 10.1111/j.1477-9552.2006.00064.x
Subject(s) - arable land , agricultural science , cluster analysis , livestock , farm income , diversity (politics) , bayesian probability , statistics , agricultural economics , geography , mathematics , economics , environmental science , agriculture , forestry , archaeology , sociology , anthropology
A Bayesian method of classifying observations that are assumed to come from a number of distinct subpopulations is outlined. The method is illustrated with simulated data and applied to the classification of farms according to their level and variability of income. The resultant classification shows a greater diversity of technical charactersitics within farm types than is conventionally the case. The range of mean farm income between groups in the new classification is wider than that of the conventional method and the variability of income within groups is narrower. Results show that the highest income group in 2000 included large specialist dairy farmers and pig and poultry producers, whilst in 2001 it included large and small specialist dairy farms and large mixed dairy and arable farms. In both years the lowest income group is dominated by non‐milk producing livestock farms.