Introduction to Scoring Methods: Financial Problems of Farm Holdings


  • Dominique Desbois


The goal of this paper is to provide a methodological introduction to “scoring” techniques on the basis of a case study about the financial problems of farm holdings. This case study is used as a teaching support for academic and vocational training in statistical data analysis.

First, this paper presents the estimation problem of financial risk, the constraints that in such a context the accounting data acquisition imposes, and the battery of the micro-economic criteria selected to measure the degree of insolvency of farm holdings. Secondly, the information provided by this battery of financial ratios is analyzed by way of multidimensional statistical techniques such as principal component analysis (PCA), and discriminant analysis. The framework provided by multidimensional tools such as PCA, discriminant analysis, and logistic regression procedures make it possible to show the methodological improvement carried out by such tools for this kind of micro-economic study. The results obtained are interpreted directly on the basis of outputs from the software used. Last, a measurement based on the ROC curve is provided in order to compare the classifying performances of linear discriminant analysis and logistic regression. This appraisal shows that the two methods are almost equivalent for individual prediction. A subset of the original data and SPSS code instructions are provided for training purposes.

This case study aims to offer a methodological introduction to the detection of financial risks applicable to farm holdings for analysts from public agencies (Regional Directorates) or professional and technical offices in charge of agriculture, as well as professional services specialized in technical and financial management (Chambers of Agriculture, Centers for Rural Economics). This case study is also currently used into the curriculum of the AgroParisTech engineering school for students completing their master degree.


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