Cluster Analysis on Individual Risk: Some Results from Estonian Data. Christine Le Thi and Jesús Antón Trade and Agriculture Directorate

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1 Cluster Analysis on Individual Risk: Some Results from Estonian Data Christine Le Thi and Jesús Antón Trade and Agriculture Directorate Fourth meeting of the OECD Network for Farm Level Analysis, 7-8 September 2009

2 1 - Nature of the problem 2- Cluster analysis Outline Normalization of risk data Characteristics of three clusters 3- Cluster Analysis based on size farm Is cluster analysis better that size classes? 4- Implications and further work OECD Trade & Agriculture Directorate 2

3 Nature of the Problem Micro data is good to estimate variability at individual level, but: What is a representative farmer? Average values: including variance / covariance? An individual observed farm? An average farm inside groups of similar farmers? What criteria to define similarity? Risk related criteria vs Farm size OECD Trade & Agriculture Directorate 3

4 Description of the data From Estonian FADN (Farm Accountancy Data Network) Sample: 104 farm households Period coverage: from 2000 to 2007 Major commodity: Wheat, Oats, Barley, Rye, mixed cereal OECD Trade & Agriculture Directorate 4

5 2-Cluster analysis based on risk OECD Trade & Agriculture Directorate 5

6 Normalization of data according to risk Farm income (F) = Revenue from main production (Ri) + Revenue from rest of commodities (RoR) + + Subsidies (S) - Total costs (C) Var (F) = Var (Ri) + Var (RoR) + Var(S) + Var(C)+ + 2*COV (Ri,RoR) + 2*COV(Ri,S) *COV(S,C) Correct for the size: Variability is measured in terms of Coefficient of Variation Squared OECD Trade & Agriculture Directorate 6

7 Normalization cont. Normalization is carried out on: 4 variables on components of risks: R from wheat, rest of revenue, subsidies, cost 6 variables on covariance of components Normalization with the revenue factor = Revenue from Wheat + Rest of revenue + Subsidies OECD Trade & Agriculture Directorate 7

8 Normalization cont. Formulas : Variables on the variability of Revenue from wheat, Rest of Revenue, Subsidies and Cost are normalized according to their weight on revenue, e.g: Variables on covariance were normalized with respect to the previous normalization and multiplied by a factor 2 ( -2, if cost), e.g: OECD Trade & Agriculture Directorate 8

9 Cluster Analysis based on risk We used Normalized variables to perform the cluster analysis We carried out a standard Cluster analysis which is the hierarchical cluster analysis We used the Euclidian distance to join together all farms that are nearer from one another Ward s method has been applied OECD Trade & Agriculture Directorate 9

10 Main results on the different type of clustering Family farm income Rest of revenue Revenue from wheat Subsidies Cost COV (Cost, other) Other covariances Whole sample 2,027, Cluster analysis based on risk Cluster 1 910, Cluster 2 1,813, Cluster 3 2,027, Cluster analysis based on size Size (Revenue) Normalized variability of Cluster 1, M (0.1-1,7) 716, Cluster 2, M (1,9-3,6) 2,506, Cluster 3, M (3,7-5,5) 4,352, OECD Trade & Agriculture Directorate 10

11 Characteristics of three clusters Coefficient of variation (normalized) OECD Trade & Agriculture Directorate 11

12 Description of each cluster (example) Cluster 1: Low risk farms with risks spread on the different components Cluster 2: High risk farms with a large component of risk coming from the rest of revenue and cost risks Cluster 3: Medium risk farms with a larger component of the risk coming from the cost and revenue risks but compensated by the covariance (Cost, other) OECD Trade & Agriculture Directorate 12

13 3- Cluster analysis based on size OECD Trade & Agriculture Directorate 13

14 Description of the cluster analysis based on size (revenue) Clustering of farms according to their size revenue: we clustered the farms into 3 homogeneous size clusters in terms of revenue Size 1, farms in range [ ] Size 2, farms in range [ ] Size 3, farms in range [ ] OECD Trade & Agriculture Directorate 14

15 Characteristics of three size groups Coefficient of variation (normalized) by size group OECD Trade & Agriculture Directorate 15

16 Description of each group 3 groups with different size But marked by the same type of characteristics: 3 groups of farms are very similar to the average of the whole sample in terms of risk The risk component (in the 3 groups) is mainly explained by the risk on cost and the rest of revenue The risk cluster and the size cluster have similar number of farms OECD Trade & Agriculture Directorate 16

17 Implications and further steps The risk cluster analysis allows to differentiate the groups in terms of risk characteristics Clusters based on risk are preferable to other grouping (clustering based on size) for risk analysis We plan to improve this cluster analysis, particularly including price and yield variability We will plan to do modelling work with the Estonian data based on these clusters Should we try with the other countries? OECD Trade & Agriculture Directorate 17

18 Thank You Trade and Agriculture Directorate Visit our website: Contact us: OECD Trade & Agriculture Directorate 18