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Risk-based certification in organic farming: Derivation of improved strategies based on the data of large German checkpoints


Project code: 2810OE019
Contract period: 01.11.2010 - 30.09.2013
Budget: 231,318 Euro
Purpose of research: Applied research

The objective of this research project is the further development of risk based inspection approaches in organic farming control systems. The existing risk based systems of five German control bodies were discussed during a workshop. The control data bases on the years 2009 and 2010 of these control bodies were merged, to quantitatively analyse the risk of non-compliance of organic farms with the European Union’s organic regulation (Reg. (EC) 834/2007). This approach and the method applied enlarge the up to now mainly qualitative evaluation of the risk of noncompliance. First, a descriptive data analysis on the attributes of the organic farms, their production structure, control frequencies and resulting control results, i.e., resulting sanctions is performed. This analysis revealed differences between control bodies regarding the structure of the inspected farms. This differences concern the spreading of farms over German federal states, shares of specific farm types, such as vineyards, and the share of farms that are member in a farming association. These specific characteristics of the farms inspected can affect the disclosure of noncompliance and hence can affect control results. Therefore, it is plausible that sanction frequencies of farms can differ between control bodies due to the different structure of the inspected farms. Notably, the most severe sanction is not documented in the control data bases of the five control bodies. Remarkable differences consist between control bodies regarding the imposition of slight sanction categories. The share of severely sanctioned farms in the period of investigation was 6.4 %. This characteristic was used as dependent variable in the statistic models. To estimate the risk of a severe sanction, logistic regression (logit) models were applied. The general characteristics of organic farms (farm size in hectares, organic control experience and membership in an organic farming association) and the characteristics of farm production were used to explain the occurrence of severe sanctions. Farm size (measured in hectares), farming of non-organic land or land in conversion, the cultivation of vegetables and bovine, pig and poultry husbandry were identified as factors that increase the risk of severe sanctions. Farming of permanent grassland, meadow orchards and grapes on the other side reduces this risk. The basic model specification only considered the farm characteristics. Subsequently, the logit models were extended by further variables that affect the detection of non-compliance and, hence, affect the imposition of severe sanctions. For that purpose, dummy variables for federal states with a large number of farms were added to the basic model to test for the influence of the competent authority which is responsible for the regional implementation of the European organic regulation. Accordingly, the model was extended by dummy variables for the five control bodies in the sample. Furthermore, different variables on sanctions in the previous year were used in the logit model. Finally, the different model extensions were combined to analyse the influence of specific variables. These models revealed significant and robust results for four out of the five control bodies and for two out of the three federal states analysed regarding their influence on the probability of severe sanctions. Since these models control for the influence of farm characteristics, there is strong evidence for a non-uniform implementation of the European organic regulation in Germany. Based on the statistical analysis and the discussion of its results with the control bodies that contributed to this research project, recommendations for the further development of risk based organic controls are given. These recommendations address organic control bodies, the competent authorities supervising the organic control system and research policy to further develop risk based organic controls to increase the efficiency of the control system.

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