The existing method of certification in the organic agriculture system, which requires periodic inspection of all operators, is inefficient due to the high cost of these controls. A risk-based decision support system, which could assist the inspection body during the planning of the annual inspection visits, is advocated as being more cost-effective and efficient. The risk-based decision support system is constructed as a Bayesian network; the models incorporate the factors that influence risk of irregularity and analyse their effects by determining probability of noncompliance. Empirical findings, using a sample of Italian data regarding inspection of organic farms, support the idea that the current risk categories used by control bodies in Italy are reasonable, but could be recursively updated by using a Bayesian network model and incremental inspection evidence.
Keywords: Organic certification, risk-based inspections, risk modelling, discretechoice models, bayesian networks
Jel Code: C41