This paper investigated if the inspection procedures in organic certification may be improved exploiting information that is generally available from the control bodies involved in the certification process. The analysis was based on data from the archives of one of the largest Italian organic control bodies, containing information on operators’ characteristics, and including: risk scores for farmers, inspectors’ characteristics, type of inspection and the outcome of the inspection in terms of the type of non-compliance detected. The analysis considered both irregularities, i.e. mainly formal or bureaucratic non-compliance, and infringements, i.e. more substantial non-compliance. A bivariate probit model with random parameters was used to estimate the likelihood of, presumably correlated, irregularities and infringements, conditional to a set of covariates concerning risk assessment of the operators, inspector’s characteristics, and modalities of the inspections, including the period of the year scheduled for the inspections. The results showed that irregularities and infringements were actually correlated and that there is scope for improving the effectiveness of inspections, particularly using an appropriate timing for inspections and taking samples more frequently during inspections.
Improving controls in organic farming by timely inspections: a statistical analysis / Gambelli, Danilo; Solfanelli, Francesco; Zanoli, Raffaele. - In: BIOLOGICAL AGRICULTURE & HORTICULTURE. - ISSN 0144-8765. - ELETTRONICO. - 34:3(2018), pp. 186-198. [10.1080/01448765.2017.1421100]
Improving controls in organic farming by timely inspections: a statistical analysis
Gambelli, Danilo;SOLFANELLI, FRANCESCO;Zanoli, Raffaele
2018-01-01
Abstract
This paper investigated if the inspection procedures in organic certification may be improved exploiting information that is generally available from the control bodies involved in the certification process. The analysis was based on data from the archives of one of the largest Italian organic control bodies, containing information on operators’ characteristics, and including: risk scores for farmers, inspectors’ characteristics, type of inspection and the outcome of the inspection in terms of the type of non-compliance detected. The analysis considered both irregularities, i.e. mainly formal or bureaucratic non-compliance, and infringements, i.e. more substantial non-compliance. A bivariate probit model with random parameters was used to estimate the likelihood of, presumably correlated, irregularities and infringements, conditional to a set of covariates concerning risk assessment of the operators, inspector’s characteristics, and modalities of the inspections, including the period of the year scheduled for the inspections. The results showed that irregularities and infringements were actually correlated and that there is scope for improving the effectiveness of inspections, particularly using an appropriate timing for inspections and taking samples more frequently during inspections.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.