Optimal Quality Assurance Systems for Agricultural Outputs

New quality assurance systems (QASs) are being put in place to facilitate the flow of information about agricultural and food products. But what constitutes a proper mix of public and private efforts in setting up QASs is an unsettled question. A better understanding of private sector incentives for setting up such systems will help clarify what role the public sector might have in establishing standards. We contribute to this understanding by modeling the optimal degree of "stringency" or assurance in a processor's quality control system over procurement of agricultural output when there exists uncertainty about quality. Our model addresses two questions: (1) Should a buyer of agricultural outputs implement a QAS as a way to gain and provide information about product quality to its potential customers? and (2) Given that it is profitable to adopt a QAS, what is the profit-maximizing degree of assurance in the system? We study a particular case in which the input buyer requires its suppliers to implement a given QAS. Increased stringency through the QAS reduces the probability of type I errors of falsely declaring that a product is of high quality and of type II errors of rejecting high-quality output. The optimal degree of assurance balances the marginal cost of increased assurance with the value of reduced type I and type II errors. The model predicts that the optimal degree of assurance depends on (1) the likelihood that the sought-after attribute is discoverable by consumers, (2) the price premium paid for the attribute, (3) the cost of quality control, and (4) the damage caused by false certification. A number of privately developed U.S. QASs are examined to see how well the model predictions are supported.