Testing Errors, Supplier Segregation, and Food Safety

32 Pages Posted: 19 May 2006

See all articles by S. Andrew Starbird

S. Andrew Starbird

Santa Clara University - Department of Information Systems & Analytics

Date Written: August 2006

Abstract

Diagnostic tests provide valuable information to buyers about credence attributes like food safety and GMO content. Errors in testing, however, can mislead buyers and lead to problems like adverse selection. The ability to segregate suppliers who can deliver safe food from suppliers who cannot depends on the accuracy of the test procedure. In this article we examine the effect of test sensitivity, specificity, and sampling error on the ability to segregate safe and unsafe suppliers. We find that there is a maximum level of error below which unsafe suppliers are deterred from accepting a utility maximizing buyer's bid price. The maximum error depends on the probability that a supplier's production is unsafe and the cost of producing an unsafe lot, among other things. Understanding this relationship makes it possible to design contracts and government regulations that discourage unsafe suppliers from trading.

Keywords: testing, sensitivity, specificity, sampling error, inspection, asymmetric information, food safety, adverse selection

JEL Classification: L14, L15, Q13

Suggested Citation

Starbird, Sterling Andrew, Testing Errors, Supplier Segregation, and Food Safety (August 2006). Available at SSRN: https://ssrn.com/abstract=903434 or http://dx.doi.org/10.2139/ssrn.903434

Sterling Andrew Starbird (Contact Author)

Santa Clara University - Department of Information Systems & Analytics ( email )

500 El Camino Real
Santa Clara, CA 95053
United States

HOME PAGE: http://omis.scu.edu/

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