The political economy of labeling

• Published in: Food policy Vol. 78; pp. 6 - 13
• Main Authors: Zilberman, David, Kaplan, Scott, Gordon, Ben
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2018
• Subjects: California; decision making; food policy; GMOs; Labeling; markets; Political economy; politics; Willingness to pay; California; GMOs; Labeling; Political economy; Willingness to pay
• ISSN: 0306-9192; 1873-5657
• DOI: 10.1016/j.foodpol.2018.02.008

•Mandatory labeling (ML) is optimal when many people strongly prefer “green” products.•Voluntary labeling (VL) is optimal if there is a minority who gain enough to pay for labeling costs.•No labeling (NL) is optimal when labeling costs are high and gains from information are low.•Gains from ML increase as the cost of VL increases and as more people favor “green” vs. “brown.”•ML may induce people to switch from brown to “green” products if labeling costs are high. Labeling arrangements are introduced to provide information and affect market outcomes. Mandatory labeling of products like genetically-modified organisms (GMOs) is subject to controversy and political debate. The exact outcome depends on the specific public decision-making process (direct vote by the public vs. voting by representatives), the political power distribution among groups, and the workings of legislative and regulatory processes. This paper presents a conceptual framework to assess the welfare implications of labeling decisions that are decided by political processes. We identify conditions under which there are gains from mandatory labeling compared to no labeling, and find that the gain from passing a mandatory labeling proposition is larger if the voluntary labeling option is not available. The conclusions suggest that when mandatory labeling is not feasible politically, promoters of labeling will introduce voluntary labeling. The paper uses the results of this conceptual framework to analyze different case studies of labeling propositions, including Proposition 37 that was voted on in California in 2012. The findings suggest that labeling decisions may evolve with new scientific knowledge, new information technologies, and changing attitudes.