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Consumer Acceptance of Traffic-light Labelling on Food vs. Financial Products

  • Drescher, Larissa S.
  • Marette, Stephan
  • Roosen, Jutta

For products with risky characteristics, there are many debates about the best way to inform consumers. Traffic-lights have been already implemented in the UK on food products to guide consumers in making healthier food choices. In response to the recent financial crisis, a discussion about the compulsory usage of traffic-light labels on financial products has started by politicians and media in the UK and Germany. Similarly to foods, a green label on financial products would highlight a positive product attribute level (such as an above average rate of return); yellow that special attention is needed, whereas red would identify an adverse attribute level. This paper presents results of a choice experiment conducted in Germany to evaluate the impact of traffic-light labelling on food purchases in comparison to financial product purchases. Special attention is given to consumers’ involvement level in food and financial product purchases. In general, results indicate that traffic-lights affect consumers’ purchases of both product groups. While the low-fat attribute has no significant impact on food choices without traffic-lights, it has a positive impact on choices once signalled with a traffic-light label. We find that traffic-lights on financial products result in a halo-effect for the variance of returns: without traffic-lights, a product with a high variance of returns is chosen less often but more often if the product is labelled with a traffic-light.

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File URL: http://purl.umn.edu/114431
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Paper provided by European Association of Agricultural Economists in its series 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland with number 114431.

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Date of creation: 2011
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Handle: RePEc:ags:eaae11:114431
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  1. Hallstein, Eric & Villas-Boas, Sofia B, 2009. "Are Consumers Color Blind? : An empirical investigation of a traffic light advisory for sustainable seafood," CUDARE Working Paper Series 1088, University of California at Berkeley, Department of Agricultural and Resource Economics and Policy.
  2. Jae Bong Chang & Jayson L. Lusk, 2011. "Mixed logit models: accuracy and software choice," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(1), pages 167-172, January/F.
  3. Gunne Grankvist & Ulf Dahlstrand & Anders Biel, 2004. "The Impact of Environmental Labelling on Consumer Preference: Negative vs. Positive Labels," Journal of Consumer Policy, Springer, vol. 27(2), pages 213-230, June.
  4. Jutta Roosen & Stéphan Marette & Sandrine Blanchemanche & Philippe Verger, 2009. "Does Health Information Matter for Modifying Consumption? A Field Experiment Measuring the Impact of Risk Information on Fish Consumption," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 31(1), pages 2-20.
  5. David R. Just & Travis J. Lybbert, 2008. "Risk Averters that Love Risk? Marginal Risk Aversion in Comparison to a Reference Gamble," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(3), pages 612-626.
  6. repec:cdl:agrebk:918308 is not listed on IDEAS
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