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Free (Ad)vice

Author

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  • Matthew Mitchell

    (University of Toronto)

Abstract

Consumers increasingly rely on intermediaries (“influencers”) to provide information about products, often because product choice is vast. Examples include blogs, Twitter endorsements, and search engine results. Such advice is typically not paid for directly by the consumer, but instead the benefit to the influencer comes from mixing advice and endorsement, often in a way that is unobservable to the follower. Giving enough good advice is necessary to keep followers, but there is a tension between the best advice and most revenue. This paper models such a dynamic relationship between such an influencer and their follower. The relationship between influencer and follower evolves between periods of less and more ads. The model can provide insight into stricter enforcement of policies like the FTCs mandate of disclosure on paid Twitter endorsements. If disclosure makes adds less valuable, it may be that superior policies to tweet-by-tweet disclosure might exist. For instance an opt-in policy that effectively deregulates influencers with good reputations.

Suggested Citation

  • Matthew Mitchell, 2018. "Free (Ad)vice," 2018 Meeting Papers 1194, Society for Economic Dynamics.
  • Handle: RePEc:red:sed018:1194
    as

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    References listed on IDEAS

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