Becker Friedman Institute
for Research in Economics
The University of Chicago

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Free (Ad)vice

April 2017
Matthew Mitchell

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. Influencers who inherently value attention provide better advice for followers. 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 a opt-in policy that effectively deregulates influencers with good reputations. The model can also be interpreted as a search engine that biases organic search results to maximize profits, potentially at the expense of providing advice that leads to competing services. Market power by the influencer may be good or bad for welfare, despite bias, suggesting that biased search results by a dominant engine is not necessarily a justification for antitrust-type action.

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