Ratings Design and Barriers to Entry

I study the impact of consumer reviews on the incentives for firms to enter and participate in the marketplace. Firms produce goods of heterogeneous, unknown quality that is gradually revealed through user-generated feedback, and face both entry and exit decisions. For each firm, the platform constructs a rating based on previous consumer feedback that provides the market with information regarding product quality. Under full transparency, consumers' equilibrium choices induces slow feedback rates for struggling firms and new entrants, inducing low entry rates as well as negative selection effects - high-quality firms exit early. This benchmark offers several theoretical predictions, some of which echo existing empirical findings, the others are novel and I test directly using data from Yelp!. I then turn to the design of such ratings systems. These platforms must balance the need to provide consumers with accurate information and high-quality experiences against the need to encourage firms to participate in the marketplace. The key insight is that optimal rating systems involve upper censorship, i.e. the exclusion of reviews from highly-firms' ratings, as a means of making the task of climbing the ratings hill less daunting, thus stimulating entry and stifling exit. Classification-JEL: L13, L43, L96