Peer Recognition and Content Provision Online

This paper provides both theoretical and empirical studies on the incentive effect of peer recognition on online content provision. Our theoretical model illustrates how a Bayesian influencer strategically determines her online contribution. Using unique data from the largest Chinese Question-and-Answer platform, we analyze the content provisions of all the influencers with more than 10,000 followers on the platform over two years. Using an instrumental variable approach, we find that a simple OLS method is likely to under-estimate the incentive of peer recognition for content provision since the reputational and privacy concerns might have an adverse effect