Abstract

We analyse the impact of intermediaries' concentration on the allocation of revenues in online platforms. We study sponsored search - the sale of ad space on search engines through online auctions - documenting how advertisers increasingly bid through a handful of specialized intermediaries. This enhances automated bidding and data pooling, but lessens competition whenever the intermediary represents competing advertisers. Using data on nearly 40 million Google's keyword-auctions, we first apply machine learning algorithms to cluster keywords into thematic groups serving as relevant markets. Then, through an instrumental variable strategy, we quantify a negative and sizeable impact of intermediaries' concentration on platform's revenues.