This project aims to understand the relationship between media revenue models and the incentives to create high quality content. We plan to conduct an observational analysis that studies how newspaper content quality changes following the introduction or removal of a paywall. Our primary dataset consists of daily newspaper article data that has been collected from approximately 3,000 publishers in the United States. We will match a set of treated publishers that have recently introduced a paywall, including large publishers such as Fortune and Slate, to control publishers who do not require a subscription and are advertiser supported. We will use Twitter data as an outcome measure of quality. In particular, we plan to augment Gentzkow & Shapiro 2010 with politicians’ tweets rather than congressional speeches.