This report contains an overview of the relevant economic research literature on the digital transformation of news markets and the impact on the quality of news. It compares various definitions of fake news, including false news and other types of disinformation and finds that there is no consensus on this. It presents some survey data on consumer trust and quality perceptions of various sources of online news that indicate relatively high trust in legacy printed and broadcasted news publishers and lower trust in algorithm-driven news distribution channels such as aggregators and social media. Still, two thirds of consumers access news via these channels. More analytical empirical evidence on the online consumption of genuine and fake news shows that strong newspaper brands continue to attract large audiences from across the political spectrum for direct access to newspaper websites. Real news consumption on these sites dwarfs fake news consumption. Fake news travels faster and further on social media sites. Algorithm-driven news distribution platforms have reduced market entry costs and widened the market reach for news publishers and readers. At the same time, they separate the role of content editors and curators of news distribution. The latter becomes algorithm-driven, often with a view to maximize traffic and advertising revenue. That weakens the role of trusted editors as quality intermediaries and facilitates the distribution of false and fake news content. It might lead to news market failures. News distribution platforms have recently become aware of the need to correct for these potential failures. Non-regulatory initiatives such as fact-checking, enhanced media literacy and news media codes of conduct can also contribute.