Media bias, competition and limited resources: the role of reputation

Abstract

Media news is the primary source of information for many people and decision-making processes. Usually, media companies are perceived as biased. In fact, media companies adopt specific political discourses and give preference to some news over others. This specialization on the media market can occur due to resource constrains. Previous literature considers different causes of media bias, however, the specialization on some type of news is usually ignored. This thesis has the objective to contribute to filling the gap in the literature on the consequence of competition in media markets and media bias when firms are able to specialize on certain news. To do so, it develops a model of competition in a media market where firms seek to maximize their reputation for providing information to a representative reader who rates their quality. More importantly, this model incorporates the fact that information is multidimensional and firms face constraints in their ability to learn from all relevant features for making a decision to incorporate the fact that firms can specialize. The results show that competition reduces bias via two channels: first, competition incentives firms to allocate their resources in a way such that they have more precision than their competitors; second, more competition leads to more accuracy, and more accuracy incentives firms to report honestly.