This paper studies the effect of entertainment shows on the propensity to watch the news through viewers? inertia on channel choice. It uses the legally-induced cancellation of the game-show Pasapalabra in 2019 to study audience inertia around news- broadcasts. The cancellation of this popular show is estimated to have decreased news audience by about 28% on the largest Spanish news broadcast, which was emitted on the same channel directly after the cancelled show. This paper proposes a dynamic discrete demand model for audience with consumer inertia to show the impact of entertainment programming on subsequent news broadcasts. It employs a detailed clicker panel-dataset to disentangle heterogeneous consumer preferences from inertia. Additionally, it uses data from the 2019 Spanish national elections that happened before and after the cancellation to provide suggestive evidence that the decrease in viewership of Telecinco?s news broadcast can be associated to a decrease in voter participation.

Individuals are often exposed to information they did not actively seek, such as news shared by others, raising the question of how such information environments shape personal information choices. This paper studies how expectations of external information influence agents’ choices of news bias. Extending a standard model of Bayesian learning from biased sources to account for the anticipation of additional information, we show that expected information critically impacts news bias choices. We characterize the optimal learning strategy depending on the decision maker’s prior belief and the structure of the additional information, offering a novel explanation for why people often consume like-minded media news while also engaging with opposing ones. Applying this to social contexts, we find that highly uncertain agents tend to coordinate on the same news bias, whereas relatively certain individuals may opt for opposing ones. We also shed light on how to foster information acquisition among agents with more extreme beliefs.

This paper studies the role of viewers’ heterogeneous ad aversion for media content demand and advertisers’ willingness to pay. Using high-frequency individual level data from free-to-air TV permits us to observe viewers’ minute level choices from the consideration set of alternatives. We first illustrate the potential selection challenges of using market level data to estimate viewers’ demand for content and average ad elasticity. We find that ad elasticity varies considerably by content; however this could be due to heterogeneous individuals self-selecting into particular content. To address this problem we exploit minute-level data on individual choices to estimate viewers’ heterogeneous ad aversion adapting the demand model in (Dubois et al 2020) to media content. With this approach we prioritize estimating heterogeneous preferences without placing distributional assumptions on individuals’ ad aversion or on how it correlates with observable demographic characteristics. We find that ad aversion is highly heterogeneous and not strongly correlated with observable socioeconomic characteristics such as socio-economic status or gender. We can also disentangle ad aversion from cohort preferences for content and idiosyncratic inertia/state dependence, which are relevant also for the advertisers’ side of the market. Our findings indicate that advertisers’ willingness to pay per impression is positively associated with the content’s ability to reach audiences with high ad aversion. We find robust evidence of a per-impression price premium for ad slots that target individuals with higher levels of ad aversion.