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.

We consider a Bayesian decision maker (DM) who, before making a decision, needs to allocate her limited attention across news sources with different biases. When choosing what news to read, the DM expects to receive some additional information in the future beyond her control. We show that the expectation of future information may affect the DM’s optimal learning decision in several ways. In particular, it can rationalize both the choice of news that reinforce or weaken ones prior (own and opposite-biased learning). The DM chooses own-biased learning when she is very certain of her action and, as long as the additional information is sufficiently powerful, opposite-biased learning when she is moderately certain. On the other hand, a very uncertain DM might want to make her choice of news dependent on the bias of the additional information. Applying our rational framework to study how expected future social interactions can impact peoples news consumption decisions, we show that people may (mis)coordinate the type of news they read with respect to their social group.

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.