Job Market Paper
Competition and Errors in Breaking News
Abstract: Reporting errors are endemic to breaking news, even though accuracy is prized by consumers. I present a continuous-time model to understand the strategic forces behind such reporting errors. News firms are rewarded for reporting before their competitors, but also for making reports that are credible in the eyes of consumers. Errors occur when firms fake, reporting a story despite lacking evidence. I establish existence and uniqueness of an equilibrium, which is characterized by a system of ordinary differential equations. Errors are driven by both a lack of commitment and by competition. A lack of commitment power gives rise to errors even in the absence of competition: firms are tempted to fake after their credibility has been established, capitalizing on the inability of consumers to detect fake reports. Competition exacerbates faking by engendering a preemptive motive. In addition, competition introduces observational learning, which causes errors to propagate through the market. The equilibrium features rich dynamics. Firms become gradually more credible over time whenever there is a preemptive motive. The increase in credibility rewards firms for taking their time, and thus endogenously mitigates the haste-inducing effects of preemption. A firm’s behavior will also change in response to a rival report. This can take the form of a copycat effect, in which one firm’s report triggers an immediate surge in faking by others.
Reputation in News Media: Speed vs. Accuracy
Abstract: We study news firms’ reporting behavior, including their propensity to misreport, when they are reputation driven. In our model, a news firm (sender) dynamically learns about a state and reports to a consumer (receiver). Senders are concerned with their reputation at the end of the game, and must choose when to time their report. We find that in equilibrium, the sender fakes, i.e., report despite being ignorant of the state, with positive probability in every period. This faking in turn leads to a higher level of misreporting than if the sender were instead truthful. We further find the sender’s reputations is endogenously rewarded for both speed and accuracy, and thus we provide a microfoundation to the speed-accuracy tradeoff in the news media setting. Finally, we consider the dynamics in the sender’s strategy, finding that the sender becomes more truthful, and thus less prone to misreporting, as time passes.
Dynamic Reputation-Driven Media Bias
Abstract: We study the dynamics of reputation-driven media bias. To this end, we present a dynamic model of reputation-driven media bias. A firm privately learns about an issue in increments and reports to a consumer with each new piece of information. With each new report, the consumer updates her beliefs about the firm’s information quality, i.e., the firm’s reputation. Firms are forward-looking and thus take into account both their immediate and future reputations when reporting. Nonetheless, we establish that equilibrium reporting behavior is identical for myopic and forward-looking firms. In equilibrium, firms bias their reports, and this bias is shown to be driven by two separate factors. First, firms can appear more reputable by appealing to a consumer’s prior bias (the prior effect). Separately firms with reports that are more consistent across time are viewed more favorably (the consistency effect). The relative importance of the consistency effect grows over time as the firm accumulates a richer history of reports.
Works In Progress
News Accuracy and Speed: Theory and Experiment (with Silvio Ravaioli)
Preemption and Private Learning