The past few decades have ushered in an experimental revolution in economics whereby scholars are now much more likely to generate their own data. While there are virtues associated with this movement, there are concomitant difficulties. Several scientific disciplines, including economics, have launched research registries in an effort to attenuate key inferential issues. This study assesses registries both empirically and theoretically, with a special focus on the AEA registry. We find that over 90% of randomized control trials (RCTs) in economics do not register, only 50% of the RCTs that register do so before the intervention begins, and the majority of these preregistrations are not detailed enough to significantly aid inference. Our empirical analysis further shows that using other scientific registries as aspirational examples is misguided, as their perceived success in tackling the main issues is largely a myth. In light of these facts, we advance a simple economic model to explore potential improvements. A key insight from the model is that removal of the (current) option to register completed RCTs could increase the fraction of trials that register. We also argue that linking IRB applications to registrations could further increase registry effectiveness.

No abstract

We introduce a robust approach to study dynamic monopoly pricing of a durable good in the face of buyer learning. A buyer receives information about her willingness-to-pay for the seller’s product over time, and decides when to make a one-time purchase. The seller does not know how the buyer learns, but commits to a pricing strategy to maximize profits against the worst-case information arrival process. We show that a constant price path delivers the robustly optimal profit, with profit and price both lower than under known values. Thus, under the robust objective, intertemporal incentives do not arise at the optimum, despite the possibility for information arrival to influence the timing of purchases. We delineate whether constant prices remain optimal (or not) when the seller seeks robustness against a subset of information arrival processes. As part of the analysis, we develop new techniques to study dynamic Bayesian persuasion.

No abstract