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Tuesday, November 28, 2023 at 11:40am to 1:10pm
Statler Hall, 165
7 East Ave, Ithaca, NY 14850, USA
Stefano DellaVigna, University of California, Berkeley
"Fast or Slow? Uncovering Expert Views from Decision Time"
with David Card and Dmitry Taubinsky
Cognitive scientists and psychologists stress the information content of decision time, e.g., in drift-diffusion models. So far, however, economists have made limited use of the speed of decision-making outside of laboratory experiments. We show in the context of decision-making by journal editors and referees that decision time provides a valuable signal about the information held by experts. A simple two period model where an agent can decide in the first period whether to accept or reject a project, or pay a heterogenous cost and receive a second signal, yields two key predictions. First, decision time is inverse U-shaped in the expected quality of the project given initial information, peaking at the point where the probability of a positive decision is 1/2. Second, whether delay is associated with more accurate decisions depends on two opposing forces: a selection effect arising from the tendency to decide the clear-cut cases early; and a learning effect arising from the value of belated information. We bring these insights to the editorial decision setting, taking advantage of the fact that we observe a proxy for the quality of papers – accumulated citations -- as well as signals of the information available to the decision makers and the time taken at each step of decision. We document that the decision time is indeed inverse U-shaped in the strength of the early signals received by the editor and referees. Second, we show that citations are positively related to decision time for papers that are ultimately rejected, but negatively related to decision time for those that are ultimately accepted. In the context of our model this implies that the selection effect for early decisions dominates the learning effect. Indeed, fitting a structural version of our model, we find that the extra information in later signals is quite modest, suggesting that decision makers' costs of delay are low.
While we strongly encourage in-person attendance in 165 Statler Hall, a remote attendance option will also be available. If you are interested in participating remotely, please register at:
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Note: If you have previously registered for the Fall 2023 Behavioral Economics Workshop, there is no need to re-register—you will use the same link for the entire semester (see your confirmation email).
Note: The BEDR Workshop and the Behavioral Economics Workshop use separate links; hence, you still must register for the Behavioral Economics Workshop even if you have already registered for the BEDR Workshop.