Joint with George Georgiads, Sina Khorasani and Luis Rayo We derive optimal contests for environments where output takes the form of breakthroughs and the principal has an informational advantage over the contestants. Whether or not the principal is able to provide real-time feedback to contestants, the optimal prize allocation is egalitarian: all agents who have succeeded in a pre-specified time interval share the prize equally. When providing feedback is feasible, the optimal contest takes a stark cyclical form: contestants are fully apprised of their own success, and at the end of each fixed-length cycle, they are informed about peer success as well.
Joint with Andrea Galeotti and Jakub Steiner
We study rotation schemes that govern individuals’ activities within an organization during an epidemic. We optimize the frequency of rotation and degree of cross-mixing of the rotating subpopulations. Frequency affects risk over the length of diffusion within the infected subpopulation until the organization detects and/or reacts to the infection. If the reaction time is short, then such risk is undesirable since the growth of the prevalence is initially convex in time.
Frequent rotation, which acts as insurance against exposure time risk, is then optimal. Infrequent rotation becomes optimal if the organization reacts slowly. Mixing of the rotating subpopulations is detrimental because it increases the share of interactions between sick and healthy individuals. However, the effect of mixing is small if the terminal prevalence is low in the absence of mixing.