Get Rid of Unanimity Rule: The Superiority of Majority Rules with Veto Power

We study unanimous decision making under incomplete information. We argue that all unanimous decision rules are not equivalent. We show that majority rules with veto power are (i) Pareto superior to commonly used unanimous rules, and (ii) ex-ante efficient in a broad class of situations

Designing Contests Between Heterogeneous Contestants: An Experimental Study of Tie-Breaks and Bid-Caps in All-Pay Auctions*

A well-known theoretical result in the contest literature is that greater heterogeneity decreases investments of contestants because of the “discouragement effect.” Levelling the playing field by favouring weaker contestants through strict bid-caps and favourable tie-breaking rules can reduce discouragement and increase the designer\u27s revenue. We test these predictions in a laboratory experiment. Our data confirm that placing bid-caps and using favourable tie-breaking rules significantly diminishes discouragement of weaker contestants. However, its impact on revenues is muted by the fact that the encouragement of weaker contestants is offset by stronger contestants competing less aggressively, even when not predicted by theory. We discuss deviations from the Nash predictions in light of different behavioural approaches

Composite SUVR: a new method for boosting Alzheimer's disease monitoring and diagnostic performance, applied to tau PET

Background: Abnormal brain tau protein accumulation is strongly linked to multiple neurodegenerative disorders. Currently, brain tau pathology is quantified in vivo using tau PET by calculating the Standardized Uptake Value Ratio (SUVR) of target and reference regions of interest (ROIs). Recent work (Schwarz et al., 2021) in Alzheimer’s Disease (AD) explored various target and reference ROIs to report performance of SUVR as a biomarker for diagnosis, disease monitoring, and clinical trial efficacy/eligibility (sample size estimate, SSE). Here we introduce a new method and biomarker: Composite SUVR (CUVR). / Methods: We analyzed longitudinal SUV data from ADNI in the available 103 participants having three or more tau PET scans ([18F]AV-1451): 58 cognitively normal (CN); 21 mild cognitive impairment; 24 probable AD. In the spirit of SUVR and statistical ROIs (Chen, et al., NeuroImage 2010), we calculate CUVR as the SUV ratio of two composite regions. Our novel method is that the composite regions are determined by a genetic algorithm that searches the possible 3^96 combinations of regions from FreeSurfer’s default atlas. We compare performance of SUVR with CUVR. Performance metrics follow Schwarz et al.: a linear mixed-effects model quantifies longitudinal group separation by tau accumulation rate (t statistic between fixed effects for CN and AD) and longitudinal precision (model residuals’ standard deviation). CUVR and SUVR values were log-transformed before model fitting. We calculated SSE for a hypothetical clinical trial designed for 80% power to reduce tau PET accumulation by 20% (vs. placebo) in non-CN individuals. / Results: Our method identified a CUVR biomarker involving 60 regions. Figure-1 shows the vast performance improvement of CUVR versus the best-performing SUVR (inferior-temporal target; eroded subcortical white matter reference). Group separation improved by 2.9x (t = 9.57 vs 3.32); longitudinal precision by 6.5x (residual std = 0.331% vs 2.14%); and CUVR required a smaller sample size by 3.9x (83 vs 318). / Conclusions: Our simple data-driven approach discovered a new tau PET biomarker called CUVR. Experimental results show state-of-the-art longitudinal group separation, longitudinal precision, and clinical trial enrichment. The remarkable performance improvements provide compelling evidence for using CUVR for both eligibility and efficacy in Alzheimer’s disease clinical trials, particularly of anti-tau therapies

The power of sunspots: An experimental analysis

This paper presents an experiment on a coordination game with extrinsic random signals, in which we systematically vary the stochastic process generating these signals and measure how signals affect behavior. We find that sunspot equilibria emerge naturally if there are salient public signals. However, highly correlated private signals can also lead to sunspot-driven behavior, even when this is not an equilibrium. Private signals reduce the power of public signals as sunspot variables. The higher the correlation of extrinsic signals and the more easily they can be aggregated, the more powerful these signals are in distracting actions from the action that minimizes strategic uncertainty

Unanimous rules in the laboratory

We study the information aggregation properties of unanimous voting rules in the laboratory. In line with theoretical predictions, we find that majority rule with veto power dominates unanimity rule. We also find that the strategic voting model is a fairly good predictor of subject behavior. Finally, we exploit a framing effect to study how the presence of less sophisticated agents affects Veto's welfare properties.SCOPUS: ar.jinfo:eu-repo/semantics/publishe