The Equivalence of Contests

We use a Tullock-type contest to show that intuitively and structurally different contests can be strategically equivalent. Strategically equivalent contests generate the same best response functions and, as a result, the same efforts. Two strategically equivalent contests, however, may yield different equilibrium payoffs. We propose a simple two-step procedure to identify strategically equivalent contests. Using this procedure, we identify contests that are strategically equivalent to the original Tullock contest, and provide new examples of strategically equivalent contests. Finally, we discuss possible contest design applications and avenues for future theoretical and empirical research

Overdissipation and Convergence in Rent-seeking Experiments: Cost Structure and Prize Allocation Rules

We study experimentally the effects of cost structure and prize allocation rules on the performance of rent-seeking contests. Most previous studies use a lottery prize rule and linear cost, and find both overdissipation relative to Nash equilibrium prediction and significant variation in individual subject efforts. In a 2 2 design, we investigate the effects of sharing the prize proportionally and of a convex cost function, while holding fixed the Nash equilibrium prediction for effort. We find that the share rule results in average effort closer to the Nash prediction, lower variation in individual efforts, and convergence of the distribution of individual efforts towards Nash over time. Combining the share rule with a convex cost function further enhances these results. Our findings indicate that a significant amount of subjects’ non-equilibrium behavior in contests can be explained by features of the experimental design. These results contribute towards design guidelines for contests based on behavioral principles that take into account contest features that may not affect the Nash equilibrium prediction. These lessons suggest design guidelines for future experiments on contests

Focality and Asymmetry in Multi-battle Contests

This article examines behavior in two-person constant-sum Colonel Blotto games in which each player maximizes the expected total value of the battlefields won. A lottery contest success function is employed in each battlefield. Recent experimental research on such games provides only partial support for Nash equilibrium behavior. We hypothesize that the salience of battlefields affects strategic behavior (the salient target hypothesis). We present a controlled test of this hypothesis – against Nash predictions – when the sources of salience come from certain asymmetries in either battlefield values or labels (as in Schelling (1960)). In both cases, subjects over-allocate the resource to the salient battlefields relative to the Nash prediction. However, the effect is stronger with salient values. In the absence of salience, we replicate previous results in the literature supporting the Nash prediction

Precision and Resolution in Spectroscopic Model Fitting

Applied Science

Heat map of correlation matrix for the expression of 11 canonical Hh-pathway component genes in TCGA-GBM (N = 149, significant cut-off |r|>0.17, MTC with FDR 0.1).

<p>Heat map of correlation matrix for the expression of 11 canonical Hh-pathway component genes in TCGA-GBM (N = 149, significant cut-off |r|>0.17, MTC with FDR 0.1).</p

Log scale distribution of GLI1 mRNA expression in a) already published MB cases, along with 1 new case of MB from our repository b) distribution of GLI1 mRNA expression (RNA-Seq data) of the TCGA-GBM sub-cohort (N = 149), c) distribution of GLI1 mRNA expression in NIBMG-GBM cases (N = 19), d) distribution of GLI1 mRNA expression in GBM patient-derived early passage neurospheres (N = 6) and e) comparison of median GLI1 mRNA expression levels of high-Hh-MB (N = 13), low-Hh-MB (N-44), NIBMG-GBM (N = 19) and GBM patient-derived neurospheres (N = 6).

<p>Log scale distribution of GLI1 mRNA expression in a) already published MB cases, along with 1 new case of MB from our repository b) distribution of GLI1 mRNA expression (RNA-Seq data) of the TCGA-GBM sub-cohort (N = 149), c) distribution of GLI1 mRNA expression in NIBMG-GBM cases (N = 19), d) distribution of GLI1 mRNA expression in GBM patient-derived early passage neurospheres (N = 6) and e) comparison of median GLI1 mRNA expression levels of high-Hh-MB (N = 13), low-Hh-MB (N-44), NIBMG-GBM (N = 19) and GBM patient-derived neurospheres (N = 6).</p

A, cell cycle arrest in GBM neurospheres with vismodegib treatment <i>in vitro</i> a) A49910, b), B0027, c) B0043, d) B0051 and e) M45481.

<p><b>B</b>, Number of apoptotic cells (annexin V positive) in GBM neurospheres treated either with DMSO or with 50 μM vismodegib.</p