Abstract
Abstract
Thresholds change the value of risk. A firm just below a solvency cutoff, a worker just short of a promotion, or a project just outside a funding line might benefit from variance that allows them to cross the threshold; conversely, the same variance could be detrimental to an agent already above the threshold. This paper investigates this intuition using a behavioral agent-based model where heterogeneous agents choose between risky options, are ranked, and are replaced by noisy copies of agents who clear the threshold. The model design isolates the effect of the number of agents falling below the cutoff from the impact of how strongly a failure changes the population. In the context of evolving competition, a simple below/above-threshold switch outperforms fixed risk behavior. The addition of time creates a second, larger layer of benefits, while the distance to the cutoff adds a smaller gain concentrated under intermediate cutoff pressure. This hierarchy holds for fixed-composition and auxiliary panels, even when employing alternative threshold rules, weaker information, matched turnover, optimized fixed baselines, and placebo state variables. At the most severe cutoff, the influence of extra state information approaches parity. This comparison serves to identify the conditions under which adaptive risk heuristics offer a competitive advantage in threshold selection, versus when the basic below/above switch suffices.
JEL Classification: C63, D81, C73, D91