| Abstract: |
This paper develops a state-dependent version of Prospect Theory in which loss
aversion, reference adaptation, and probability weighting vary with resource
buffers, attention constraints, and boundary-risk context. Prospect Theory is
usually treated as a descriptive account of deviations from expected-utility
rationality. This paper proposes a finite-capacity bridge model: bounded
agents operating under scarcity, limited attention, finite memory, and finite
update capacity should exhibit state-dependent risk preferences. The model
introduces a vector-valued resource buffer, perceived distance to a constraint
threshold, event-class-dependent probability weighting, and a nudge-bandwidth
model. It predicts that loss aversion should rise under scarcity and downside
exposure, reference baselines should adapt more slowly under depletion, and
probability weighting should become more distorted for low-capacity agents and
boundary-relevant rare events. The paper includes deterministic synthetic
simulations and a replication package, but does not fit human-subject data. It
is intended as a theoretical working paper and empirical identification
framework for future tests of state-dependent Prospect Theory. |