Informative Absence Under Information Asymmetry

Abstract A recurring difficulty in evaluation under uncertainty is that what is missing sometimes matters more than what is presented. Several research traditions—disclosure economics, audit methodology, intelligence analysis—have each developed ways of reasoning about absent information, but they rarely speak to each other. This paper identifies a shared cognitive structure across these fields and formalizes it as the Expectation–Detection–Inference (EDI) model of informative absence. The EDI model formalizes absence-based inference as a three-stage cognitive process: expectation formation, absence detection, and inference validation. The central claim is that absence-based inference is reliable only when three conditions jointly hold: the evaluator's expectation is defensible, the counterpart can reasonably be assumed to share that expectation, and the absence is externally verifiable rather than merely salient. These conditions are rarely met outside formal disclosure settings. The paper specifies boundary conditions under which the EDI structure is more versus less likely to produce valid inferences, and includes a case where a well-grounded absence signal proved misleading. The contribution is a structural clarification of a recurring cognitive pattern that the three literatures each rely on but none has explicitly named. The model is offered as a provisional, exploratory structure, subject to revision or rejection in light of further evidence. Keywords: informative absence, expectation formation, voluntary disclosure, completeness assertion, information asymmetry, cognitive bias JEL Classification: D81, D82, G32, M10