Information Latency: Theory and Economic Consequences

Abstract

Many economic decisions rely on observations that predate the decision time. This paper introduces information latency, the elapsed time between a decision and the most recent observation of an evolving payoff-relevant state, as a distinct source of imperfect information. Unlike classical sources of information friction, latency generates irreducible uncertainty even with exact observations and rational expectations. For sufficiently regular continuous-time Markov processes, conditional variance increases locally with latency; under the Ornstein-Uhlenbeck benchmark, it increases at a decreasing rate toward a finite bound. Following a rare-state observation, however, uncertainty can peak at an intermediate latency before declining. Neither the average latency nor the average update frequency fully characterizes information quality: the regularity of information arrival matters independently of the mean interval. Under a CARA-normal benchmark, latency-induced uncertainty generates a risk premium. With heterogeneous latency, the lowest-risk-adjusted-cost intermediary wins the business, while competition drives the price toward the second-lowest risk-adjusted cost. In a stylized contract-renewal setting, positive latency can be second-best optimal by limiting costly reclassification when direct contractual commitment is unavailable. The framework applies to credit, insurance, financial markets, and operational decisions.