An unresolved problem in Bayesian decision theory is how to value and price information. This paper resolves both problems by assuming inexpensive information. Building on Large Deviation Theory, we produce a generically complete asymptotic order on samples of i.i.d. signals in finite-state,...

This paper produces a comprehensive theory of the value of Bayesian information and its static demand. Our key insight is to assume 'natural units' corresponding to the sample size of conditionally i.i.d. signals - focusing on the smooth nearby model of the precision of an observation of a...