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,...

We extend the comparison of experiments in Blackwell (1953) to a strategic setting that both simplifies and expands upon ideas in Gossner (2000). We introduce a partial order on correlating signals, called more strategically informative, and prove that it is equivalent to the partial order more...

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...