Journal
ECONOMETRICA
Volume 70, Issue 6, Pages 2351-2366Publisher
BLACKWELL PUBL LTD
DOI: 10.1111/1468-0262.00378
Keywords
demand for information; logarithmic demand; value of information; Bayesian decision theory; comparison of experiments; large deviation theory
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An unresolved problem in Bayesian decision theory is how to value and price information., This paper resolves both problems 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, finite-action models. Computing the marginal value of an additional signal, we find it is eventually exponentially falling in quantity, and higher for lower quality signals. We provide a precise formula for the information demand, valid at low prices: asymptotically a constant times the log price, and falling in the signal quality for a given price.
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