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The Law of Large Demand for Information

Giuseppe Moscarini and Lones Smith
Econometrica
Vol. 70, No. 6 (Nov., 2002), pp. 2351-2366
Published by: The Econometric Society
Stable URL: http://www.jstor.org/stable/3081989
Page Count: 16
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The Law of Large Demand for Information
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Abstract

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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