The Law of Large Demand for Information

Giuseppe Moscarini and Lones Smith

Econometrica, 2002, vol. 70, issue 6, 2351-2366

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. Copyright The Econometric Society 2002.

Date: 2002
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