The Law of Large Demand for Information
AbstractAn 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.
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Bibliographic InfoArticle provided by Econometric Society in its journal Econometrica.
Volume (Year): 70 (2002)
Issue (Month): 6 (November)
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- Jussi Keppo & Giuseppe Moscarini & Lones Smith, 2005.
"The Demand for Information: More Heat than Light,"
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- Stefano Ficco, 2004. "Information Overload in Monopsony Markets," Tinbergen Institute Discussion Papers 04-082/1, Tinbergen Institute.
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- Duffie, Darrell & Malamud, Semyon & Manso, Gustavo, 2010.
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- Duffie, Darrell & Malamud, Semyon & Manso, Gustavo, 2009. "The Relative Contributions of Private Information Sharing and Public Information Releases to Information Aggregation," Research Papers 2023, Stanford University, Graduate School of Business.
- Darrell DUFFIE & Semyon MALAMUD & Gustavo MANSO, . "The Relative Contributions of Private Information Sharing and Public Information Releases to Information Aggregation," Swiss Finance Institute Research Paper Series 09-33, Swiss Finance Institute.
- Vlastakis, Nikolaos & Markellos, Raphael N., 2012. "Information demand and stock market volatility," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1808-1821.
- Moscarini, Giuseppe, 2004. "Limited information capacity as a source of inertia," Journal of Economic Dynamics and Control, Elsevier, vol. 28(10), pages 2003-2035, September.
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