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Interpreted and generated signals

Author

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  • Hong, Lu
  • Page, Scott

Abstract

Private information is typically modeled as signals. A joint probability distribution captures relationships between signals and between signals and relevant variables. In this paper, we define and contrast two types of signals: generated and interpreted. We demonstrate that even though the standard assumption of conditional independence is a reasonable benchmark assumption for generated signals, it imposes a specific, and unlikely structure on interpreted signals. We also show that independent interpreted signals are negatively correlated in their correctness, but generated signals can be independent. Our findings may limit the contexts in which many models of information aggregation and strategic choices in auctions, markets, and voting apply.

Suggested Citation

  • Hong, Lu & Page, Scott, 2009. "Interpreted and generated signals," Journal of Economic Theory, Elsevier, vol. 144(5), pages 2174-2196, September.
  • Handle: RePEc:eee:jetheo:v:144:y:2009:i:5:p:2174-2196
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    References listed on IDEAS

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    5. Al-Najjar, Nabil I. & Casadesus-Masanell, Ramon & Ozdenoren, Emre, 2003. "Probabilistic representation of complexity," Journal of Economic Theory, Elsevier, vol. 111(1), pages 49-87, July.
    6. Holland, John H & Miller, John H, 1991. "Artificial Adaptive Agents in Economic Theory," American Economic Review, American Economic Association, vol. 81(2), pages 365-371, May.
    7. Hong, Lu & Page, Scott E., 2001. "Problem Solving by Heterogeneous Agents," Journal of Economic Theory, Elsevier, vol. 97(1), pages 123-163, March.
    8. Paul Klemperer, 2004. "Auctions: Theory and Practice," Online economics textbooks, SUNY-Oswego, Department of Economics, number auction1.
    9. Paul Klemperer, 2004. "Introduction to Auctions: Theory and Practice," Introductory Chapters,in: Auctions: Theory and Practice Princeton University Press.
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    Cited by:

    1. Oktay Sürücü, 2014. "Lying for the Greater Good: Bounded Rationality in a Team," The International Journal of Economic Behavior - IJEB, Faculty of Business and Administration, University of Bucharest, vol. 4(1), pages 151-163.
    2. Economo, Evan & Hong, Lu & Page, Scott E., 2016. "Social structure, endogenous diversity, and collective accuracy," Journal of Economic Behavior & Organization, Elsevier, vol. 125(C), pages 212-231.
    3. Ernst, Philip & Pemantle, Robin & Satopää, Ville & Ungar, Lyle, 2016. "Bayesian aggregation of two forecasts in the partial information framework," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 170-180.
    4. Nicolas Roux & Joel Sobel, 2015. "Group Polarization in a Model of Information Aggregation," American Economic Journal: Microeconomics, American Economic Association, vol. 7(4), pages 202-232, November.
    5. repec:but:manage:v:4:y:2014:i:1:p:151-163 is not listed on IDEAS

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