Interpreted and generated signals
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.
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- Paul Klemperer, 2004.
"Auctions: Theory and Practice,"
2004-W09, Economics Group, Nuffield College, University of Oxford.
- Fryer Roland & Jackson Matthew O., 2008. "A Categorical Model of Cognition and Biased Decision Making," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 8(1), pages 1-44, February.
- Enriqueta Aragones & Itzhak Gilboa & Andrew Postlewaite & David Schmeidler, 2004.
Cowles Foundation Discussion Papers
1491, Cowles Foundation for Research in Economics, Yale University.
- Enriqueta Aragones & Itzhak Gilboa & Andrew Postlewaite & David Schmeidler, 2003. "Fact-Free Learning," PIER Working Paper Archive 05-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Dec 2004.
- Enriqueta Aragones & Itzhak Gilboa & Andrew Postlewaite & David Schmeidler, 2003. "Fact-Free Learning," PIER Working Paper Archive 03-023, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Itzhak Gilboa & Enriqueta Aragones & Andrew Postlewaite & David Schmeidler, 2005. "Fact-Free Learning," Post-Print hal-00481243, HAL.
- Paul Klemperer, 2004.
"Introduction to Auctions: Theory and Practice
[Auctions: Theory and Practice]," Introductory Chapters, Princeton University Press.
- Timothy Feddersen & Wolfgang Pesendorfer, 1994.
"Voting Behavior and Information Aggregation in Elections with Private Information,"
1117, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
- Timothy Feddersen & Wolfgang Pesendorfer, 1997. "Voting Behavior and Information Aggregation in Elections with Private Information," Econometrica, Econometric Society, vol. 65(5), pages 1029-1058, September.
- Timothy Feddersen & Wolfgang Pesendorfer, 1997. "Voting Behavior and Information Aggregation in Elections With Private Information," Levine's Working Paper Archive 1560, David K. Levine.
- 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.
- Kenneth Judd & Scott E. Page, 2004. "Computational Public Economics," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 6(2), pages 195-202, 05.
- Hong, Lu & Page, Scott E., 2001. "Problem Solving by Heterogeneous Agents," Journal of Economic Theory, Elsevier, vol. 97(1), pages 123-163, March.
- Holland, John H & Miller, John H, 1991. "Artificial Adaptive Agents in Economic Theory," American Economic Review, American Economic Association, vol. 81(2), pages 365-71, May.
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