From marketing and advertising to political campaigning and court proceedings, contending parties expend resources to persuade an audience of the correctness of their view. We examine how the probability of persuading the audience depends on the resources expended by the parties, so that persuasion can be modelled as a contest. We use a Bayesian approach whereby the audience makes inferences solely based on the evidence presented to them. The evidence is produced by the resources expended by the contending parties. We find conditions on evidence production and likelihood functions that yield the well-known additive contest success functions, including the logit function as well as the one used in all-pay auctions. We also find conditions that produce a “difference” functional form. In all cases, there are three main determinants of which side the audience chooses: (i) the truth and other objective parameters of the environment; (ii) the biases of the audience as distilled in their priors and the likelihood function employed ; and (iii) the resources expended by the parties interested in persuading the audience.
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Paper provided by CESifo GmbH in its series CESifo Working Paper Series with number
CESifo Working Paper No. 2160.
Stergios Skaperdas & Samarth Vaidya, 2007.
"Persuasion as a Contest,"
Working Papers
070809, University of California-Irvine, Department of Economics.
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References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Sendhil Mullainathan & Joshua Schwartzstein & Andrei Shleifer, 2006.
"Coarse Thinking and Persuasion,"
NBER Working Papers
12720, National Bureau of Economic Research, Inc.
[Downloadable!] (restricted)
Other versions:
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.
[Downloadable!]
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.
[Downloadable!]
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