Economics Dictionary of ArgumentsHome
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| Terminology: This section explains special features of the language used by the individual authors. _____________Annotation: The above characterizations of concepts are neither definitions nor exhausting presentations of problems related to them. Instead, they are intended to give a short introduction to the contributions below. – Lexicon of Arguments. | |||
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Rachel E. Kranton on Terminology - Dictionary of Arguments
Kranton I 424 Terminology/Bloch/Demange/Kranton: Unbiased agents: (set U): prefer the outcome to match the state of nature. Biased agents: (set B) prefer outcome x= 1 to be implemented, regardless of the state of nature. Full Communication Equilibrium/FCE: (…) a full communication equilibrium (FCE) [is a state], where all biased and unbiased agents transmit messages and, therefore, spread possibly false rumors. They do so because there is a sufficiently large probability the rumor is true. The equilibrium conditions rely on the number and distribution of biased and unbiased agents in the population. In a network, for any agent, the set of possible senders of a message must contain sufficiently few biased agents. Maximal Communication Equilibrium/MCE/Bloch/Demange/Kranton: [If the condition for the] full communication [fails], there is an equilibrium, called maximal communication equilibrium (MCE), in which communication is maximized: In any equilibrium, information flows on an edge only if it flows in this MCE. A main feature of this equilibrium is that information can flow from one part of the network to another but not in the reverse direction. Unbiased agents maintain the credibility of messages by blocking those that come from a part of the network that contains too many biased agents Kranton I 432 [thus] limiting the influence of localized biased agents. Kranton I 424 Agents have a common prior belief that θ = 1 with probability π. We assume π < 1/2 so that agents initially believe the true state is 0 with higher probability. With this initial prior, agents are particularly interested in credible information that the outcome is 1. True message: M(s) = s Untrue message: M(s)≠ s Kranton I 424 Ø = The empty message ∅ corresponds to the situation where the recipient chooses not to create any message. Kranton I 422 Network Homophily: (…) homophily—the tendency for biased agents to cluster together in the same part of the social network—has a nonmonotonic influence on the spread of rumors. When homophily is low, biased agents are dispersed and do not hamper communication through the network; when homophily is high, biased agents are clustered in some areas of the network, and rumors spread without difficulties in the other areas, which only contain unbiased agents. Communication is reduced when homophily reaches intermediate levels, and small islands of biased agents can be found throughout the network. Kranton I 427 To indicate the direction of any communication, let (i, j ) denote the directed link from i to j, (j, i) denote the directed link from j to i, and let G denote the set of all directed links. G and individual agents’ types are common knowledge. Cheap talk: communication without influencing the result of a game. Francis Bloch, Gabrielle Demange & Rachel Kranton, 2018. "Rumors And Social Networks," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(2), pages 421-448._____________Explanation of symbols: Roman numerals indicate the source, arabic numerals indicate the page number. The corresponding books are indicated on the right hand side. ((s)…): Comment by the sender of the contribution. Translations: Dictionary of Arguments The note [Concept/Author], [Author1]Vs[Author2] or [Author]Vs[term] resp. "problem:"/"solution:", "old:"/"new:" and "thesis:" is an addition from the Dictionary of Arguments. If a German edition is specified, the page numbers refer to this edition. |
Kranton I Rachel E. Kranton Francis Bloch Gabrielle Demange, Rumors And Social Networks 2018 Kranton II Rachel E. Kranton George A. Akerlof Identity Economics: How Our Identities Shape Our Work, Wages, and Well-Being Princeton 2011 |
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> Counter arguments against Kranton
> Counter arguments in relation to Terminology
