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The Normality Assumption in Coordination Games with Flexible Information Acquisition

Rigos, Alexandros LU (2018) In Working Papers
Abstract
Many economic models assume that random variables follow normal (Gaussian) distributions. Yet, real-world variables may be non-normally distributed. How sensitive are these models’ predictions to distribution misspecifications? This paper addresses the question in the context of linear-quadratic beauty contests played by rationally inattentive players. It breaks with the assumption that the (common prior) distribution of the fundamental be Gaussian and provides a characterization of the class of equilibria in continuous strategies. The characterization is used to show that small departures from normality can lead to distributions of the equilibrium average action that are qualitatively different from those of Gaussian models. Numerical... (More)
Many economic models assume that random variables follow normal (Gaussian) distributions. Yet, real-world variables may be non-normally distributed. How sensitive are these models’ predictions to distribution misspecifications? This paper addresses the question in the context of linear-quadratic beauty contests played by rationally inattentive players. It breaks with the assumption that the (common prior) distribution of the fundamental be Gaussian and provides a characterization of the class of equilibria in continuous strategies. The characterization is used to show that small departures from normality can lead to distributions of the equilibrium average action that are qualitatively different from those of Gaussian models. Numerical results show that the rate at which an analyst’s errors in determining the fundamental’s distribution are amplified in her prediction is higher when the true prior is non-Gaussian than when it is an equally-misspecified Gaussian. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Working paper/Preprint
publication status
published
subject
keywords
Coordination games, Beauty-contest, Flexible information acquisition, Rational inattention, Error amplification, Misspecified priors, C72, D83
in
Working Papers
issue
2018:30
pages
52 pages
language
English
LU publication?
yes
id
01e76a0f-d026-47b1-9da5-7a71df61d81f
date added to LUP
2018-11-12 12:33:07
date last changed
2025-04-04 14:37:55
@misc{01e76a0f-d026-47b1-9da5-7a71df61d81f,
  abstract     = {{Many economic models assume that random variables follow normal (Gaussian) distributions. Yet, real-world variables may be non-normally distributed. How sensitive are these models’ predictions to distribution misspecifications? This paper addresses the question in the context of linear-quadratic beauty contests played by rationally inattentive players. It breaks with the assumption that the (common prior) distribution of the fundamental be Gaussian and provides a characterization of the class of equilibria in continuous strategies. The characterization is used to show that small departures from normality can lead to distributions of the equilibrium average action that are qualitatively different from those of Gaussian models. Numerical results show that the rate at which an analyst’s errors in determining the fundamental’s distribution are amplified in her prediction is higher when the true prior is non-Gaussian than when it is an equally-misspecified Gaussian.}},
  author       = {{Rigos, Alexandros}},
  keywords     = {{Coordination games; Beauty-contest; Flexible information acquisition; Rational inattention; Error amplification; Misspecified priors; C72; D83}},
  language     = {{eng}},
  note         = {{Working Paper}},
  number       = {{2018:30}},
  series       = {{Working Papers}},
  title        = {{The Normality Assumption in Coordination Games with Flexible Information Acquisition}},
  url          = {{https://lup.lub.lu.se/search/files/199643228/WP18_30.pdf}},
  year         = {{2018}},
}