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Quantal Response EquilibriumA Stochastic Theory of Games$
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Jacob K. Goeree, Charles A. Holt, and Thomas R. Palfrey

Print publication date: 2016

Print ISBN-13: 9780691124230

Published to Princeton Scholarship Online: January 2018

DOI: 10.23943/princeton/9780691124230.001.0001

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QRE as a Structural Model for Estimation

QRE as a Structural Model for Estimation

Chapter:
(p.141) 6 QRE as a Structural Model for Estimation
Source:
Quantal Response Equilibrium
Author(s):

Jacob K. Goeree

Charles A. Holt

Thomas R. Palfrey

Publisher:
Princeton University Press
DOI:10.23943/princeton/9780691124230.003.0006

This chapter discusses the use of maximum-likelihood methods to estimate the precision and other parameters of interest, for example, those that capture risk aversion, inequity aversion, altruism, etc. It also considers “noisy Nash” and other (nonequilibrium) error specifications. This estimation can be done with any standard statistical package, for example, GAUSS, Mathematica, R, and MATLAB. The sample programs contained in this chapter are specified in a manner that is intended to clarify the underlying structure of the quantal response equilibrium (QRE) analysis and to illustrate how to use numerical methods to calculate QRE. The chapter is organized around a series of applications, each based on a laboratory experiment that presented interesting estimation issues.

Keywords:   maximum-likelihood methods, quantal response equilibrium, QRE, Nash equilibrium, risk aversion, inequity aversion, altruism, estimation

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