Heterogeneity in Economics

Kirman, Alan

doi:10.1007/s11403-006-0005-8

Cited by 65 publications

(37 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In a large population of agents, we should expect heterogeneity of behavior [12,15]. A population of quantal responders should consist of agents who may have different error rates, or different distributions of payoff noise.…”

Section: Introductionmentioning

confidence: 99%

Quantal response equilibria with heterogeneous agents

Golman

2011

Journal of Economic Theory

View full text Add to dashboard Cite

This paper introduces a model of quantal response equilibrium with heterogeneous agents and demonstrates the existence of a representative agent for such populations.Except in rare cases, the representative agent's noise terms cannot be independently and identically distributed across the set of actions, even if that is assumed for the individual agents. This result demonstrates a fundamental difference between a representative agent and truly heterogeneous quantal responders and suggests that when fitting quantal response specifications to aggregate data from a population of subjects, the noise terms should be allowed to be jointly dependent across actions. Even though this introduces additional degrees of freedom, it makes the model well specified. The representative agent inherits a regular quantal response function from the actual agents, so this model does impose falsifiable restrictions.

show abstract

Section: Introductionmentioning

confidence: 99%

Quantal response equilibria with heterogeneous agents

Golman

2011

Journal of Economic Theory

View full text Add to dashboard Cite

show abstract

“…In a large population of agents, we should expect heterogeneity of behavior (Hommes 2006, Kirman 2006). 8 Camerer and Ho (1999) correctly recognized that individuals may combine diverse basic learning rules.…”

Section: Discussionmentioning

confidence: 99%

Why learning doesn’t add up: equilibrium selection with a composition of learning rules

Golman

2010

Int J Game Theory

View full text Add to dashboard Cite

In this paper, we investigate the aggregate behavior of populations of learning agents. We compare the outcomes in homogenous populations learning in accordance with imitate the best dynamics and with replicator dynamics to outcomes in populations that mix these two learning rules. New outcomes can emerge. In certain games, a linear combination of the two rules almost always attains an equilibrium that homogenous learners almost never locate. Moreover, even when almost all weight is placed on one learning rule, the outcome can differ from homogenous use of that rule.Thus, allowing even an arbitrarily small chance of using an alternative learning style can shift a population to select a different equilibrium.

show abstract

“…But, in a large population of agents, we should expect heterogeneity of behavior (Hommes 2006;Kirman 2006). A population of logit responders (or, more generally, any form of quantal responders) should consist of agents 1 Logit response can also arise in models of players who have to make some effort in order to implement any desired strategy, but who perfectly maximize utility subject to this control cost (Mattsson and Weibull 2002 (Golman 2011).…”

Section: Introductionmentioning

confidence: 99%

Homogeneity bias in models of discrete choice with bounded rationality

Golman¹

2012

Journal of Economic Behavior & Organization

View full text Add to dashboard Cite

Quantal response equilibrium captures bounded rationality in a strategic game by adopting a stochastic model of discrete choice along with the traditional rational expectations framework. We examine the use of a single-agent, homogeneous parametric quantal response model (e.g., logit response) to describe the aggregate behavior of heterogeneous agents sharing the same parametric form for their quantal response functions, but having individual rationality parameters, in a symmetric population game. For any parametric quantal response function arising from a unimodal distribution of exchangeable payoff disturbances, we find that a mis-specified homogeneous rationality parameter will have downward bias. Logit response is one such specification. This result implies that empirical work that disregards heterogeneity underestimates subjects' rationality.

show abstract

Heterogeneity in Economics

Abstract: Heterogeneity, Uniqueness and stability of equilibrium, Adaptation, Learning, Varying expectations, B41, C62, D50, D84, G10,

Cited by 65 publications

References 57 publications

Quantal response equilibria with heterogeneous agents

Quantal response equilibria with heterogeneous agents

Why learning doesn’t add up: equilibrium selection with a composition of learning rules

Homogeneity bias in models of discrete choice with bounded rationality

Contact Info

Product

Resources

About