The effects of payoff magnitude and heterogeneity on behavior in 2×2 games with unique mixed strategy equilibria

Abstract

The Logit version of Quantal Response Equilibrium predicts that equilibrium behav ior in games will vary systematically with payoff magnitudes, if all other factors are held constant (including the Nash equilibria of the game). We· explore this in the context of a set of asymmetric 2x2 games with unique totally mixed strategy equilibria. The data provide little support for the payoff magnitude predictions of the Logit Equilibrium model. \Ne extend the theoretical Quantal Response Equilibrium model to allow for het erogeneity, and find that the data fit the heterogeneous version of the theory significantly better.

Risk averse behavior in generalized matching pennies games

“…Adaptive learning models have been used to study the time series of choices in matching pennies games (Mookherjee and Sopher, 1997;Erev and Roth, 1998;and Camerer and Ho, 2000). Moreover, there is evidence of heterogeneity across subjects (McKelvey, Palfrey, and Weber, 2000).…”

“…However, follow-up experiments (McKelvey, Palfrey, and Weber, 2000;Goeree and Holt, 2001) have revealed discrepancies, which suggest that other factors may play a role. For instance, when individuals are risk averse or have a "social preference" component to their utility function (Bolton, 1998;Camerer, 1997), equilibrium predictions change.…”

Heterogeneous quantal response equilibrium and cognitive hierarchies

“…Players in these models are typically modelled as using quantal responses instead of best responses. 14 …”

Exploration vs Exploitation, Impulse Balance Equilibrium, and a Specification Test for the El Farol Bar Problem

“…assumption of QRE. Unlike Golman's normative approach that is suited to QRE and that generates most useful predictions for the QRE analysis of binary-choice 2 See McKelvey, Palfrey and Weber (2000) and Weizsäcker (2003) for earlier investigations of QRE models with non-homogenous agents. Rogers et al (2009) also consider a QRE model with subjective beliefs, i.e., where the distributions of others' traits are not common knowledge but each player believes that the others' traits are i.i.d.…”

“…The motivation to analyse a game with 'many' (10) agents is to best allow the structural assessment of agents' homogeneity. Controlling the payoff levels allows to check whether entry is increasing in payoffs, as expected by McKelvey, Palfrey and Weber (2000) and Goeree, Holt and Palfrey (2005), whereas controlling payoff structures aims at providing a broader picture of the problem at hand.…”