Comparing Behavioural Models Using Data from Experimental Centipede Games

Georgalos, Konstantinos (2020) Comparing Behavioural Models Using Data from Experimental Centipede Games. Economic Inquiry, 58 (1). pp. 34-48. ISSN 0095-2583

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The centipede game posits one of the most well-known paradoxes of backward induction in the literature of experimental game theory. Given that deviations from the unique subgame perfect Nash equilibrium generates a Pareto improvement, several theoretical models have been employed in order to rationalize this kind of behavior in this social dilemma. The available explanations range from social preferences including fairness, altruism or cooperation motives, errors in playing, inability to perform backward induction or different depths of reasoning. In the present study, we use the Blavatskyy's theoretical contribution, and relax the assumptions of Expected Utility maximization and risk-neutral attitudes, to test an alternative explanation. We compare various probabilistic decision theory models in terms of their descriptive (in-sample) and predictive (out-of-sample fit) performance, using data from experimental centipede games. We find that introducing non-Expected Utility preferences to the Quantal Response Equilibrium model, along with a nonlinear utility function, provides a better explanation compared to alternative specifications such as the Level-k or the Quantal Response Equilibrium model with altruistic motives. (JEL C72, C92, D81, D82).

Item Type:
Journal Article
Journal or Publication Title:
Economic Inquiry
Additional Information:
This is the peer reviewed version of the following article: Georgalos, K. (2019), COMPARING BEHAVIORAL MODELS USING DATA FROM EXPERIMENTAL CENTIPEDE GAMES. Econ Inq. doi:10.1111/ecin.12803 which has been published in final form at This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
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?? business, management and accounting(all)economics and econometrics ??
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Deposited On:
22 Jun 2019 09:12
Last Modified:
25 May 2024 01:32