Learning cycles in Bertrand competition with differentiated commodities and competing learning rules
Mikhail Anufriev (),
Dávid Kopányi () and
Jan Tuinstra ()
Journal of Economic Dynamics and Control, 2013, vol. 37, issue 12, 2562-2581
This paper stresses the importance of heterogeneity in learning. We consider a Bertrand oligopoly with firms using either least squares learning or gradient learning for determining the price. We demonstrate that convergence properties of the rules are strongly affected by heterogeneity. In particular, gradient learning may become unstable as the number of gradient learners increases. Endogenous choice between the learning rules may induce cyclical switching. Stable gradient learning gives higher average profit than least squares learning, making firms switch to gradient learning. This can destabilize gradient learning which, because of decreasing profits, makes firms switch back to least squares learning.
Keywords: Bertrand competition; Heterogeneous agents; Least squares learning; Gradient learning; Endogenous switching (search for similar items in EconPapers)
JEL-codes: C63 C72 D43 (search for similar items in EconPapers)
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Working Paper: Learning Cycles in Bertrand Competition with Differentiated Commodities and Competing Learning Rules (2013)
Working Paper: Learning Cycles in Bertrand Competition with Differentiated Commodities and Competing Learning Rules (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:dyncon:v:37:y:2013:i:12:p:2562-2581
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