Learning cycles in Bertrand competition with differentiated commodities and competing learning rules

Anufriev, M; Kopányi, D; Tuinstra, J

Learning cycles in Bertrand competition with differentiated commodities and competing learning rules

Anufriev, M

Kopányi, D Tuinstra, J

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Publication Type:: Journal Article
Citation:: Journal of Economic Dynamics and Control, 2013, 37 (12), pp. 2562 - 2581
Issue Date:: 2013-12-01

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Field	Value	Language
dc.contributor.author	Anufriev, M https://orcid.org/0000-0002-1842-6814	en_US
dc.contributor.author	Kopányi, D	en_US
dc.contributor.author	Tuinstra, J	en_US
dc.date.issued	2013-12-01	en_US
dc.identifier.citation	Journal of Economic Dynamics and Control, 2013, 37 (12), pp. 2562 - 2581	en_US
dc.identifier.issn	0165-1889	en_US
dc.identifier.uri	http://hdl.handle.net/10453/27704
dc.description.abstract	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. © 2013 Elsevier B.V.	en_US
dc.relation.ispartof	Journal of Economic Dynamics and Control	en_US
dc.relation.isbasedon	10.1016/j.jedc.2013.06.010	en_US
dc.subject.classification	Economics	en_US
dc.title	Learning cycles in Bertrand competition with differentiated commodities and competing learning rules	en_US
dc.type	Journal Article
utslib.citation.volume	12	en_US
utslib.citation.volume	37	en_US
utslib.for	1401 Economic Theory	en_US
utslib.for	1402 Applied Economics	en_US
utslib.for	1502 Banking, Finance and Investment	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Economics Discipline
utslib.copyright.status	closed_access
pubs.issue	12	en_US
pubs.publication-status	Published	en_US
pubs.volume	37	en_US

Abstract:

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. © 2013 Elsevier B.V.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/27704