Heterogeneous learning dynamics and speed of convergence
AbstractIn a simple, forward looking linear stochastic model we investigate the impact of heterogeneity in expectations formation on the speed of convergence of the learning process of agents towards equilibrium. We …nd that even when heterogeneity does not a¤ect learnability in term of its asymptotic outcome, it can still have an important impact on the learnability of an equilibrium in terms of the speed of convergence of learning dynamics.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Economics, The Univeristy of Manchester in its series Centre for Growth and Business Cycle Research Discussion Paper Series with number 148.
Length: 19 pages
Date of creation: 2010
Date of revision:
Contact details of provider:
Postal: Manchester M13 9PL
Phone: (0)161 275 4868
Fax: (0)161 275 4812
Web page: http://www.socialsciences.manchester.ac.uk/subjects/economics/our-research/centre-for-growth-and-business-cycle-research/
More information through EDIRC
Other versions of this item:
- Berardi Michele, 2012. "Heterogeneous Learning Dynamics and Speed of Convergence," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(4), pages 1-20, October.
- C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-09-11 (All new papers)
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Marianne Sensier).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.