Social Learning about Consumption
Isabelle Salle () and
Pascal Seppecher ()
No 2013-18, GREDEG Working Papers from Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France
This paper applies a social learning model to the optimal consumption rule of Allen & Carroll (2001), and delivers convincing convergence dynamics towards the optimal rule. These findings constitute a significant improvement regarding previous results in the literature, both in terms of speed of convergence and parsimony of the learning model. The learning model exhibits several appealing features: it is frugal, easy to apply to a range of learning objectives, requires few procedures and little information. Particular care is given to behavioural interpretation of the modelling assumptions in light of evidence from the fields of psychology and social science. Our results highlight the need to depart from the genetic metaphor, and account for intentional decision-making, based on agents’ relative performances. By contrast, we show that convergence is strongly hindered by exact imitation processes, or random exploration mechanisms, which are usually assumed when modelling social learning behaviour. Our results suggest a method for modelling bounded rationality, which could be tested most interestingly within the framework of a wide range of economic models with adaptive dynamics.
Keywords: learning; bounded rationality; evolutionary algorithms; consumption rule (search for similar items in EconPapers)
JEL-codes: D83 D91 C63 E21 (search for similar items in EconPapers)
Pages: 37 pages
Date: 2013-05, Revised 2013-09
New Economics Papers: this item is included in nep-cbe, nep-cmp and nep-evo
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http://www.gredeg.cnrs.fr/working-papers/GREDEG-WP-2013-18.pdf Revised version, 2013 (application/pdf)
Journal Article: SOCIAL LEARNING ABOUT CONSUMPTION (2016)
Working Paper: Social Learning about Consumption (2016)
Working Paper: Social Learning about Consumption (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:gre:wpaper:2013-18
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