Agent-Based Modeling of a Non-tâtonnement Process for the Scarf Economy: The Role of Learning
學年 106
學期 1
出版（發表）日期 2017-08-04
作品名稱 Agent-Based Modeling of a Non-tâtonnement Process for the Scarf Economy: The Role of Learning
作品名稱（其他語言）
著者 Shu-Heng Chen; Bin-Tzong Chie; Ying-Fang Kao; Ragupathy Venkatachalam
單位
出版者
著錄名稱、卷期、頁數 Computational Economics 54, p.305-341
摘要 In this paper, we propose a meta-learning model to hierarchically integrate individual learning and social learning schemes. This meta-learning model is incorporated into an agent-based model to show that Herbert Scarf’s famous counterexample on Walrasian stability can become stable in some cases under a non-tâtonnement process when both learning schemes are involved, a result previously obtained by Herbert Gintis. However, we find that the stability of the competitive equilibrium depends on how individuals learn—whether they are innovators (individual learners) or imitators (social learners), and their switching frequency (mobility) between the two. We show that this endogenous behavior, apart from the initial population of innovators, is mainly determined by the agents’ intensity of choice. This study grounds the Walrasian competitive equilibrium based on the view of a balanced resource allocation between exploitation and exploration. This balance, achieved through a meta-learning model, is shown to be underpinned by a behavioral/psychological characteristic.
關鍵字 Non-tâtonnement process;Coordination;Agent-based modeling;Learning
語言 en_US
ISSN 0927-7099
期刊性質 國外
收錄於 SSCI
產學合作
通訊作者
審稿制度 是
國別 CHE
公開徵稿
出版型式 ,電子版,紙本
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