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  • 标题:Stability and Equilibrium Selection in Learning Models: A Note of Caution
  • 本地全文:下载
  • 作者:YiLi Chien ; YiLi Chien ; In-Koo Cho
  • 期刊名称:Federal Reserve Bank of St. Louis Review
  • 印刷版ISSN:0014-9187
  • 出版年度:2021
  • 卷号:103
  • 期号:4
  • DOI:10.20955/r.103.477-88
  • 语种:English
  • 出版社:Federal Reserve Bank of St. Louis
  • 摘要:Relative to rational expectations models, learning models provide a theory of expectation formation where agents use observed data and a learning rule. Given the possibility of multiple equilibria under rational expectations, the learning literature often uses stability as a criterion to select an equilibrium. This article uses a monetary economy to illustrate that equilibrium selection based on stability is sensitive to specifications of the learning rule. The stability criterion selects qualitatively different equilibria even when the differences in learning specifications are small.
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