学习模型中的稳定性和均衡选择:注意事项

IF 2.9 4区 经济学 Q2 BUSINESS, FINANCE Federal Reserve Bank of St Louis Review Pub Date : 2021-10-01 DOI:10.20955/r.103.477-88
YiLi Chien, In-Koo Cho, B. Ravikumar
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引用次数: 0

摘要

相对于理性期望模型,学习模型提供了一种期望形成理论,其中代理使用观察到的数据和学习规则。考虑到在理性预期下存在多重均衡的可能性,学习文献通常以稳定性作为选择均衡的标准。本文以货币经济为例,说明基于稳定性的均衡选择对学习规则的规格很敏感。稳定性准则选择了质量上不同的均衡,即使学习规范的差异很小。
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Stability and Equilibrium Selection in Learning Models: A Note of Caution
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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