Behavioral learning equilibria

• 成果类型: Article
• 署名作者: Hommes, Cars; Zhu, Mei
• 署名单位: University of Amsterdam; Tinbergen Institute; Shanghai University of Finance & Economics; Shanghai University of Finance & Economics
• 刊物名称: JOURNAL OF ECONOMIC THEORY
• ISSN/ISSBN: 0022-0531
• DOI: 10.1016/j.jet.2013.09.002
• 发表日期: 2014
• 页码: 778-814
• 关键词: Bounded rationality; Stochastic consistent expectations equilibrium; adaptive learning; excess volatility; Inflation persistence

摘要

We propose behavioral learning equilibria, where boundedly rational agents learn to use a simple univariate linear forecasting rule with correctly specified unconditional mean and first-order autocorrelation. In the long run, agents learn the best univariate linear forecasting rule, without fully recognizing the more complex structure of the economy. An important feature of behavioral learning equilibria is simplicity and parsimony, which makes coordination of individual expectations on such an aggregate outcome more likely. In a first application, an asset pricing model driven by AR(1) dividends, a unique behavioral learning equilibrium exists characterized by high persistence and excess volatility, and it is stable under learning. In a second application, the New Keynesian Phillips curve, multiple equilibria coexist, learning exhibits path dependence and inflation may switch between low and high persistence regimes. (C) 2013 Elsevier Inc. All rights reserved.