Instability of sunspot equilibria in real business cycle models under adaptive learning

• 成果类型: Article
• 署名作者: Duffy, John; Xiao, Wei
• 署名单位: Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; University of Louisiana System; University of New Orleans
• 刊物名称: JOURNAL OF MONETARY ECONOMICS
• ISSN/ISSBN: 0304-3932
• DOI: 10.1016/j.jmoneco.2005.11.004
• 发表日期: 2007
• 页码: 879-903
• 关键词: real business cycle models; indeterminacy; sunspots; expectations; learning; STABILITY

摘要

We provide conditions under which a general, reduced-form class of real business cycle (RBC) models has rational expectations equilibria that are both indeterminate and stable under adaptive learning. Indeterminacy of equilibrium allows for the possibility that non-fundamental sunspot variable realizations can be used to drive the model, and several researchers have offered calibrated structural models where sunspot shocks play such a role. However, we show that the structural restrictions researchers have adopted lead to reduced-form systems that are always unstable under adaptive learning dynamics, thus calling into question the plausibility of these sunspot-driven RBC models. (c) 2006 Elsevier B.V. All rights reserved.