ON PERFECT FORESIGHT MODELS OF A STOCHASTIC WORLD

• 成果类型: Article
• 署名作者: HALIASSOS, M
• 署名单位: University System of Maryland; University of Maryland College Park
• 刊物名称: ECONOMIC JOURNAL
• ISSN/ISSBN: 0013-0133
• DOI: 10.2307/2234626
• 发表日期: 1994
• 页码: 477-491
• 关键词: long-run relationship; interest-rates; optimizing model; UNITED-STATES; inflation

摘要

Long-run analysis is often based on perfect foresight equilibrium relationships arbitrarily augmented to incorporate stochastic shocks. This paper examines whether perfect foresight models admit interpretations as limits of stochastic economies and reflect long-run behaviour and policy effects. It provides a novel interpretation of such models, specifies consistency criteria for long-run analysis, and proposes metrics for model convergence. Analytical and calibration exercises are conducted to show that convergence to perfect foresight need not occur, and even when it occurs, it does not ensure that relationships between long-run averages or low-frequency components are captured by perfect foresight models.