MODELING MODEL UNCERTAINTY

• 成果类型: Article
• 署名作者: Smets, Frank; Wouters, Raf
• 署名单位: European Central Bank; European Central Bank; National Bank of Belgium
• 刊物名称: JOURNAL OF THE EUROPEAN ECONOMIC ASSOCIATION
• ISSN/ISSBN: 1542-4766
• DOI: 10.1162/154247603770383415
• 发表日期: 2003
• 页码: 1123-1175
• 关键词: optimal monetary-policy; technology shocks; bayesian-approach; habit formation; business-cycle; interest-rates; prices; INVESTMENT

摘要

Recently there has been a great deal of interest in studying monetary policy under model uncertainty. We point out that different assumptions about the uncertainty may result in drastically different robust policy recommendations. Therefore, we develop new methods to analyze uncertainty about the parameters of a model, the lag specification, the serial correlation of shocks, and the effects of real-time data in one coherent structure. We consider both parametric and nonparametric specifications of this structure and use them to estimate the uncertainty in a small model of the U.S. economy. We then use our estimates to compute robust Bayesian and minimax monetary policy rules, which are designed to perform well in the face of uncertainty. Our results suggest that the aggressiveness recently found in robust policy rules is likely to be caused by overemphasizing uncertainty about economic dynamics at low frequencies. (JEL: E52, C32, D81)