Learning and shifts in long-run productivity growth

• 成果类型: Article
• 署名作者: Edge, Rochelle M.; Laubach, Thomas; Williams, John C.
• 署名单位: Federal Reserve System - USA; Federal Reserve Bank - San Francisco; Federal Reserve System - USA; Federal Reserve System Board of Governors
• 刊物名称: JOURNAL OF MONETARY ECONOMICS
• ISSN/ISSBN: 0304-3932
• DOI: 10.1016/j.jmoneco.2007.01.003
• 发表日期: 2007
• 页码: 2421-2438
• 关键词: DGE models; Kalman filter; Real-time data; productivity shocks

摘要

An extensive literature has analyzed the macroeconomic effects of shocks to the level of aggregate productivity; however, there has been little corresponding research on sustained shifts in the growth rate of productivity. In this paper, we examine the effects of shocks to productivity growth in a dynamic general equilibrium model where agents do not directly observe whether shocks are transitory or persistent. We show that an estimated Kalman filter model using real-time data describes economists' long-run productivity growth forecasts in the United States extremely well and that filtering has profound implications for the macroeconomic effects of shifts in productivity growth. Published by Elsevier B.V.