Learning and shifts in long-run productivity growth

被引:55
|
作者
Edge, Rochelle M. [2 ]
Laubach, Thomas [2 ]
Williams, John C. [1 ]
机构
[1] Fed Reserve Bank San Francisco, San Francisco, CA 94105 USA
[2] Fed Reserve Board, Washington, DC 20551 USA
关键词
DGE models; Kalman filter; real-time data; productivity shocks;
D O I
10.1016/j.jmoneco.2007.01.003
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
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.
引用
收藏
页码:2421 / 2438
页数:18
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