动态随机一般均衡
商业周期
经济
大缓和
贝叶斯向量自回归
贝叶斯概率
计量经济学
膨胀(宇宙学)
贝叶斯估计量
向量自回归
贝叶斯推理
货币政策
宏观经济学
统计
物理
数学
理论物理学
作者
Frank Smets,Rafael Wouters
摘要
Using a Bayesian likelihood approach, we estimate a dynamic stochastic general equilibrium model for the US economy using seven macroeconomic time series. The model incorporates many types of real and nominal frictions and seven types of structural shocks. We show that this model is able to compete with Bayesian Vector Autoregression models in out-of-sample prediction. We investigate the relative empirical importance of the various frictions. Finally, using the estimated model, we address a number of key issues in business cycle analysis: What are the sources of business cycle fluctuations? Can the model explain the cross correlation between output and inflation? What are the effects of productivity on hours worked? What are the sources of the “Great Moderation”? (JEL D58, E23, E31, E32)
科研通智能强力驱动
Strongly Powered by AbleSci AI