Estimating Time-Varying DSGE Models Using Minimum Distance Methods

L. Giraitis, G. Kapetanios, Konstantinos Theodoridis, T. Yates
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引用次数: 14

Abstract

This paper uses kernel methods to estimate a seven variable time-varying (TV) vector autoregressive (VAR) model on the US data set constructed by Smets and Wouters. We use an indirect inference method to map from this TV VAR to time variation in implied Dynamic Stochastic General Equilibrium (DSGE) parameters. We find that many parameters change substantially, particularly those defining nominal rigidities, habits and investment adjustment costs. In contrast to the ‘Great Moderation’ literature our monetary policy parameter estimates suggest that authorities tried to deliver a low and stable inflation from 1975 onwards. However, the severe adverse supply shocks in the 70s could have caused these policies to fail.
用最小距离法估计时变DSGE模型
本文利用核方法对Smets和Wouters构建的美国数据集估计了一个七变量时变向量自回归(VAR)模型。我们使用一种间接推理的方法从这个TV VAR映射到隐含的动态随机一般均衡(DSGE)参数的时间变化。我们发现许多参数发生了实质性的变化,特别是那些定义名义刚度、习惯和投资调整成本的参数。与“大缓和”文献相反,我们的货币政策参数估计表明,自1975年以来,当局试图实现低而稳定的通胀。然而,70年代严重的不利供应冲击可能导致这些政策失败。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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