Identifying noise shocks

被引：2

作者：

Benati, Luca ^{[1
]}

Chan, Joshua ^{[2
]}

Eisenstat, Eric ^{[3
]}

Koop, Gary ^{[4
]}

机构：

[1] Univ Bern, Dept Econ, Schanzeneckstr 1, CH-3001 Bern, Switzerland

[2] Purdue Univ, Dept Econ, 100 Grant St, W Lafayette, IN 47907 USA

[3] Univ Queensland, Sch Econ, Brisbane, Qld 4072, Australia

[4] Univ Strathclyde, Dept Econ, 199 Cathedral St, Glasgow G4 0QU, Lanark, Scotland

来源：

JOURNAL OF ECONOMIC DYNAMICS & CONTROL | 2020年 / 111卷

基金：

澳大利亚研究理事会;

关键词：

Noise Shocks; News Shocks; Structural VARs; VARMAs; NEWS;

D O I：

10.1016/j.jedc.2019.103780

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

We study identifying restrictions that allow news and noise shocks to be recovered empirically within a Bayesian structural VARMA framework. In population, the identification scheme we consider exactly recovers news and noise shocks. Monte Carlo evidence further demonstrates its excellent performance, as it recovers the key features of the postulated data-generation process-the real-business cycle model of Barsky and Sims (2011) augmented with noise shocks about future total factor productivity (TFP)-with great precision. In an empirical application, evidence suggests that TFP noise shocks play a minor role in macroeconomic fluctuations. (C) 2019 Elsevier B.V. All rights reserved.

引用

页数：17

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