Economics at your fingertips  

Identifying noise shocks

Luca Benati (), Joshua Chan, Eric Eisenstat and Gary Koop ()

Journal of Economic Dynamics and Control, 2020, vol. 111, issue C

Abstract: 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.

Keywords: Noise Shocks; News Shocks; Structural VARs; VARMAs (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Identifying Noise Shocks (2018) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

DOI: 10.1016/j.jedc.2019.103780

Access Statistics for this article

Journal of Economic Dynamics and Control is currently edited by J. Bullard, C. Chiarella, H. Dawid, C. H. Hommes, P. Klein and C. Otrok

More articles in Journal of Economic Dynamics and Control from Elsevier
Bibliographic data for series maintained by Haili He ().

Page updated 2021-01-25
Handle: RePEc:eee:dyncon:v:111:y:2020:i:c:s0165188919301770