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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
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Working Paper: Identifying Noise Shocks (2018) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:eee:dyncon:v:111:y:2020:i:c:s0165188919301770

DOI: 10.1016/j.jedc.2019.103780

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

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