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Identifying Noise Shocks

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

No 41, Working Paper Series from Economics Discipline Group, UTS Business School, University of Technology, Sydney

Abstract: We make four contributions to the ‘news versus noise’ literature: (I) We provide a new identification scheme which, in population, exactly recovers news and noise shocks. (II) We show that our scheme is not vulnerable to Chahrour and Jurado’s (2018) criticism about the observational equivalence of news and noise shocks, which uniquely holds if the econometrician only observes a fundamental, and agents’ expectations about it. By contrast, we show that observational equivalence breaks down when the econometrician observes macroeconomic variables encoding information about the signal (and therefore about news and noise shocks), because they are chosen by agents conditional on all information, including the signal itself. (III) We propose a new econometric methodology for implementing our identification scheme, and we show, via a Monte Carlo study, that it has an excellent performance. (IV) We provide several empirical applications of our identification scheme and econometric methodology. Our results uniformly suggest that, contrary to previous findings in the literature, noise shocks play a minor role in macroeconomic fluctuations.

Pages: 41 pages
Date: 2018-01-01
New Economics Papers: this item is included in nep-ecm and nep-mac
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