Author(s):
Joshua C.C. Chan, Economics Discipline Group, UTS Business School, University of Technology, Sydney, Eric Eisenstat,University of Queensland, Luca Benati, University of Bern, Gary Koop,University of Strathclyde
Date of publication: 2018
Working paper number: 41
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.