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The identification of dominant macroeconomic drivers: coping with confounding shocks

Alistair Dieppe (), Neville Francis and Gene Kindberg-Hanlon

No 2534, Working Paper Series from European Central Bank

Abstract: We address the identification of low-frequency macroeconomic shocks, such as technology, in Structural Vector Autoregressions. Whilst identification issues with long-run restrictions are well documented, we demonstrate that the recent attempt to overcome said issues using the Max-Share approach of Francis et al. (2014) and Barsky and Sims (2011) has its own shortcomings, primarily that they are vulnerable to bias from confounding non-technology shocks, although less so than long-run specifications. We offer a new spectral methodology to improve empirical identification. This new preferred methodology offers equivalent or improved identification in a wide range of data generating processes and when applied to US data. Our findings on the bias generated by confounding shocks also importantly extends to the identification of dominant business-cycle shocks, which will be a combination of shocks rather than a single structural driver. This can result in a mis-characterization of the business cycle anatomy. JEL Classification: C11, C30, E32

Keywords: confounding shocks; identification; long-horizon and business-cycle shocks (search for similar items in EconPapers)
Date: 2021-04
New Economics Papers: this item is included in nep-ecm and nep-mac
Note: 95834
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