Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/272982 
Year of Publication: 
2022
Series/Report no.: 
Bank of Canada Staff Working Paper No. 2022-38
Publisher: 
Bank of Canada, Ottawa
Abstract: 
We propose a new empirical framework that jointly decomposes the conditional variance of economic time series into a common and a sector-specific uncertainty component. We apply our framework to a large dataset of disaggregated industrial production series for the US economy. Our results indicate that common uncertainty and uncertainty linked to non- durable goods both recorded their pre-pandemic global peaks during the 1973-75 recession. In contrast, durable goods uncertainty recorded its pre-pandemic peak during the global financial crisis of 2008-09. Vector autoregression exercises identify unexpected changes in durable goods uncertainty as drivers of downturns that are both economically and statistically significant, while unexpected hikes in non-durable goods uncertainty are expansionary. Our findings suggest that: (i) uncertainty is heterogeneous at a sectoral level; and (ii) durable goods uncertainty may drive some business cycle effects typically attributed to aggregate uncertainty.
Subjects: 
Business fluctuations and cycles
Econometric and statistical methods
Monetarypolicy and uncertainty
JEL: 
E32
E44
C51
C55
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.