Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/296344 
Year of Publication: 
2023
Citation: 
[Journal:] Quantitative Economics [ISSN:] 1759-7331 [Volume:] 14 [Issue:] 3 [Year:] 2023 [Pages:] 1021-1058
Publisher: 
The Econometric Society, New Haven, CT
Abstract: 
We estimate sectoral spillovers around the Great Moderation with the help of forecast error variance decomposition tables. Obtaining such tables in high dimensions is challenging because they are functions of the estimated vector autoregressive coefficients and the residual covariance matrix. In a simulation study, we compare various regularization methods on both and conduct a comprehensive analysis of their performance. We show that standard estimators of large connectedness tables lead to biased results and high estimation uncertainty, both of which are mitigated by regularization. To explore possible causes for the Great Moderation, we apply a cross-validated estimator on sectoral spillovers of industrial production in the US from 1972 to 2019. We find that the spillover network has considerably weakened, which hints at structural change, for example, through improved inventory management, as a critical explanation for the Great Moderation.
Subjects: 
VAR models
shrinkage
networks
industrial production
JEL: 
C32
C52
E23
E27
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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