Estimating large-dimensional connectedness tables: The great moderation through the lens of sectoral spillovers

Felix Brunner, Ruben Hipp

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
11 Downloads (Pure)

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.

Original languageEnglish
Pages (from-to)1021-1058
Number of pages38
JournalQuantitative Economics
Volume14
Issue number3
DOIs
Publication statusPublished - Jul 2023

Keywords

  • C32
  • C52
  • E23
  • E27
  • industrial production
  • networks
  • shrinkage
  • VAR models

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