Discussion of “Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions”

Jouchi Nakajima

Annals of the Institute of Statistical Mathematics, 2020, vol. 72, issue 1, No 2, 33-36

Abstract: Abstract The author focuses on the “decoupling and recoupling” idea that can critically increase both computational and forecasting efficiencies in practical problems for economic and financial data. My discussion is twofold. First, I briefly describe the idea with an example of time-varying vector autoregressions, which are widely used in the context. Second, I highlight the issue of how to assess patterns of simultaneous relationships.

Keywords: Bayesian forecasting; Decouple/recouple; Time-varying vector autoregressions; Multivariate time-series models (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10463-019-00742-2

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