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General Bayesian time-varying parameter VARs for predicting government bond yields

Manfred M. Fischer, Niko Hauzenberger, Florian Huber, Michael Pfarrhofer

arXiv 26 Feb 2021 · Econometrics

arXiv:2102.13393 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Time-varying parameter (TVP) regressions commonly assume that time-variation in the coefficients is determined by a simple stochastic process such as a random walk. While such models are capable of capturing a wide range of dynamic patterns, the true nature of time variation might stem from other sources, or arise from different laws of motion. In this paper, we propose a flexible TVP VAR that assumes the TVPs to depend on a panel of partially latent covariates. The latent part of these covariates differ in their state dynamics and thus capture smoothly evolving or abruptly changing coefficients. To determine which of these covariates are important, and thus to decide on the appropriate state evolution, we introduce Bayesian shrinkage priors to perform model selection. As an empirical application, we forecast the US term structure of interest rates and show that our approach performs well relative to a set of competing models. We then show how the model can be used to explain structural breaks in coefficients related to the US yield curve.

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36
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Joshua CC Chan, Eric Eisenstat, and Rodney Strachan (2020) Reducing the state space dimension in a large TVP-VAR0.81142100%
2Timothy Cogley and Thomas J. Sargent (2005) Drifts and volatilities: Monetary policies and outcomes in the post WWII US0.73732100%
3Francis X Diebold and Canlin Li (2006) Forecasting the term structure of government bond yields0.73732100%
4Giorgio Primiceri (2005) Time varying structural autoregressions and monetary policy0.73732100%
5Christopher A Sims and Tao Zha (2006) Were there regime switches in US monetary policy?0.73732100%
6Carlos M Carvalho, Nicholas G Polson, and James G Scott (2010) The horseshoe estimator for sparse signals0.64422100%
7Gary Koop, Roberto Leon-Gonzalez, and Rodney W Strachan (2009) On the evolution of the monetary policy transmission mechanism0.64422100%
8Thomas Dangl and Michael Halling (2012) Predictive regressions with time-varying coefficients0.51121100%
9Thomas J Sargent and Paolo Surico (2011) Two illustrations of the quantity theory of money: Breakdowns and revivals0.51121100%
10Sylvia Frühwirth-Schnatter and Helga Wagner (2010) Stochastic model specification search for Gaussian and partial non-Gaussian state space models0.51121100%

Showing the top 10 of 36 scored citations.