Gaussian Process Vector Autoregressions and Macroeconomic Uncertainty

Niko Hauzenberger, Florian Huber, Massimiliano Marcellino and Nico Petz

No 17646, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: We develop a non-parametric multivariate time series model that remains agnostic on the precise relationship between a (possibly) large set of macroeconomic time series and their lagged values. The main building block of our model is a Gaussian process prior on the functional relationship that determines the conditional mean of the model, hence the name of Gaussian process vector autoregression (GP-VAR). A flexible stochastic volatility specification is used to provide additional flexibility and control for heteroskedasticity. Markov chain Monte Carlo (MCMC) estimation is carried out through an efficient and scalable algorithm which can handle large models. The GP-VAR is illustrated by means of simulated data and in a forecasting exercise with US data. Moreover, we use the GP-VAR to analyze the effects of macroeconomic uncertainty, with a particular emphasis on time variation and asymmetries in the transmission mechanisms.

JEL-codes: C11 C14 C32 (search for similar items in EconPapers)
Date: 2022-11
References: Add references at CitEc
Citations:

Downloads: (external link)
https://cepr.org/publications/DP17646 (application/pdf)
CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org

Related works:
Journal Article: Gaussian Process Vector Autoregressions and Macroeconomic Uncertainty (2025)
Working Paper: Gaussian Process Vector Autoregressions and Macroeconomic Uncertainty (2022)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cpr:ceprdp:17646

Ordering information: This working paper can be ordered from
https://cepr.org/publications/DP17646

Access Statistics for this paper

More papers in CEPR Discussion Papers from C.E.P.R. Discussion Papers Centre for Economic Policy Research, 33 Great Sutton Street, London EC1V 0DX.
Bibliographic data for series maintained by ().