Investigating Growth at Risk Using a Multicountry Non-parametric Quantile Factor Model
Clark, Todd E. and Huber, Florian and Koop, Gary and Marcellino, Massimilano and Pfarrhofer, Michael (2023) Investigating Growth at Risk Using a Multicountry Non-parametric Quantile Factor Model. Discussion paper. University of Strathclyde, Glasgow.
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Abstract
We develop a Bayesian non-parametric quantile panel regression model. Within each quantile, the response function is a convex combination of a linear model and a non-linear function, which we approximate using Bayesian Additive Regression Trees (BART). Cross-sectional information at the pth quantile is captured through a conditionally heteroscedastic latent factor. The non-parametric feature of our model enhances flexibility, while the panel feature, by exploiting cross-country information, increases the number of observations in the tails. We develop Bayesian Markov chain Monte Carlo (MCMC) methods for estimation and forecasting with our quantile factor BART model (QF-BART), and apply them to study growth at risk dynamics in a panel of 11 advanced economies.
ORCID iDs
Clark, Todd E., Huber, Florian, Koop, Gary ORCID: https://orcid.org/0000-0002-6091-378X, Marcellino, Massimilano and Pfarrhofer, Michael;-
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Item type: Monograph(Discussion paper) ID code: 91356 Dates: DateEvent28 July 2023PublishedSubjects: Social Sciences > Economic History and Conditions Department: Strathclyde Business School > Economics Depositing user: Pure Administrator Date deposited: 03 Dec 2024 16:00 Last modified: 03 Dec 2024 16:00 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/91356