7 citations · 7 across the 4 of their papers we have counts for
7 papers · 1 filter
Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks
Florian Huber, Gary Koop
The shocks which hit macroeconomic models such as Vector Autoregressions (VARs) have the potential to be non-Gaussian, exhibiting asymmetries and fat tails. This consideration moti…
Forecasting US Inflation Using Bayesian Nonparametric Models
Todd E. Clark, Florian Huber, Gary Koop +1
The relationship between inflation and predictors such as unemployment is potentially nonlinear with a strength that varies over time, and prediction errors error may be subject to…
Investigating Growth at Risk Using a Multi-country Non-parametric Quantile Factor Model
Todd E. Clark, Florian Huber, Gary Koop +2
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 functio…
Subspace Shrinkage in Conjugate Bayesian Vector Autoregressions
Florian Huber, Gary Koop
Macroeconomists using large datasets often face the choice of working with either a large Vector Autoregression (VAR) or a factor model. In this paper, we develop methods for combi…
Nowcasting in a Pandemic using Non-Parametric Mixed Frequency VARs
Florian Huber, Gary Koop, Luca Onorante +2
This paper develops Bayesian econometric methods for posterior inference in non-parametric mixed frequency VARs using additive regression trees. We argue that regression tree model…
Bayesian Inference in High-Dimensional Time-varying Parameter Models using Integrated Rotated Gaussian Approximations
Florian Huber, Gary Koop, Michael Pfarrhofer
Researchers increasingly wish to estimate time-varying parameter (TVP) regressions which involve a large number of explanatory variables. Including prior information to mitigate ov…