86 citations · 156 across the 36 of their papers we have counts for
10 papers · 1 filter
Real-time Inflation Forecasting Using Non-linear Dimension Reduction Techniques
Niko Hauzenberger, Florian Huber, Karin Klieber
In this paper, we assess whether using non-linear dimension reduction techniques pays off for forecasting inflation in real-time. Several recent methods from the machine learning l…
Capital Flows and the Stabilizing Role of Macroprudential Policies in CESEE
Markus Eller, Niko Hauzenberger, Florian Huber +2
In line with the recent policy discussion on the use of macroprudential measures to respond to cross-border risks arising from capital flows, this paper tries to quantify to what e…
On the equivalence of pathwise mild and weak solutions for quasilinear SPDEs
Gaurav Dhariwal, Florian Huber, Alexandra Neamţu
The main goal of this work is to relate weak and pathwise mild solutions for parabolic quasilinear stochastic partial differential equations (SPDEs). Extending in a suitable way te…
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…
Measuring the Effectiveness of US Monetary Policy during the COVID-19 Recession
Martin Feldkircher, Florian Huber, Michael Pfarrhofer
The COVID-19 recession that started in March 2020 led to an unprecedented decline in economic activity across the globe. To fight this recession, policy makers in central banks eng…
Inference in Bayesian Additive Vector Autoregressive Tree Models
Florian Huber, Luca Rossini
Vector autoregressive (VAR) models assume linearity between the endogenous variables and their lags. This assumption might be overly restrictive and could have a deleterious impact…
Dynamic shrinkage in time-varying parameter stochastic volatility in mean models
Florian Huber, Michael Pfarrhofer
Successful forecasting models strike a balance between parsimony and flexibility. This is often achieved by employing suitable shrinkage priors that penalize model complexity but a…
Dynamic Shrinkage Priors for Large Time-varying Parameter Regressions using Scalable Markov Chain Monte Carlo Methods
Niko Hauzenberger, Florian Huber, Gary Koop
Time-varying parameter (TVP) regression models can involve a huge number of coefficients. Careful prior elicitation is required to yield sensible posterior and predictive inference…
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…
A multi-country dynamic factor model with stochastic volatility for euro area business cycle analysis
Florian Huber, Michael Pfarrhofer, Philipp Piribauer
This paper develops a dynamic factor model that uses euro area (EA) country-specific information on output and inflation to estimate an area-wide measure of the output gap. Our mod…