no code implementations • 16 Feb 2024 • Niko Hauzenberger, Massimiliano Marcellino, Michael Pfarrhofer, Anna Stelzer
We propose and discuss Bayesian machine learning methods for mixed data sampling (MIDAS) regressions.
no code implementations • 18 Jan 2024 • Luca Barbaglia, Lorenzo Frattarolo, Niko Hauzenberger, Dominik Hirschbuehl, Florian Huber, Luca Onorante, Michael Pfarrhofer, Luca Tiozzo Pezzoli
Timely information about the state of regional economies can be essential for planning, implementing and evaluating locally targeted economic policies.
no code implementations • 25 Jul 2022 • Florian Huber, Luca Onorante, Michael Pfarrhofer
In this paper, we forecast euro area inflation and its main components using an econometric model which exploits a massive number of time series on survey expectations for the European Commission's Business and Consumer Survey.
no code implementations • 25 Feb 2022 • Stefan Griller, Florian Huber, Michael Pfarrhofer
We investigate the consequences of legal rulings on the conduct of monetary policy.
no code implementations • 7 Oct 2021 • Todd E. Clark, Florian Huber, Gary Koop, Massimiliano Marcellino, Michael Pfarrhofer
We develop a Bayesian non-parametric quantile panel regression model.
no code implementations • 8 Mar 2021 • Martin Feldkircher, Florian Huber, Gary Koop, Michael Pfarrhofer
Panel Vector Autoregressions (PVARs) are a popular tool for analyzing multi-country datasets.
1 code implementation • 5 Mar 2021 • Michael Pfarrhofer
This paper proposes methods for Bayesian inference in time-varying parameter (TVP) quantile regression (QR) models featuring conditional heteroskedasticity.
no code implementations • 26 Feb 2021 • Manfred M. Fischer, Niko Hauzenberger, Florian Huber, Michael Pfarrhofer
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.
no code implementations • 9 Nov 2020 • Niko Hauzenberger, Michael Pfarrhofer, Luca Rossini
In this paper we propose a time-varying parameter (TVP) vector error correction model (VECM) with heteroskedastic disturbances.
1 code implementation • 28 Aug 2020 • Florian Huber, Gary Koop, Luca Onorante, Michael Pfarrhofer, Josef Schreiner
This paper develops Bayesian econometric methods for posterior inference in non-parametric mixed frequency VARs using additive regression trees.
no code implementations • 4 Apr 2018 • Florian Huber, Tamás Krisztin, Michael Pfarrhofer
In this paper, we assess the impact of climate shocks on futures markets for agricultural commodities and a set of macroeconomic quantities for multiple high-income economies.