1 citations · 2 across the 7 of their papers we have counts for
7 papers
Nowcasting the euro area with social media data
Konstantin Boss, Luigi Longo, Luca Onorante
Using a state-of-the-art large language model, we extract forward-looking and context-sensitive signals related to inflation and unemployment in the euro area from millions of Redd…
Nowcasting economic activity in European regions using a mixed-frequency dynamic factor model
Luca Barbaglia, Lorenzo Frattarolo, Niko Hauzenberger +5
Timely information about the state of regional economies can be essential for planning, implementing and evaluating locally targeted economic policies. However, European regional a…
Forecasting euro area inflation using a huge panel of survey expectations
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 Euro…
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…
Fast and Flexible Bayesian Inference in Time-varying Parameter Regression Models
Niko Hauzenberger, Florian Huber, Gary Koop +1
In this paper, we write the time-varying parameter (TVP) regression model involving K explanatory variables and T observations as a constant coefficient regression model with KT ex…
Inducing Sparsity and Shrinkage in Time-Varying Parameter Models
Florian Huber, Gary Koop, Luca Onorante
Time-varying parameter (TVP) models have the potential to be over-parameterized, particularly when the number of variables in the model is large. Global-local priors are increasing…
Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam's Window
Luca Onorante, Adrian E. Raftery
Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially a…