This paper outlines the recently developed method for assessing the trend level in employment rates adopted by Norges Bank. The approach employs a Bayesian VAR to decompose disaggregated employment data into trend and cyclical components, using quarterly labor market data on 30 demographic...

This paper introduces a Bayesian Quantile Factor Augmented VAR (BQFAVAR) to examine the asymmetric effects of monetary policy throughout the business cycle. Monte Carlo experiments demonstrate that the model effectively captures non-linearities in impulse responses. Analysis of aggregate...

We study the application of approximate mean field variational inference algorithms to Bayesian panel VAR models in which an exchangeable prior is placed on the dynamic parameters and the residuals follow either a Gaussian or a Student-t distribution. This reduces the estimation time of possibly...

This paper explores the evolution of non-working time in Spain over recent years by analysing the results of two surveys conducted by the National Statistics Institute: the Quarterly Survey on Labor Costs and the Labor Force Survey. Using time series models and intervention analysis, potential...

What drives the recent inflation surge? To answer this question, one must decompose inflation fluctuations into the contribution of structural shocks. We document how whimsical such a historical shock decomposition can be in standard vector autoregressive (VAR) models. We show that the...

In 1936, John Maynard Keynes proposed that emotions and instincts are pivotal in decision-making, particularly for investors. Both positive and negative moods can influence judgments and decisions, extending to economic and financial choices. Intuitions, emotional states, and biases...

We document that about 33% of the core inflation basket in the euro area is sensitive to monetary policy shocks. We assess potential theoretical mechanisms driving the sensitivity. Our results suggest that items of a discretionary nature, as reflected in a higher share in the consumption baskets...

We provide a versatile nowcasting toolbox that supports three model classes (dynamic factor models, large Bayesian VAR, bridge equations) and offers methods to manage data selection and adjust for Covid-19 observations. The toolbox aims at simplifying two key tasks: creating new nowcasting...