We develop an income shock classification taxonomy that classifies income changes into 9 categories based on the magnitude, direction and permamency of the income change. Using 01/2017 - 06/2022 bank transaction data of Belgian employees and workers, we apply this classification on labour income...

Common sense tells that historical data are more informative for the estimation of today's nowcasting models when observed in a similar economic state as today. We operationalise this intuition by proposing a state-based weighted estimation procedure of GDP nowcasting models, in which...

We empirically test the prediction of Pastor, Stambaugh, and Taylor 2020 that green firms can outperform brown firms when climate change concerns strengthen unexpectedly for S&P 500 companies over the period January 2010 - June 2018. To capture unexpected increases in climate change concerns, we...

Policymakers, firms, and investors closely monitor traditional survey-based consumer confidence indicators and treat it as an important piece of economic information. We propose a latent factor model for the vector of monthly survey-based consumer confidence and daily sentiment embedded in...

We propose a parsimonious regime switching model to characterize the dynamics in the volatilities and correlations of US deposit banks' stock returns over 1994-2011. A first innovative feature of the model is that the within-regime dynamics in the volatilities and correlation depend on the shape...

We investigate the effect of market liquidity on equity-collateralized funding accounting for endogeneity. Theory suggests market liquidity can affect funding liquidity in stabilizing and destabilizing manners. Using the average fee on stock loans as a proxy for equity-collateralized funding...

This paper presents variance extraction procedures for univariate time series. The volatility of a times series is monitored allowing for non-linearities, jumps and outliers in the level. The volatility is measured using the height of triangles formed by consecutive observations of the time...

Factor construction methods are widely used to summarize a large panel of variables by means of a relatively small number of representative factors. We propose a novel factor construction procedure that enjoys the properties of robustness to outliers and of sparsity; that is, having relatively...