This paper exploits daily infrared images taken from satellites to track economic activity in advanced and emerging countries. We first develop a framework to read, clean, and exploit satellite images. Our algorithm uses the laws of physics (Planck's law) and machine learning to detect the heat...

To forecast an aggregate, we propose adding disaggregate variables, instead of combining forecasts of those disaggregates or forecasting by a univariate aggregate model. New analytical results show the effects of changing coefficients, mis-specification, estimation uncertainty and...

A small labour market model for the six largest euro area countries (Germany, France, Italy, Spain, the Netherlands, Belgium) is estimated in a state -space framework. The model entails, in the long run, four driving forces: a trend labour force component, a trend labour productivity component,...

To forecast an aggregate, we propose adding disaggregate variables, instead of combining forecasts of those disaggregates or forecasting by a univariate aggregate model. New analytical results show the effects of changing coefficients, mis-specification, estimation uncertainty and...

A small labour market model for the six largest euro area countries (Germany, France, Italy, Spain, the Netherlands, Belgium) is estimated in a state -space framework. The model entails, in the long run, four driving forces: a trend labour force component, a trend labour productivity component,...

In this paper we develop a general framework to analyze state space models with timevarying system matrices where time variation is driven by the score of the conditional likelihood. We derive a new filter that allows for the simultaneous estimation of the state vector and of the time-varying...

In this paper we extract latent factors from a large cross-section of commodity prices, including fuel and non-fuel commodities. We decompose each commodity price series into a global (or common) component, block-specific components and a purely idiosyncratic shock. We find that the bulk of the...

This study applies a model averaging approach to conditionally forecast housing investment in the largest euro area countries and the euro area. To account for substantial modelling uncertainty, it estimates many vector error correction models (VECMs) using a wide set of short and long-run...

Outlier detection in high-dimensional datasets poses new challenges that have not been investigated in the literature. In this paper, we present an integrated methodology for the identification of outliers which is suitable for datasets with higher number of variables than observations. Our...

Using comparable survey data from twelve European countries from 1994 to 2001 we investigate households’ attitudes towards mortgage indebtedness. We find that a given debt burden creates much higher distress in countries with fewer mortgage holders relative to countries where a significant...