This paper documents the existence of a significant forecast error on crude oil futures, particularly evident since the mid-1990s, which is negative on average and displays a non-trivial cyclical component (risk premium). We show that the forecast error on oil futures could have been explained...

The process through which economic policy is conceived and decided cannot be simply described as the optimisation of a well-defined loss function subject to the constraints provided by a model of the economy. Even ignoring the forbidding difficulties of eliciting a stable and explicit loss...

The forecasting profession, especially when producing forecasts intended to support economic policy, does not currently enjoy a good reputation. Complaints are sometimes voiced about its lack of scientific discipline, which in turn implies that the forecast results may be viewed as arbitrary. At...

En este artículo se presenta un nuevo enfoque para la estimación de modelos de factores de gran dimensión cuyas cargas de factores están sujetas a cambios markovianos de régimen. Dicho enfoque consiste en una extensión del filtro de regresión de tres pasos lineal a casos en los cuales los...

We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...

We consider simple methods to improve the growth nowcasts and forecasts obtained by mixed frequency MIDAS and UMIDAS models with a variety of indicators during the Covid-19 crisis and recovery period, such as combining forecasts across various specifications for the same model and/or across...

The paper addresses the issue of forecasting a large set of variables using multivariate models. In particular, we propose three alternative reduced rank forecasting models and compare their predictive performance with the most promising existing alternatives, namely, factor models, large scale...

We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...