In this paper we propose to use the common trends of the Mexican economy in order to predict economic activity one and two steps ahead. We exploit the cointegration properties of the macroeconomic time series, such that, when the series are I(1) and cointegrated, there is a factor...

We adopt a series of shrinkage and factor analytic methodologies to compute nowcasts of the main Finnish turnover indexes, using continuously accumulating firm-level data. We show that the estimates based on large dimensional models provide an accurate and timelier alternative to the ones...

This paper analyses the contribution of survey data, in particular various sentiment indicators, to nowcasts of quarterly euro area GDP. It uses a genuine real-time dataset that is constructed from original press releases in order to transform the actual dataflow into an interpretable flow of...

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...

The authors analyse 149 newly compiled monthly time series on financial market stress conditions in the euro area. With the aid of a factor model they find different sources of financial stress that are important for selecting and preparing the appropriate policy response. The existence of a...

In this paper we propose to use the common trends of the Mexican economy in order to predict economic activity one and two steps ahead. We exploit the cointegration properties of the macroeconomic time series, such that, when the series are I(1) and cointegrated, there is a factor...