This paper suggests a term structure model which parsimoniously exploits a broad macroeconomic information set. The model does not incorporate latent yield curve factors, but instead uses the common components of a large number of macroeconomic variables and the short rate as explanatory...

We propose a shadow-rate term structure model for the euro area yield curve from 1999 to mid-2015, when bond yields had turned negative at various maturities. Yields in the model are constrained by a lower bound, but - as a special feature of our specification - the bound is allowed to change...

Standard measures of prices are often contaminated by transitory shocks. This has prompted economists to suggest the use of measures of underlying in?ation to formulate monetary policy and assist in forecasting observed in?ation. Recent work has concentrated on modelling large datasets using...

This paper shows how large-dimensional dynamic factor models are suitable for structural analysis. We establish sufficient conditions for identification of the structural shocks and the associated impulse response functions. In particular, we argue that, if the data follow an approximate factor...

We derive forecast weights and uncertainty measures for assessing the role of individual series in a dynamic factor model (DFM) to forecast euro area GDP from monthly indicators. The use of the Kalman filter allows us to deal with publication lags when calculating the above measures. We find...

We estimate and forecast growth in euro area monthly GDP and its components from a dynamic factor model due to Doz et al. (2005), which handles unbalanced data sets in an efficient way. We extend the model to integrate interpolation and forecasting together with cross-equation accounting...

We propose a new method for multivariate forecasting which combines Dynamic Factor and multivariate GARCH models. The information contained in large datasets is captured by few dynamic common factors, which we assume being conditionally heteroskedastic. After presenting the model, we propose a...

Forecasts from dynamic factor models potentially benefit from refining the data set by eliminating uninformative series. The paper proposes to use prediction weights as provided by the factor model itself for this purpose. Monte Carlo simulations and an empirical application to short-term...

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 paper addresses the issue of measuring the NAIRU for the euro area and assessing the robustness and precision of the obtained estimates. The empirical framework adopted is based on systems combining an Okun-type relationship between cyclical unemployment and the output gap with a Phillips...