In this Paper we study identification in dynamic factor models and argue that factor models are better suited than VARs to provide a structural representation of the macroeconomy. Factor models distinguish measurement errors and other idiosyncratic disturbances from structural macroeconomic...

This paper proposes a new way to compute a coincident and a leading index of economic activity. The method provides a unified approach for the selection of the coincident and the leading variables, for averaging them into coincident and leading indexes and for the identification of turning...

Equilibrium business cycle models have typically less shocks than variables. As pointed out by Altug, 1989, and Sargent, 1989, if variables are measured with error, this characteristic implies that the model solution for measured variables has a factor structure. This Paper compares estimation...

This paper analyzes identification conditions, and proposes an estimator, for a dynamic factor model where the idiosyncratic components are allowed to be mutually non-orthogonal. This model, which we call the generalized dynamic factor model, is novel to the literature, and generalizes the...

The Paper uses a large data set, consisting of 447 monthly macroeconomic time series concerning the main countries of the Euro area to simulate out-of-sample predictions of the Euro area industrial production and the harmonized inflation index and to evaluate the role of financial variables in...

This Paper proposes a new forecasting method that exploits information from a large panel of time series. The method is based on the generalized dynamic factor model proposed in Forni, Hallin, Lippi, and Reichlin (2000), and takes advantage of the information on the dynamic covariance structure...

This paper documents the existence of a slowly evolving trend in the dividend-price ratio, dpt, determined by a demographic variable, MY: the middle-aged to young ratio. Deviations of dpt from this long-run component explain transitory but persistent fluctuations in stock market returns. The...

In this paper, we construct a large Bayesian Vector Autoregressive model (BVAR) for the Euro Area that captures the complex dynamic inter-relationships between the main components of the Harmonized Index of Consumer Price (HICP) and their determinants. The model is estimated using Bayesian...

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 for US time series with the most promising existing alternatives, namely, factor...

We propose to use the attractiveness of pooling relatively short time series that display similar dynamics, but without restricting to pooling all into one group. We suggest estimating the appropriate grouping of time series simultaneously along with the group-specific model parameters. We cast...