This paper presents ideas and methods underlying the construction of an indicator that tracks euro area GDP growth but, unlike GDP growth, (i) is updated monthly and almost in real time, and (ii) is free from short-run dynamics. Removal of short-run dynamics from a time series to isolate the...

This paper, along with the companion paper Forni, Hallin, Lippi and Reichlin (1999), introduces a new model-the generalized dynamic factor model-for the empirical analysis of financial and macroeconomic data sets characterized by a large number of observations both cross-section and over time....

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...

This Paper is the result of the Bank of Italy-CEPR project to construct a monthly coincident indicator of the business cycle of the euro area. The index is estimated on the basis of a harmonized data set of monthly statistics of the euro area (951 series) which we constructed from a variety of...

In a situation where agents can only observe a noisy signal of the shock to future economic fundamentals, SVAR models can still be successfully employed to estimate the shock and the associated impulse response functions. Identification is reached by means of dynamic rotations of the reduced...

We introduce noisy information into a standard present value stock price model. Agents receive a noisy signal about the structural shock driving future dividend variations. The resulting equilibrium stock price includes a transitory component — the "noise bubble" — which can be responsible...

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...