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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...
Persistent link: https://www.econbiz.de/10005667125
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...
Persistent link: https://www.econbiz.de/10005789173
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...
Persistent link: https://www.econbiz.de/10005123887
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...
Persistent link: https://www.econbiz.de/10005136502
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...
Persistent link: https://www.econbiz.de/10005504237
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...
Persistent link: https://www.econbiz.de/10005661541
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...
Persistent link: https://www.econbiz.de/10010328558
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...
Persistent link: https://www.econbiz.de/10011604758
Persistent link: https://www.econbiz.de/10000840658
Persistent link: https://www.econbiz.de/10000770575