Structural FECM: Cointegration in large-scale structural FAVAR models
Anindya Banerjee,
Massimiliano Marcellino and
Igor Masten
No 9858, CEPR Discussion Papers from C.E.P.R. Discussion Papers
Abstract:
Starting from the dynamic factor model for non-stationary data we derive the factor-augmented error correction model (FECM) and, by generalizing the Granger representation theorem, its moving-average representation. The latter is used for the identification of structural shocks and their propagation mechanism. Besides discussing contemporaneous restrictions along the lines of Bernanke et al. (2005), we show how to implement classical identification schemes based on long-run restrictions in the case of large panels. The importance of the error-correction mechanism for impulse response analysis is analysed by means of both empirical examples and simulation experiments. Our results show that the bias in estimated impulse responses in a FAVAR model is positively related to the strength of the error-correction mechanism and the cross-section dimension of the panel. We observe empirically in a large panel of US data that these features have a substantial effect on the responses of several variables to the identified real shock.
Keywords: Cointegration; Dynamic factor models; Factor-augmented error correction models; Favar; Structural analysis (search for similar items in EconPapers)
JEL-codes: C32 E17 (search for similar items in EconPapers)
Date: 2014-03
New Economics Papers: this item is included in nep-ecm and nep-mac
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Journal Article: Structural FECM: Cointegration in large‐scale structural FAVAR models (2017)
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