Structural FECM: cointegration in large-scale structural FAVAR models

Anindya Banerjee, Massimiliano Marcellino, Igor Masten

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
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Abstract

Starting from the dynamic factor model for non-stationary data we derive the
factor-augmented error correction model (FECM) and its moving-average representation.The latter is used for the identication of structural shocks and their propagation mechanisms. We show how to implement classical identication 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 identied permanent real (productivity) and monetary policy shocks.
Original languageEnglish
Pages (from-to)1069-1086
Number of pages18
JournalJournal of Applied Econometrics
Volume32
Issue number6
Early online date3 May 2017
DOIs
Publication statusPublished - 1 Sep 2017

Keywords

  • Dynamic Factor Models
  • Cointegration
  • Structural Analysis
  • Factor-augmented Error Correction Models
  • FAVAR

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