An overview of the factor-augmented error-correction model

Anindya Banerjee, Massimiliano Marcellino, Igor Masten

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

4 Citations (Scopus)

Abstract

The Factor-augmented Error-Correction Model (FECM) generalizes the factor-augmented VAR (FAVAR) and the Error-Correction Model (ECM), combining error-correction, cointegration and dynamic factor models. It uses a larger set of variables compared to the ECM and incorporates the long-run information lacking from the FAVAR because of the latter’s specification in differences. In this paper, we review the specification and estimation of the FECM, and illustrate its use for forecasting and structural analysis by means of empirical applications based on Euro Area and US data.
Original languageEnglish
Title of host publicationDynamic Factor Models
EditorsSiem Jan Koopman, Eric Hillebrand
PublisherEmerald
Pages3-41
Number of pages39
Volume35
ISBN (Print)9781785603532
DOIs
Publication statusPublished - 2016

Publication series

NameAdvances in Econometrics
PublisherEmerald
ISSN (Print)0731-9053

Keywords

  • Factor-augmented error correction models
  • FAVAR
  • Dynamic factor models
  • cointegration
  • structural analysis

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