@inbook{5e8dd8068e0247a79bcda0488d8356f6,
title = "An overview of the factor-augmented error-correction model",
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{\textquoteright}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.",
keywords = "Factor-augmented error correction models, FAVAR, Dynamic factor models, cointegration, structural analysis",
author = "Anindya Banerjee and Massimiliano Marcellino and Igor Masten",
year = "2016",
doi = "10.1108/S0731-905320150000035001",
language = "English",
isbn = "9781785603532",
volume = "35",
series = "Advances in Econometrics",
publisher = "Emerald",
pages = "3--41",
editor = "Koopman, {Siem Jan} and Eric Hillebrand",
booktitle = "Dynamic Factor Models",
}