TY  - CHAP
AB  - Abstract We generalise the spectral EM algorithm for dynamic factor models in Fiorentini, Galesi, and Sentana (2014) to bifactor models with pervasive global factors complemented by regional ones. We exploit the sparsity of the loading matrices so that researchers can estimate those models by maximum likelihood with many series from multiple regions. We also derive convenient expressions for the spectral scores and information matrix, which allows us to switch to the scoring algorithm near the optimum. We explore the ability of a model with a global factor and three regional ones to capture inflation dynamics across 25 European countries over 1999–2014.
VL  - 35
SN  - 978-1-78560-353-2, 978-1-78560-352-5/0731-9053
DO  - 10.1108/S0731-905320150000035006
UR  - https://doi.org/10.1108/S0731-905320150000035006
AU  - Fiorentini Gabriele
AU  - Galesi Alessandro
AU  - Sentana Enrique
PY  - 2016
Y1  - 2016/01/01
TI  - Fast ML Estimation of Dynamic Bifactor Models: An Application to European Inflation
T2  - Dynamic Factor Models
T3  - Advances in Econometrics
PB  - Emerald Group Publishing Limited
SP  - 215
EP  - 282
Y2  - 2024/09/21
ER  -