RT Generic
T1 Factor extraction using Kalman filter and smoothing: this is not just another survey
A1 Poncela Blanco, Maria Pilar
A1 Ruiz Ortega, Esther
A1 Miranda Gualdrón, Karen Alejandra
A2 Universidad Carlos III de Madrid. Departamento de Estadística, 
AB Dynamic Factor Models, which assume the existence of a small number of unobservedlatent factors that capture the comovements in a system of variables, are the main "bigdata" tool used by empirical macroeconomists during the last 30 years. One importanttool to extract the factors is based on Kalman  lter and smoothing procedures that cancope with missing data, mixed frequency data, time-varying parameters, non-linearities,non-stationarity and many other characteristics often observed in real systems of economicvariables. This paper surveys the literature on latent common factors extracted using Kalmanfilter and smoothing procedures in the context of Dynamic Factor Models. Signal extractionand parameter estimation issues are separately analyzed. Identi cation issues are also tackledin both stationary and non-stationary models. Finally, empirical applications are surveyedin both cases.
SN 2387-0303
YR 2020
FD 2020-06-25
LK https://hdl.handle.net/10016/30644
UL https://hdl.handle.net/10016/30644
LA eng
DS e-Archivo
RD 2 may. 2024