Dynamic factor models: does the specification matter?

e-Archivo Repository

Show simple item record

dc.contributor.author Miranda Gualdrón, Karen Alejandra
dc.contributor.author Poncela, Pilar
dc.contributor.author Ruiz Ortega, Esther
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística
dc.date.accessioned 2021-03-23T19:30:36Z
dc.date.available 2021-03-23T19:30:36Z
dc.date.issued 2021-03-23
dc.identifier.issn 2387-0303
dc.identifier.uri http://hdl.handle.net/10016/32210
dc.description.abstract Dynamic Factor Models (DFMs), which assume the existence of a small number of unobserved underlying factors capturing the comovements in large systems of variables, are very popular among empirical macroeconomists to reduce dimension and to extract factors with an economic interpretation. Factors can be extracted using either non-parametric Principal Components (PC) or parametric Kalman filter and smoothing (KFS) procedures, with the former being computationally simpler and robust against misspecification and the latter being efficient if the specification is correct and coping in a natural way with missing and mixed-frequency data, time-varying parameters, non-linearities and non-stationarity among many other stylized facts often observed in real systems of economic variables. This paper analyses the empirical consequences on factor estimation and forecasting of using alternative extraction procedures and estimators of the DFM parameters under various sources of potential misspecification. In particular, we consider factor extraction when assuming different number of factors and different factor dynamics. The factors are extracted from a popular data base of US macroeconomic variables that has been widely analyzed in the literature without consensus about the most appropriate model speciffication. We show that this lack of consensus is ony marginally cruzial when it comes to factor extraction but it matters when the objective is forecasting.
dc.relation.ispartofseries Working paper Statistics and Econometrics
dc.relation.ispartofseries 21-03
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Em Algorithm
dc.subject.other Kalman Filter
dc.subject.other Principal Components
dc.subject.other State-Space Model
dc.title Dynamic factor models: does the specification matter?
dc.type workingPaper
dc.relation.projectID Gobierno de España. PID2019-108079GB-C21
dc.relation.projectID Gobierno de España. PID2019-108079GB- C22
dc.identifier.uxxi DT/0000001889
 Find Full text

Files in this item

*Click on file's image for preview. (Embargoed files's preview is not supported)

The following license files are associated with this item:

This item appears in the following Collection(s)

Show simple item record