Dynamic Common Factors in the Presence of Seasonality

• Activity Number: 477
• Type: Contributed
• Date/Time: Wednesday, August 3, 2011 : 8:30 AM to 10:20 AM
• Sponsor: Business and Economic Statistics Section
• Author(s): Fabio Humberto Nieto*+ and Daniel Peña and Dagoberto Saboyá
• Companies: Universidad Nacional de Colombia and Universidad Carlos III de Madrid and Universidad Externado de Colombia
• Keywords: Dynamic common factors ; Multivariate time series ; Seasonality

Abstract

Dynamic common factors, as stochastic processes, have been analyzed under the assumptions that some of them are nonstationary and the others are stationary. Methodologically, this assumption implies that observed time series must be deseasonalized before exploring for common factors in the multivariate time series they conform. Besides the frequent use of determining common factors for getting efficiency in forecasting, they might be used for computing coincident indexes in economy and, from them, leading indexes. It is well known that a deseasonalized time series may exhibit spurious characteristics, specifically, in showing cycles the original data do not contain. In this paper, we address the problem of determining common factors when some of the time series under study are seasonal and this characteristic can be specified by seasonal common factors, in the sense they are seasonal stochastic processes. In this way, one would not need to deseasonalize time series before doing an entertained analysis.