JSM 2012 Home

JSM 2012 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Online Program Home

Abstract Details

Activity Number: 327
Type: Topic Contributed
Date/Time: Tuesday, July 31, 2012 : 10:30 AM to 12:20 PM
Sponsor: Business and Economic Statistics Section
Abstract - #305296
Title: Semiparametric Dynamic Factor Models for Nonstationary Time Series
Author(s): Michael Eichler*+ and Giovanni Motta
Companies: Maastricht University and Maastricht University
Address: Tongersestraat 53, Maastricht, _, 6211 LM, Netherlands
Keywords: semiparametric ; dynamic factor model ; panel time series ; nonstationarity

Current approaches for fitting dynamic factor models to nonstationary time series are based on dynamic principal components analysis in the frequency domain. These approaches are fully nonparametric and depend strongly on the chosen bandwidths for smoothing over frequency and time. As an alternative, we propose a semiparametric approach in which only parts of the model are allowed to be time-varying. More precisely, we consider two specifications: first, the latent factors admit a dynamic representation with time-varying autoregressive coefficients while the loadings are constant over time. Second, the factor model is stationary while the loadings are time-varying.

Estimation of the model parameters is accomplished by application of the EM algorithm and the Kalman filter. The time-varying parameters are modelled locally by polynomials and estimated by maximizing the likelihood locally. Simulation results show that compared to estimation of the factors by principal components our approach produces superior results in particular for small cross-sectional dimension. We illustrate our approach also applications to real data.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2012 program

2012 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.