Long Memory Factor Model: On Estimation of Factor Memories

61 Pages Posted: 22 Feb 2017 Last revised: 13 Feb 2018

See all articles by Ying Lun Cheung

Ying Lun Cheung

Capital University of Economics and Business - International School of Economics and Management

Date Written: January 16, 2018

Abstract

This paper considers the estimation of factor memories in the context of a high-dimensional factor model. Both factors and idiosyncratic error terms are potentially non-stationary fractional integrated processes. We propose a three-step procedure to estimate the latent factors. We then apply the fully-extended local Whittle (FELW) estimator of Abadir et al. (2007) to compute factor memories. This estimator is consistent and satisfies the same normal CLT, as if the factors are observed. Finite sample performance of the proposed procedure is evaluated in a simulation study. Finally, we apply the proposed estimator on a large dataset of macroeconomic variables.

Keywords: approximate factor models, principal components, long memory, fractional integration

JEL Classification: C14, C22, C38

Suggested Citation

Cheung, Ying Lun, Long Memory Factor Model: On Estimation of Factor Memories (January 16, 2018). Available at SSRN: https://ssrn.com/abstract=2921952 or http://dx.doi.org/10.2139/ssrn.2921952

Ying Lun Cheung (Contact Author)

Capital University of Economics and Business - International School of Economics and Management ( email )

Beijing
China

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
104
Abstract Views
501
rank
267,623
PlumX Metrics