Long Memory Factor Model: On Estimation of Factor Memories

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

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)

Goethe University Frankfurt ( email )

Gr├╝neburgplatz 1
Frankfurt am Main, 60323
Germany

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