Author: CHEUNG Ying Lun, Goethe University Frankfurt
Presented at: Vienna Workshop on High-Dimensional Time Series in Macroeconomics and Finance, 2017
This paper considers the estimation of factor memories in the context of a high-dimensional factor model. We model both factors and idiosyncratic error terms as potentially nonstationary fractional integrated processes. We propose a three-step procedure to estimate latent factors. We then apply the fully-extended local Whittle (FELW) estimator of Abadir et al. (2007) to compute factor memories. We show that 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 our estimator to a large dataset of macroeconomic variables.