Estimating non-stationary common factors: Implications for risk sharing
In this paper, we analyze and compare the finite sample properties of alternative factor extraction procedures in the context of non-stationary Dynamic Factor Models (DFMs). On top of considering procedures already available in the literature, we extend the hybrid method based on the combination of principal components and Kalman filter and smoothing algorithms to non-stationary models. We show that, if the idiosyncratic noises are non-stationary, procedures based on extracting the factors using the non-stationary original series work better
than those based on differenced variables. We apply the methodology to the analysis of cross-border risk-sharing fitting non-stationary DFM to aggregate GDP and consumption of the set of 21 OECD industrialized countries. The goal is to check if international risk sharing
is a short or long-run issue.
CORONA Francisco;
PONCELA BLANCO Maria Del Pilar;
RUIZ Esther;
2019-02-01
SPRINGER
JRC109413
0927-7099 (online),
https://link.springer.com/article/10.1007%2Fs10614-018-9875-9,
https://publications.jrc.ec.europa.eu/repository/handle/JRC109413,
10.1007/s10614-018-9875-9 (online),
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